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METHODOLOGY FOR
PREDICTING DEPENDABILITY MEASURES OF
SWARM STRUCTURES OF UNMANNED AERIAL
VEHICLES OF AGRICULTURAL APPLICATION |
35-53 |
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A.A. Kostiuk, V.E. Tsvetkov, P.S.
Korolev, S.N. Polesskiy |
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This paper presents a methodology for
predicting dependability measures of
swarm structures of unmanned aerial
vehicles used in agriculture. The main
attention is paid to the development of
mathematical models for assessing the
dependability of hardware, software, and
communication systems in drone swarms.
Two types of UAVs are considered in the
paper: DJI Phantom 4 RTK (for crop
monitoring) and Tevel Aerobotics (for
automated harvesting). The developed
methodology improves the accuracy of
dependability prediction of UAV swarm
structures, which helps to optimize
their maintenance and increase the
efficiency of their application in
agriculture. The developed mathematical
model for predicting the dependability
of swarm structures of agricultural UAVs
includes a combination of hardware and
software components and communication
systems.
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Cite: A.A. Kostiuk, V.E. Tsvetkov, P.S.
Korolev, S.N. Polesskiy METHODOLOGY FOR
PREDICTING DEPENDABILITY MEASURES OF
SWARM STRUCTURES OF UNMANNED AERIAL
VEHICLES OF AGRICULTURAL APPLICATION.
Reliability: Theory & Applications.
2025, September 3(86): 35-53, DOI: https://doi.org/10.24412/1932-2321-2025-386-35-53
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A COMPARATIVE ANALYSIS
OF POWER ISHITA DISTRIBUTION EXPLORING
ITS SIGNIFICANT CONTRIBUTION AND
PRACTICAL APPLICATIONS |
54-66 |
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Rashid A. Ganaie, Manzoor A. Khanday,
Dilawar A. Bhat, Yudhishther Singh Bagal |
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This research presents the development
of a novel statistical model termed the
weighted power Ishita distribution. The
study delves into its fundamental
structural properties, offering a
comprehensive theoretical foundation.
The parameters of proposed distribution
are meticulously estimated through the
maximum likelihood estimation method,
ensuring robust and reliable results. To
validate its applicability and
demonstrate its superiority, the model
is evaluated using three real-world
lifetime data sets, highlighting its
efficacy and potential for practical
applications.
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Cite: Rashid A. Ganaie, Manzoor A.
Khanday, Dilawar A. Bhat, Yudhishther
Singh Bagal A COMPARATIVE ANALYSIS OF
POWER ISHITA DISTRIBUTION EXPLORING ITS
SIGNIFICANT CONTRIBUTION AND PRACTICAL
APPLICATIONS. Reliability: Theory &
Applications. 2025, September 3(86):
54-66, DOI: https://doi.org/10.24412/1932-2321-2025-386-54-66
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THE DEVELOPMENT OF
RISK-BASED THINKING PRINCIPLES AT A
MACHINE-BUILDING ENTERPRISE UNDER
CONDITIONS OF INDUSTRY 4.0 |
67-77 |
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Yaroslav Vavilin |
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The article deals with the problem of
formal introduction of risk-based
thinking features in machine-building
production under conditions of Industry
4.0 together with the expansion of the
use of digital technologies. The
research aims to address the following
objectives: to analyze the necessity and
influence of risk management
implementation within the organization's
quality management system; to determine
the levels required for realizing
risk-based thinking; to develop a
methodological foundation for
integrating risk-based thinking
considering Industry 4.0 elements; to
perform a comparative analysis of the
proposed model with known risk
management systems. The study employs
well-established methods of
process-based approaches (Deming-Shewhart
cycle) and systems analysis. The authors
make an attempt to formalize the work on
ensuring the proper use of risk and
capability management tools from the
perspective of a system analysis and
process approach. Works related to risk
management at the stages of the
Deming-Shewhart cycle are highlighted
and the levels and components of the
machine-building production system model
that are subject to analysis are
determined. The task of introducing
risk-based thinking in quality
management systems of machine- building
enterprises is critical due to the
increasing complexity of products,
increasing consumer demands and the need
to ensure increased safety. Risk
analysis makes it possible to identify
potential threats to product quality in
advance, minimize the consequences of
defects, reduce error correction costs
and increase the competitiveness of the
enterprise in the market.
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Cite: Yaroslav Vavilin THE DEVELOPMENT
OF RISK-BASED THINKING PRINCIPLES AT A
MACHINE-BUILDING ENTERPRISE UNDER
CONDITIONS OF INDUSTRY 4.0. Reliability:
Theory & Applications. 2025, September
3(86): 67-77, DOI: https://doi.org/10.24412/1932-2321-2025-386-67-77
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APPLICATION OF WEIGHT
MEASURE ORDERING FOR INTUITIONISTIC
FUZZY CRITICAL PATH ANALYSIS |
78-89 |
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S. Priyadharshini, G. Deepa, S.
Ramprasath |
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The intuitionistic fuzzy critical path
problem is a frequent and important
challenge in network optimization,
particularly in the planning and
management of complex projects. However,
the traditional critical path approach
often fails to accurately reflect
real-world scenarios. To address this,
we have developed a critical path
strategy within an intuitionistic fuzzy
framework. In this study, the critical
path is determined using a ranking
algorithm, where the edge weights are
modeled as triangular intuitionistic
fuzzy numbers (ITFN). We have introduced
definitions for ranking strategies that
help identify the intuitionistic fuzzy
critical path. Additionally, a proposed
criticality degree measures that
significance of each activity. Examples
are provided to illustrate the proposed
strategy, and the simulation results of
the ranking techniques are also
presented.
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Cite: S. Priyadharshini, G. Deepa, S.
Ramprasath APPLICATION OF WEIGHT MEASURE
ORDERING FOR INTUITIONISTIC FUZZY
CRITICAL PATH ANALYSIS. Reliability:
Theory & Applications. 2025, September
3(86): 78-89, DOI: https://doi.org/10.24412/1932-2321-2025-386-78-89
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A RANKING FUNCTION
APPROACH BASED ON CENTROID FOR
GENERALIZED HEXAGONAL FUZZY NUMBERS TO
SOLVE FUZZY MULTI-OBJECTIVE
TRANSPORTATION PROBLEMS |
90-106 |
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Ramakant Sharma, Sohan Lal Tyagi |
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In a real-world scenario, the decision
maker is unsure about the precise value
of transportation parameters due to
uncontrolled factors such as fuel prices,
weather conditions, product availability,
and requirements. Therefore, o fuzzy
numbers are used to handle these
uncertainties. This Paper aims to find
an efficient solution to fuzzy
multi-objective transportation problems
(FMOTP) where all parameters (objective
functions, availabilities, requirements)
are given in the form of generalized
hexagonal fuzzy numbers. In the Proposed
approach, FMOTP is transformed into
Fuzzy Single-Objective Transportation
Problems (FSOTP) using the geometric
mean technique. A new ranking function
based on the centroid and in-center
point method for hexagonal fuzzy numbers
defuzzifies the FSOTP into a Crisp
Single-Objective Transportation Problem
(CSOTP). The optimal solution for the
transformed CSOTP is obtained using the
proposed approach based on the
zero-entry cell method. Using the
optimal solution of CSOTP the fuzzy
efficient solution of FMOTP is obtained.
Additionally, two numerical problems are
solved to elaborate the Proposed
approach, and results are compared with
other existing methods. A comparison and
analysis of the results show that the
proposed approach provides a more
optimized solution for FMOTP. This
approach is easily applicable to
real-life transportation problems in
which decision-makers are unsure about
the exact value of parameters.
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Cite: Ramakant Sharma, Sohan Lal Tyagi
A RANKING FUNCTION APPROACH BASED ON
CENTROID FOR GENERALIZED HEXAGONAL FUZZY
NUMBERS TO SOLVE FUZZY MULTI-OBJECTIVE
TRANSPORTATION PROBLEMS. Reliability:
Theory & Applications. 2025, September
3(86): 90-106, DOI: https://doi.org/10.24412/1932-2321-2025-386-90-106
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A STATISTICAL
FRAMEWORK FOR ENHANCING PROCESS CONTROL
AND RELIABILITY USING AUTOENCODERS
RANDOM SURVIVAL FORESTS AND NHPP
MODELING |
107-125 |
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|
P. Sricharani, P. Satya Shekar Varma, M.
V. Lavanya |
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Statistical Process Control (SPC) plays
a critical role in ensuring the
reliability and quality of high-grade
products. This study introduces two
advanced machine learning methods to
enhance SPC by integrating Auto encoders
for anomaly detection and Random
Survival Forests (RSF) for failure
prediction. The Autoencoder model is
employed to monitor real-time sensor
data, learning the normal patterns of
product quality and identifying
deviations that indicate potential
quality issues. By flagging anomalies
when product performance metrics diverge
from expected thresholds, the
autoencoder helps to adjust SPC limits
dynamically, improving responsiveness to
emerging quality concerns. Additionally,
RSF is used to predict the likelihood of
product failure over time, based on
historical failure data and process
parameters. This predictive approach
enables proactive interventions to
prevent quality issues before they occur,
enhancing long-term product
dependability. Together, these machine
learning methods create a comprehensive
framework for real-time monitoring and
failure prediction, providing a more
adaptive and data driven approach to
quality control. The integration of Auto
encoders and RSF into the SPC
methodology significantly advances the
precision and effectiveness of product
reliability assessment, offering a
powerful tool for maintaining
high-quality standards in manufacturing
processes.
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Cite: P. Sricharani, P. Satya Shekar
Varma, M. V. Lavanya A STATISTICAL
FRAMEWORK FOR ENHANCING PROCESS CONTROL
AND RELIABILITY USING AUTOENCODERS
RANDOM SURVIVAL FORESTS AND NHPP
MODELING. Reliability: Theory &
Applications. 2025, September 3(86):
107-125, DOI: https://doi.org/10.24412/1932-2321-2025-386-107-125
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A BAYESIAN APPROACH TO
RELIABILITY ANALYSIS IN THE
STRESS-STRENGTH MODEL WITH WEIGHTED
EXPONENTIAL DISTRIBUTIONS CONSIDERING
FUZZINESS |
126-139 |
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Alka Yadav, Satyanshu Kumar Upadhyay |
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The paper considers a Bayesian approach
to the analysis of reliability in a
stress-strength model when both stress
and strength follow a weighted
exponential distribution. The main focus
of the paper considers a situation when
the available data incorporate fuzziness.
The situations when stress and strength
distributions have common shape
parameters and also when they have
different shape and scale parameters are
entertained separately. The entire
analysis is done using the Bayes
paradigm using weak proper priors for
the model parameters. Since the
resulting posteriors are not available
in analytically closed form, the paper
uses the recourse of Markov chain Monte
Carlo simulation technique. Finally, a
numerical illustration is provided based
on real data examples. The results are
found to be satisfactory.
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Cite: Alka Yadav, Satyanshu Kumar
Upadhyay A BAYESIAN APPROACH TO
RELIABILITY ANALYSIS IN THE
STRESS-STRENGTH MODEL WITH WEIGHTED
EXPONENTIAL DISTRIBUTIONS CONSIDERING
FUZZINESS. Reliability: Theory &
Applications. 2025, September 3(86):
126-139, DOI: https://doi.org/10.24412/1932-2321-2025-386-126-139
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SYSTEMATIC FAILURES IN
FUNCTIONAL SAFETY AND THE PROBABILITY
MEASURE |
140-148 |
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|
Hendrik Schabe |
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In this paper the probability measure is
discussed. The point of interest is,
whether probabilistic models are stable
under different conditions and if they
can be used further on, when conditions
change. Systematic failures, as
described in many standards of
functional safety, play a role regarding
this problem. Reducing systematic
failures also means, to keep
probabilistic calculus working. However,
systematic failures have not been
studied systematically regarding the
question to keep the probability measure.
An outline is given on the connection
between systematic failures and the
possibility to use probability calculus
in technical problems in exploitation
situations, where data from e.g. lab
experiments are extrapolated to use
conditions.
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Cite: Hendrik Schabe SYSTEMATIC
FAILURES IN FUNCTIONAL SAFETY AND THE
PROBABILITY MEASURE. Reliability: Theory
& Applications. 2025, September 3(86):
140-148, DOI: https://doi.org/10.24412/1932-2321-2025-386-140-148
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DEVELOPMENT OF A NEW
CURRENT LIMITING SYSTEM WITH AUTOMATIC
REGULATION OF CUT-OFF CURRENT |
149-154 |
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R.Z. Sultanov, N.A. Aliyev, G.A. Aliyeva |
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The article considers the problem of
ensuring reliable operation of DC
electric drives under short- term
overloads, when the installed power of
the electric motor is limited. It is
shown that the use of traditional
current cutoff units does not allow for
the effective use of the maximum
permissible overload capacity of the
motor when changing the reference speed.
The dependence of the permissible
overload current on the rotation speed
is analyzed, and the limitations of the
existing control schemes are identified.
In this paper, the existing schemes of
automated electric drives equipped with
traditional current cutoff units are
considered and their main disadvantages
are identified. As a solution, a current
limiting system with automatic
regulation of the cutoff current is
proposed, aimed at increasing the
reliability and energy efficiency of
adjustable electric drives. The key
feature of the proposed system is to
adapt the cutoff current value depending
on the rotation speed of the motor,
which allows dynamically matching the
electromechanical characteristics of the
drive with the permissible overload
curve of the motor. A current limiting
circuit for a DC electric drive is
proposed, in which the cutoff current
setting is automatically changed
depending on the value of the specified
speed. The circuit ensures full use of
the maximum permissible overload
capacity of the electric motor at all
values of the setting voltage.
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Cite: R.Z. Sultanov, N.A. Aliyev, G.A.
Aliyeva DEVELOPMENT OF A NEW CURRENT
LIMITING SYSTEM WITH AUTOMATIC
REGULATION OF CUT-OFF CURRENT.
Reliability: Theory & Applications.
2025, September 3(86): 149-154, DOI: https://doi.org/10.24412/1932-2321-2025-386-149-154
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A NEW MIN-MAX RANKED
SET SAMPLING SCHEME WITH UNEQUAL SAMPLE
SIZES |
155-171 |
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O. Rahimi Dehcheraghi, S.M.T.K.
MirMostafaee |
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In this paper, a new type of ranked set
sampling scheme with unequal sample
sizes called the new min-max ranked set
sampling scheme with unequal sample
sizes, is proposed to expedite the
sampling process and reduce costs by
utilizing fewer data compared to the
existing ranked set sampling plans with
unequal sample sizes, such as the
minimum ranked set sampling scheme with
unequal samples. We study the parameter
estimation for the exponential
distribution using the maximum
likelihood and Bayesian methods based on
the new scheme. The Metropolis-Hastings
strategy is implemented to derive the
approximate Bayesian estimates of the
parameter under two loss functions. A
simulation study is conducted, from
which the effectiveness of the new
scheme can be observed compared to the
simple random sampling scheme and the
minimum ranked set sampling scheme with
unequal samples. A real data set is also
analyzed. Finally, The paper ends with
some remarks.
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Cite: O. Rahimi Dehcheraghi, S.M.T.K.
MirMostafaee A NEW MIN-MAX RANKED SET
SAMPLING SCHEME WITH UNEQUAL SAMPLE
SIZES. Reliability: Theory &
Applications. 2025, September 3(86):
155-171, DOI: https://doi.org/10.24412/1932-2321-2025-386-155-171
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ANALYSIS OF MAPj, PH°/PH[,
PH°/1 RETRIAL INVENTORY QUEUE, TWO WAY
COMMUNICATION, (S, S) REPLENISHMENT
POLICY, NEGATIVE ARRIVAL, WORKING
BREAKDOWN AND REPAIR |
172-186 |
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G. Ayyappan, V. Ganesan |
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The retrial inventory queueing model
with two-way communication, the (s, S)
replenishment strategy, negative arrival,
working breakdown, and repair are all
topics that are discussed in this paper.
Our assumption is that the arrival is a
Markovian arrival process and that a
server is the entity that is responsible
for providing phase type services. When
there is a positive inventory and the
server is idle, the customer who arrives
is instantly attended to their needs. In
the event that this instance does not
occur, the customer who is arriving will
be moved to orbit, and a retrial
customer from orbit will join afterwards
if the server is idle and has positive
inventory. When the inventory level is
positive, the server will make outgoing
calls that follow phase type
distribution during the idle period. If
the inventory level is zero, the server
will continue to stay idle. A negative
arrival may occur while the server is
providing service. Since the server is
experiencing a breakdown, the consumer
will experience slow service at this
time. After the slow service ends, the
server will immediately begin the repair
procedure, which follows a phase-type
distribution. The policy of (s,S) is
utilised to replenish the items. By
employing the matrix analytic method, we
are able to derive the steady state
probability vector. Additionally, we
address the busy period, performance
measurements, and cost analysis, in
addition to providing some numerical
examples.
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Cite: G. Ayyappan, V. Ganesan ANALYSIS
OF MAPj, PH°/PH[, PH°/1 RETRIAL
INVENTORY QUEUE, TWO WAY COMMUNICATION,
(S, S) REPLENISHMENT POLICY, NEGATIVE
ARRIVAL, WORKING BREAKDOWN AND REPAIR.
Reliability: Theory & Applications.
2025, September 3(86): 172-186, DOI: https://doi.org/10.24412/1932-2321-2025-386-172-186
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GROK'S ROLE IN
TRANSFORMING COMMUNICATION FOR DISASTER
RISK MANAGEMENT |
187-191 |
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|
Renat R. Khaydarov |
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The increasing prevalence of natural
hazards, exacerbated by climate change
and urbanization, underscores the
urgency of effective disaster risk
management (DRM) to safeguard
communities and infrastructure.
Technical assessments, laden with
specialized terminology, often hinder
stakeholder engagement, particularly
among non-specialists critical to
decision-making processes. This study
explores the prospective applications of
Grok, an AI model by xAI, in enhancing
DRM through its advanced natural
language processing capabilities. Grok
can translate complex multi-hazard risk
evaluations, develop tailored
educational content, and support
real-time early warning systems,
fostering inclusive communication. The
research aims to evaluate Grok's
efficacy in bridging technical and
non-technical domains, promoting
informed urban planning and disaster
preparedness. Ultimately, this research
lays the groundwork for future empirical
studies on Al-driven DRM innovations.
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Cite: Renat R. Khaydarov GROK'S ROLE IN
TRANSFORMING COMMUNICATION FOR DISASTER
RISK MANAGEMENT. Reliability: Theory &
Applications. 2025, September 3(86):
187-191, DOI: https://doi.org/10.24412/1932-2321-2025-386-187-191
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METHODOLOGY FOR
DETERMINING TYPICAL SCENARIOS OF TOTAL
ELECTRICITY GENERATION BY GREEN SOURCES
REDUCING THE RISK OF DISRUPTION OF
BALANCE RELIABILITY |
192-205 |
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|
Rahmanov Nariman Rahman, Guliyev
Huseyngulu Bayram, Ibrahimov Famil
Shamil |
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The article proposes a methodology for
identifying scenarios for aggregate
electricity generation by renewable
sources, such as wind and solar power
plants, located in geographically
diverse regions of the area with
different climatic and weather
conditions. To cover the demand of
electric power systems, it is rational
to use these green sources with
complementarity from generation when
planning load modes, as well as to
reduce the risk of balance reliability
of power systems. To determine the
scenarios of aggregate generation of the
used green sources, a cluster analysis
is used based on the clustering of
medoids using real-time measurements of
wind speed, solar radiation and ambient
temperature performed for all regions of
the considered area where all green
sources of electricity in the form of
wind and solar power plants are
installed. Clusters of these sources and
loads are established separately and
jointly. For each scenario of generation
and planned growth in demand of the
power system, the volume of additional
capacity of green sources is estimated.
The proposed methodology was tested on
the example of the power system of
Azerbaijan. The study found that, in
order to reduce the risk of disruption
to the system's balance reliability,
scenarios of combined generation from
wind farms located in the northern
regions adjacent to the Caspian Sea with
electricity generation from solar farms
located in the southwestern regions of
the country provide a more reliable way
to increase the share of wind and solar
generation in covering the planned
demand growth compared to scenarios
based on the separate use of these green
energy sources.
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Cite: Rahmanov Nariman Rahman, Guliyev
Huseyngulu Bayram, Ibrahimov Famil
Shamil METHODOLOGY FOR DETERMINING
TYPICAL SCENARIOS OF TOTAL ELECTRICITY
GENERATION BY GREEN SOURCES REDUCING THE
RISK OF DISRUPTION OF BALANCE
RELIABILITY. Reliability: Theory &
Applications. 2025, September 3(86):
192-205, DOI: https://doi.org/10.24412/1932-2321-2025-386-192-205
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REDUCING RENTAL COSTS
IN TWO-STAGE HYBRID FSSP: BRANCH AND
BOUND VS. HEURISTIC APPROACHES |
206-216 |
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Kanika Gupta, Deepak Gupta, Sonia Goel |
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|
This paper proposes a Branch and Bound (BB)
based heuristic to solve a two-stage
hybrid Flow Shop Scheduling Problem (HFSSP),
incorporating practical constraints such
as machine rental costs, transportation
time, and job weightage. The scheduling
environment includes multiple parallel
machines at the first stage, where each
job can be processed on any one machine,
followed by a single rented machine at
the second stage. To effectively model
uncertainty in processing times,
triangular fuzzy numbers are used.
Additionally, transportation time
between stages and job weightage are
integrated into the model to reflect
realistic industrial conditions. The
proposed BB algorithm systematically
explores the space of feasible job
sequences, pruning non-promising
branches to derive an optimal or
near-optimal schedule under the given
constraints. Its performance is
benchmarked against two widely used
heuristic approaches—NEH and GRASP-NEH—focusing
on minimizing total elapsed time and
rental cost of the second-stage machine.
Experimental results indicate that the
BB approach consistently outperforms the
heuristic methods, particularly in
reducing rental costs and providing
better control over the utilization of
the rented resource. While heuristic
methods offer computational speed, they
often compromise on cost efficiency and
precision in handling fuzzy parameters.
Overall, the study demonstrates the
effectiveness of the BB method as a
robust and efficient alternative for
solving complex scheduling problems,
especially in scenarios where minimizing
rental costs is a critical objective.
The integration of fuzzy processing
times, transportation delays, and job
priorities further enhances the
practical relevance of the proposed
approach.
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Cite: Kanika Gupta, Deepak Gupta, Sonia
Goel REDUCING RENTAL COSTS IN TWO-STAGE
HYBRID FSSP: BRANCH AND BOUND VS.
HEURISTIC APPROACHES. Reliability:
Theory & Applications. 2025, September
3(86): 206-216, DOI: https://doi.org/10.24412/1932-2321-2025-386-206-216
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ON THE BURR TYPE IV
DISTRIBUTION APPLIED TO LIFETIME
SURVIVAL DATA |
217-228 |
|
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|
Claire Joy G. Mariquit, Bernadette F.
Tubo |
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|
|
This study presents the Burr type IV (Burrjy)
distribution, which is one of the twelve
continuous distributions within the Burr
family. The paper thoroughly evaluates
its properties and applications in
survival analysis. Key distributional
characteristics such as survival, hazard,
quantile, cumulative distribution, and
probability density functions are
derived. Density plots are simulated to
illustrate common patterns, including
J-shaped, U-shaped, and reversed
J-shaped forms, frequently observed in
engineering and reliability contexts.
The applicability of the Burrjy
distribution is demonstrated through
three real-life datasets, each
exhibiting distinct density shapes. The
findings affirm the flexibility and
robustness of the Burrjy distribution in
modeling a variety of data shapes,
underscoring its potential for broader
applications in survival analysis and
related fields.
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Cite: Claire Joy G. Mariquit,
Bernadette F. Tubo ON THE BURR TYPE IV
DISTRIBUTION APPLIED TO LIFETIME
SURVIVAL DATA. Reliability: Theory &
Applications. 2025, September 3(86):
217-228, DOI: https://doi.org/10.24412/1932-2321-2025-386-217-228
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A NON- MARKOVIAN
RETRIAL QUEUE WITH NON PERSISTENT
CUSTOMERS, GENERAL RETRIAL TIMES ALONG
WITH REOCCURRING CUSTOMERS |
229-237 |
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|
S. Palaniammal, K. Kumar, R.Keerthana |
|
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|
A non-Markovian retrial queue with non
persistent customers, general retrial
times along with reoccurring customers
is taken into concern in this place
study. In this model, the retrial
periods for reoccurring customers have
an exponential distribution, while all
the service periods and retrial periods
for transitory customers are pretended
to follow a general distribution. The
PGF for the total amount of customers
and the average amount of customers in
the invisible waiting region is acquired
by applying the supple-mentary variable
method. We compute the waiting period
delivery. Out of attention, special
cases are conferred. Numerical outcomes
are reveals.
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Cite: S. Palaniammal, K. Kumar,
R.Keerthana A NON- MARKOVIAN RETRIAL
QUEUE WITH NON PERSISTENT CUSTOMERS,
GENERAL RETRIAL TIMES ALONG WITH
REOCCURRING CUSTOMERS. Reliability:
Theory & Applications. 2025, September
3(86): 229-237, DOI: https://doi.org/10.24412/1932-2321-2025-386-229-237
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RELIABILITY OF
ELECTRICAL MACHINES VIA POWER LOSS
MODELING IN MATLAB |
238-248 |
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Sara Alimamedova, Saida Kerimova |
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The article discusses a reliable
mathematical approach to calculating
power losses in electrical equipment,
which is a critical component in the
design, analysis, and optimization of
electric power systems. Ensuring
accurate loss estimation requires
detailed modeling of equipment
parameters such as rated power, voltage,
current, resistance, and material
properties that influence energy
dissipation. For alternating current
systems, it is particularly important to
consider the interaction of active and
reactive components, as well as the
losses occurring in conductors, magnetic
circuits, and other elements. The
application of proven mathematical
models enables engineers to evaluate
system efficiency and operational
stability under different scenarios.
MATLAB tools and algorithms play a key
role in automating these calculations,
allowing for precise simulations across
a wide range of load conditions, voltage
levels, and equipment configurations.
This not only improves the accuracy of
loss assessments but also supports
optimization of design parameters to
ensure long-term reliability, energy
efficiency, and cost-effectiveness of
electrical machines and systems.
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Cite: Sara Alimamedova, Saida Kerimova
RELIABILITY OF ELECTRICAL MACHINES VIA
POWER LOSS MODELING IN MATLAB.
Reliability: Theory & Applications.
2025, September 3(86): 238-248, DOI: https://doi.org/10.24412/1932-2321-2025-386-238-248
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RELIABILITY ANALYSIS
AND PERFORMANCE OPTIMIZATION OF A
2-OUT-OF-4 REDUNDANT SYSTEM USING RPGT
AND METAHEURISTIC ALGORITHMS |
249-256 |
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Shakuntla Singla, Shilpa Rani, Diksha
Mangla |
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In this paper focuses on the reliability
analysis and performance optimization of
a 2-out-of-4 redundant system, modeled
using the Regenerative Point Graphical
Technique (RPGT). The study aims to
evaluate system behavior under various
failure and repair rate conditions and
to determine optimal parameters that
enhance system reliability and
availability. The system consists of
four units A, B, C, and D arranged in a
2-out-of-4 configuration, meaning the
system continues to function as long as
at least two units are operational. A
state-space model is developed, where
each state corresponds to a distinct
combination of operational, failed, and
repair conditions of these units. The
transitions between these states are
governed by exponentially distributed
failure and repair processes, and are
represented using a directed graph
structure. Transition probabilities are
derived from these time-dependent
exponential distributions, allowing
precise evaluation of system behavior.
To enhance the system's performance,
three metaheuristic optimization
algorithms — Cuckoo Search Algorithm (CSA),
Particle Swarm Optimization (PSO), and
Genetic Algorithm (GA)-are employed.
These algorithms are applied to optimize
key system parameters: failure rates (A)
and repair rates (p). The objective is
to maximize the Mean Time to System
Failure (MTSF) and steady-state
availability, and to minimize the
expected number of inspections required
by the repair personnel. The comparative
analysis of optimization results reveals
the relative effectiveness of each
algorithm. PSO consistently provides the
highest values for MTSF and availability,
indicating stronger performance in
identifying optimal solutions. CSA also
performs well, showing close results to
PSO. GA, while effective, yields
comparatively lower reliability indices.
The outcomes demonstrate how advanced
optimization techniques can be
successfully integrated with RPGT-based
modeling to develop a detailed and
practical understanding of complex
redundant systems. These insights
support better maintenance planning,
enabling organizations to improve
reliability and reduce downtime in
industrial, communication, and critical
control systems. This methodology can be
extended to other system configurations
and industries, making it a valuable
tool in the field of reliability
engineering and operational research
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Cite: Shakuntla Singla, Shilpa Rani,
Diksha Mangla RELIABILITY ANALYSIS AND
PERFORMANCE OPTIMIZATION OF A 2-OUT-OF-4
REDUNDANT SYSTEM USING RPGT AND
METAHEURISTIC ALGORITHMS. Reliability:
Theory & Applications. 2025, September
3(86): 249-256, DOI: https://doi.org/10.24412/1932-2321-2025-386-249-256
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CENSORED COUNT DATA
REGRESSION MODELS: NUMBER OF CAESAREAN
SECTION DELIVERIES USING INTEGRATED
NESTED LAPLACE APPROXIMATION |
257-269 |
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Srinu Setti, B. Muniswamy |
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Count data depicts the frequency of an
occurrence within a specific time frame.
Consider the frequency of caesarean
operations that women undergo during
their lives. Almost every academic field,
including management, economics,
medicine, and industrial organizations,
relies on count data. Count data is
extensively utilized across various
fields, including marketing, public
health, and biomedical science. This
study aims to estimate the posterior
means, variances, or quantiles of the
NCSD for women aged 15 to 49 in Andhra
Pradesh, India, using the RCPRM and
RCNBRM methodologies. The RCPRM and
RCNBRM are used to determine the optimal
fit. The secondary dataset NFHS-5 is
used for the study. This research
utilizes INLA to model the NCSD.
Subsequently, it analyzed delivery
patterns among pregnant women.
Information criteria DIC and WAIC are
utilized to compare for the best fit.
The DIC values 4608.60 and 4593.90 of
RCNBRM are less than the DIC values
4864.74 and 4860.68 of RCPRM. Thus, from
the results, it is inferred that RCNBRM
is the best fit for NCSD and that Breech
Presentation, the present age of the
respondent, High Blood Pressure, Child
is Twin, Prolonged Labour, Education
Level, and Heart Disease are significant
determinants of the NCSD. Therefore,
government policymakers need to consider
these variables while making healthcare
policies for women aged 15 to 49 years
who are of childbearing age.
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Cite: Srinu Setti, B. Muniswamy
CENSORED COUNT DATA REGRESSION MODELS:
NUMBER OF CAESAREAN SECTION DELIVERIES
USING INTEGRATED NESTED LAPLACE
APPROXIMATION. Reliability: Theory &
Applications. 2025, September 3(86):
257-269, DOI: https://doi.org/10.24412/1932-2321-2025-386-257-269
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FIXED POINT THEOREMS
IN TRICOMPLEX VALUED CONTROLLED METRIC
SPACES |
270-278 |
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Shivani Chourasiya, Kavita Shrivastava |
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Throughout the years, scholars have
broadened traditional fixed point
theories to include more intricate
structures like tricomplex valued metric
spaces, aiming to tackle issues in
multidimensional and hyper-complex
contexts. While there is a rising
interest in tricomplex valued spaces,
the current literature addressing fixed
point theorems in these areas presents
several limitations. The existing
research highlights numerous
shortcomings; thus, this article employs
innovative types of contraction mappings
via a control function to illustrate
fixed point theorems in tricomplex
valued controlled metric spaces. These
findings enhance the understanding of
fixed point theory and pave the way for
new applications in more complex and
diverse mathematical frameworks.
Consequently, our study fosters progress
in the field, establishing a strong
basis for future research and potential
uses across various scientific and
engineering fields.
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Cite: Shivani Chourasiya, Kavita
Shrivastava FIXED POINT THEOREMS IN
TRICOMPLEX VALUED CONTROLLED METRIC
SPACES. Reliability: Theory &
Applications. 2025, September 3(86):
270-278, DOI: https://doi.org/10.24412/1932-2321-2025-386-270-278
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BAYESIAN ESTIMATION OF
POISSON-COMPOUNDED EXPONENTIAL TYPE
DISTRIBUTION UNDER DIFFERENT LOSS
FUNCTIONS |
279-288 |
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Na Elah, Peer Bilal Ahmad |
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Poisson moment exponential distribution
is an important distribution and has
gained special attention recently. It
plays role in various fields, mostly in
actuarial sciences. Thus its parametric
estimation becomes important thing to do.
The classical approach using the maximum
likelihood method is the most used way
to estimate the parameters of a
distribution. In this paper, we
considered the Bayesian approach to
estimate the parameter of the
distribution using beta prior which is a
conjugate prior. The Bayes estimate for
the parameter is obtained under Squared
Error Loss Function (SELF) which is a
symmetric loss function, Weighted SELF (WSELF)
and Entropy Loss Function (ELF). Through
a simulation study, the comparison is
made on the performance of Bayes
estimate under these loss functions with
respect to Bias and Mean Square Error (MSE).
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Cite: Na Elah, Peer Bilal Ahmad
BAYESIAN ESTIMATION OF
POISSON-COMPOUNDED EXPONENTIAL TYPE
DISTRIBUTION UNDER DIFFERENT LOSS
FUNCTIONS. Reliability: Theory &
Applications. 2025, September 3(86):
279-288, DOI: https://doi.org/10.24412/1932-2321-2025-386-279-288
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OPTIMIZING FUZZY
DETERIORATING INVENTORY MODEL WITH TIME
DEPENDENT DEMAND AND PARTIAL BACKLOGGING
UNDER RESALABLE RETURNS |
289-299 |
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Kapil Dave, Tanuj Kumar |
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This paper investigates with the
development of a fuzzy inventory model
with timevarying demand, deterioration
and backlogging with resalable returns.
The returns rate, demand and backlogging
parameters are taken as trapezoidal
fuzzy numbers. Numerical example is
given to validate the proposed
mathematical model which has been
developed for determining the optimal
cycle time and optimal total inventory
cost and profit. Sensitivity analysis is
also carried out to explore the effect
of changes in the optimal solution with
respect to change in various parameters.
The aim of this paper is to develop
inventory policies that minimize the
total cost so that to get the maximum
total profit in both crisp and fuzzy
modeling, and comparison of crisp and
fuzzy models. Our study focuses on
de-fuzzifying the total cost using the
signed distance method and comparing it
with the crisp model. This inventory
model incorporates fuzzy demand and
constant holding cost per unit item
under the reasonable return policy while
considering the impact of deterioration
as a linearly increasing function of
time. The retailer allows its
unsatisfactory costumers to return their
products. We assume that the return
product will be sold at the same price.
Customers are allowed to return the
product during any phase of the length
of the replenishment cycle. The retailer
does not return the full amount to its
customers for the returned goods. He
offers 80% of the initial amount of the
product. The number of returns are
assumed to be proportional to demand.
The demand is dependent on time. Partial
backlogging is an important issue in the
inventory theory which is related how to
deal with the unfulfilled demand that
occurs due to the shortage of stock. In
real practice some customers prefers to
wait for backorder during the shortage
time and some turns to buy from other
sellers. The waiting time period for
next replenishment determine whether the
backlogging would be accepted or not.
During the shortage period the longer
the waiting time is, the smaller is the
backlogging rate would be. So
backlogging rate is a variable that
depends on the waiting time for next
replenishment.
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Cite: Kapil Dave, Tanuj Kumar
OPTIMIZING FUZZY DETERIORATING INVENTORY
MODEL WITH TIME DEPENDENT DEMAND AND
PARTIAL BACKLOGGING UNDER RESALABLE
RETURNS. Reliability: Theory &
Applications. 2025, September 3(86):
289-299, DOI: https://doi.org/10.24412/1932-2321-2025-386-289-299
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A COMPARATIVE ANALYSIS
OF RESPONSE SURFACE METHODOLOGY IN
LINEAR PROGRAMMING |
300-309 |
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Mushtaq A. Lone, S. A. Mir, R.
Vijaykrishnaraj, Showkat Ahmad Bhat,
Aafaq A. Rather, Raeesa Bashir, Manzoor
A. Khanday, Aamir Majeed Parray |
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A linear mathematical programming
approach has been employed to tackle the
problem of land allocation in this
comparative study. One design of
experiment technique used in creating
new processes and improving their
efficiency is response surface approach.
Different search methods have been
employed in this study to identify the
best distribution of agricultural land.
The results of all formulated
mathematical programming problem are
obtained by using R software and
different R functions like
mexchalgorithmO and qconalgorithm (),
argumants to these problems are bl, b2,
b3 were developed. Furthermore, the
Branch and Bound method has been
utilized to provide the proper integer
solution when the problem's solution
turns out to be non-integer.
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Cite: Mushtaq A. Lone, S. A. Mir, R.
Vijaykrishnaraj, Showkat Ahmad Bhat,
Aafaq A. Rather, Raeesa Bashir, Manzoor
A. Khanday, Aamir Majeed Parray A
COMPARATIVE ANALYSIS OF RESPONSE SURFACE
METHODOLOGY IN LINEAR PROGRAMMING.
Reliability: Theory & Applications.
2025, September 3(86): 300-309, DOI: https://doi.org/10.24412/1932-2321-2025-386-300-309
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REGRESSION WITH
VOLATILE ERRORS IN THE PRESENCE OF
MEASUREMENT ERRORS |
310-321 |
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Anna Thomas, Nimitha John |
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This study explores the estimation and
testing of regression models with
volatile errors when measurement errors
are present. The presence of measurement
error in models with heteroscedastic
disturbances, such as those following an
autoregressive conditional
heteroscedasticity (ARCH) or Generalized
ARCH (GARCH) structure, can lead to
biased estimates and misleading
inferences. To address this, we develop
an estimation framework that accounts
for both heteroscedasticity and
mismeasured observations, ensuring
consistent and asymptotically normal
parameter estimates. We estimate the
parameters using corrected score
estimation and weighted linear
regression, which effectively mitigate
the impact of measurement error and
hetroscedasticity. Additionally, we
perform a Likelihood Ratio (LR) test to
assess the significance of measurement
errors in regression models with
volatile errors. Through Monte Carlo
simulations, we analyze the bias and
efficiency of traditional estimators and
demonstrate the robustness of our
proposed approach. Finally, the
methodology is applied to real-life
economic and financial data,
illustrating its practical relevance and
effectiveness in empirical research. The
findings contribute to improving
statistical inference in models where
measurement error and volatility coexist,
ensuring more reliable and accurate
parameter estimation.
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Cite: Anna Thomas, Nimitha John
REGRESSION WITH VOLATILE ERRORS IN THE
PRESENCE OF MEASUREMENT ERRORS.
Reliability: Theory & Applications.
2025, September 3(86): 310-321, DOI: https://doi.org/10.24412/1932-2321-2025-386-310-321
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RISK-BASED THINKING
AND MEASUREMENT UNCERTAINTY: ADDRESSING
ISO/IEC 17025 CHALLENGES WITH MODERN
TOOLS |
322-329 |
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Rashid Mammadov |
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ISO/IEC 17025, the internationally
recognized standard for the competence
of testing and calibration laboratories,
fundamentally embeds risk-based thinking
(RBT) as a cornerstone for achieving and
maintaining the reliability of
measurement results and the robust
management of measurement uncertainty.
This article critically examines the
synergistic application of RBT to
proactively address the inherent and
often complex challenges associated with
quantifying and controlling measurement
uncertainty. It aims to provide
laboratories with practical, actionable
insights into leveraging modern tools
and methodologies that are not only
compliant with ISO/IEC 17025
requirements but also enhance
operational effectiveness. By exploring
a spectrum of advanced statistical
techniques (such as Monte Carlo
simulations and Bayesian approaches),
the integration of sophisticated digital
tools (including TIMS, specialized
uncertainty software, and data analytics),
and the adoption of innovative
operational practices, this study
delineates a clear roadmap. The ultimate
goal is to empower laboratories to
bolster confidence in their measurement
outcomes, ensure unimpeachable
metrological traceability, stringently
adhere to regulatory and customer
compliance, and foster a culture of
continuous improvement in their quality
management systems.
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Cite: Rashid Mammadov RISK-BASED
THINKING AND MEASUREMENT UNCERTAINTY:
ADDRESSING ISO/IEC 17025 CHALLENGES WITH
MODERN TOOLS. Reliability: Theory &
Applications. 2025, September 3(86):
322-329, DOI: https://doi.org/10.24412/1932-2321-2025-386-322-329
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AN INTEGRATED APPROACH
TO ENSURING THE RELIABILITY OF POWER
TRANSMISSION LINES IN THE CONTEXT OF
DIGITAL ENERGY |
330-338 |
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I.N. Rahimli, N.A. Ganiyeva |
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In the context of the rapid development
of digital technologies and their
large-scale implementation in various
sectors of the economy, the energy
industry is also entering a phase of
deep digital transformation. One of the
key areas of this transformation is
increasing the reliability and
manageability of the energy
infrastructure, in particular, power
transmission lines (PTL), which are the
main element of the electricity
transmission and distribution system.
Modern challenges, such as the
increasing load on the power grid,
changing climate conditions and the need
to integrate distributed energy sources,
require new approaches to reliability
management. This paper discusses the key
elements of digital transformation,
including the use of intelligent
monitoring systems, the Internet of
Things (IoT), big data analysis and
artificial intelligence for diagnostics
and forecasting the technical condition
of power transmission lines. The need
for a comprehensive strategy combining
technical, organizational and
information measures is substantiated.
Recommendations are presented for the
implementation of digital solutions in
the practice of operating power lines in
order to increase their fault tolerance,
prompt response to incidents and the
overall efficiency of the power system.
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Cite: I.N. Rahimli, N.A. Ganiyeva AN
INTEGRATED APPROACH TO ENSURING THE
RELIABILITY OF POWER TRANSMISSION LINES
IN THE CONTEXT OF DIGITAL ENERGY.
Reliability: Theory & Applications.
2025, September 3(86): 330-338, DOI: https://doi.org/10.24412/1932-2321-2025-386-330-338
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IMPROVING THE
RELIABILITY OF DISTRICT HEATING SYSTEMS
AT CHP PLANTS UNDER VARIABLE THERMAL
LOADS |
339-344 |
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G.K. Abdullayeva, R.K. Karimova, A.L.
Bakhtiyarov |
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District heating systems powered by
Combined Heat and Power (CHP) plants are
critical for delivering thermal energy
to residential, industrial, and
municipal consumers. However, the
variability of thermal load—driven by
daily and seasonal demand fluctuations—poses
significant challenges to system
reliability. This paper presents a
methodology for evaluating the
reliability of such systems under
dynamic thermal conditions. By combining
deterministic modeling of thermal load
profiles with a stochastic failure
analysis of key components, the study
performs a year-long simulation with
hourly resolution. A time-dependent
failure rate model is introduced,
correlating failure intensity with the
rate of change in thermal demand,
thereby accounting for the mechanical
and thermal stress experienced by pumps,
valves, pipelines, and heat exchangers.
Simulation results reveal that while
modern CHP equipment has high baseline
reliability, rapid thermal load
transitions notably increase the
likelihood of failures. These findings
highlight the necessity of predictive
maintenance strategies and adaptive
control mechanisms. The proposed
framework contributes to the development
of resilient and smart district heating
infrastructures capable of sustaining
reliable operation under increasingly
complex load dynamics.
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Cite: G.K. Abdullayeva, R.K. Karimova,
A.L. Bakhtiyarov IMPROVING THE
RELIABILITY OF DISTRICT HEATING SYSTEMS
AT CHP PLANTS UNDER VARIABLE THERMAL
LOADS. Reliability: Theory &
Applications. 2025, September 3(86):
330-338, DOI: https://doi.org/10.24412/1932-2321-2025-386-339-344
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AN INTEGRATED APPROACH
TO ENHANCING THE RELIABILITY OF
SUBSTATION POWER SUPPLY SYSTEMS |
345-353 |
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Rahila Muradova |
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The reliability of substation power
supply systems is a critical factor in
ensuring the stability and uninterrupted
operation of modern power grids. This
paper examines advanced quantitative
failure analysis methods that
incorporate physical degradation
processes, component interdependencies,
and time-dependent failure
characteristics. An integrated approach
is proposed, combining structural
redundancy, digital condition monitoring,
thermal management, and predictive
maintenance strategies. Modeling and
statistical analysis confirm that
implementing these comprehensive
measures can increase system
availability to 0.999 and reduce failure
rates by 25- 40%. The methodology is
applicable to both new substation
designs and upgrades of existing
infrastructure, supporting improved
technical reliability and economic
efficiency in operation.
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Cite: Rahila Muradova AN INTEGRATED
APPROACH TO ENHANCING THE RELIABILITY OF
SUBSTATION POWER SUPPLY SYSTEMS.
Reliability: Theory & Applications.
2025, September 3(86): 345-353, DOI: https://doi.org/10.24412/1932-2321-2025-386-345-353
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KRISHNAV-P
DISTRIBUTION AND ITS BIOMEDICAL
APPLICATION |
354-366 |
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Praseeja C. B., Prasanth C. B. |
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This paper introduces a novel class of
distributions, termed the KrishNav-P
distribution (KNPD), developed through
the application of a weighted
distribution technique to the baseline
Fav-Jerry distribution. The statistical
properties of the KNPD are rigorously
analyzed, and parameter estimation is
performed using the maximum likelihood
estimation method. To evaluate the
practical applicability and performance
of the proposed distribution, it is
applied to a real-world dataset
consisting of weight loss measurements (in
kilograms) from 77 secondary school
students aged 12 to 15 in the Thrissur
District, Kerala. The data, collected
between January and June 2021, pertain
to students who experienced weight loss
following a COVID-19 infection and
tested the goodness of fit and the
superiority of the distribution over the
baseline and other existing
distributions are also demonstrated.
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Cite: Praseeja C. B., Prasanth C. B.
KRISHNAV-P DISTRIBUTION AND ITS
BIOMEDICAL APPLICATION. Reliability:
Theory & Applications. 2025, September
3(86): 354-366, DOI: https://doi.org/10.24412/1932-2321-2025-386-354-366
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OPTIMIZING PATHFINDING:
A NOVEL ALGORITHM FOR GRAPH THEORY |
367-380 |
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Aijaz Ahmad Magray, Ajjaz Maqbool Dar,
Firdous Ahmad, Aafaq A. Rather, R.
Vijaykrishnaraj, D. Vedavathi Saraja,
Syed M. Parveen, Raeesa Bashir |
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In this paper, a new proposed algorithm
called the Pentacode-algorithm is
successfully designed and implemented to
solve the space and time problems
associated with previous algorithms.
Several parameters, such as Shortest
Distance (SD), Time to Search Shortest
Distance (TSSD), and Loss of Information
Packets (LIP) have been checked and
verified using the proposed algorithm.
The simulation results achieved from the
MATLAB tool authenticate the correct
functionality of the proposed
Pentacode-algorithm. Advance
improvements have been proved in the
proposed algorithm in terms of the space
search and time issues. In addition,
First-Node-Die (FND), Half-Node-Die (HND)
and Last- Node-Die (LND) are determined
in our results. The comparative results
have shown that the Pentacode-algorithm
is more proficient than the previous
algorithm. This Pentacode-algorithm can
be applied to warless communication
systems, network routing and protocol
multidirectional transmission and
Quantum computing research.
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Cite: Aijaz Ahmad Magray, Ajjaz Maqbool
Dar, Firdous Ahmad, Aafaq A. Rather, R.
Vijaykrishnaraj, D. Vedavathi Saraja,
Syed M. Parveen, Raeesa Bashir
OPTIMIZING PATHFINDING: A NOVEL
ALGORITHM FOR GRAPH THEORY. Reliability:
Theory & Applications. 2025, September
3(86): 367-380, DOI: https://doi.org/10.24412/1932-2321-2025-386-367-380
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ANALYSING STRESS
STRENGTH RELIABILITY OF LIFE TEST ON
AEROSOL PARTICLES BY GOMPERTZ
DISTRIBUTION USING NOVEL JOINT
PROGRESSIVE CENSORING |
381-389 |
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Showkat Ahmad Lone |
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System reliability has become a popular
subject of study in engineering due to
its wide range of potential applications.
When a reliability practitioner aims to
observe a specific number of failed
units, a balanced case of joint
progressive censoring scheme is proposed
to improve the efficiency of an
experiment. This paper investigates
parametric inference for system
reliability using a novel case of joint
progressive censoring, with a specific
focus on two independent Gompertz
populations. The system reliability
parameter is estimated using both
likelihood and Bayesian inferential
approaches. The Metropolis-Hastings
algorithm is employed to compute
Bayesian estimates under different loss
functions. Asymptotic confidence
intervals and Bayesian credible
intervals are also derived. A thorough
simulation study is conducted to
evaluate the performance of the proposed
methods across various sample sizes.
Additionally, to demonstrate the
practical utility of the approach,
virus-containing aerosol particles (VCAP)
lifetime data under two velocities are
analyzed.
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Cite: Showkat Ahmad Lone ANALYSING
STRESS STRENGTH RELIABILITY OF LIFE TEST
ON AEROSOL PARTICLES BY GOMPERTZ
DISTRIBUTION USING NOVEL JOINT
PROGRESSIVE CENSORING. Reliability:
Theory & Applications. 2025, September
3(86): 381-389, DOI: https://doi.org/10.24412/1932-2321-2025-386-381-389
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A NEW COUNT DATA
PROBABILITY MODEL: PROPERTIES AND
APPLICATIONS |
390-405 |
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Morifat, Bilal Ahmad Para |
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In the field of count data analysis,
over-dispersion poses significant
challenges, often limiting the
effectiveness of traditional Poisson
model. To address this limitation, we
propose a novel two parameter
distribution as an extension of Poisson
distribution namely two-Parameter
Poisson Garima Distribution (TPPGD).
This distribution enhances modeling
flexibility for over-dispersed data,
offering a superior fit for real-world
datasets. In this paper we derive the
theoretical properties of TPPGD,
including its probability mass function,
cumulative distribution function and
different statistical properties.
Parameter estimation has been done using
the maximum likelihood method and the
moment method. Finally, the validity of
the proposed model is checked using
different real world data sets.
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Cite: Morifat, Bilal Ahmad Para A NEW
COUNT DATA PROBABILITY MODEL: PROPERTIES
AND APPLICATIONS. Reliability: Theory &
Applications. 2025, September 3(86):
390-405, DOI: https://doi.org/10.24412/1932-2321-2025-386-390-405
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RELIABILITY,
AVAILABILITY AND MAINTAINABILITY (RAM)
ANALYSIS OF SOME PROCESS INDUSTRIES: A
CRITICAL REVIEW OF LITERATURE |
406-421 |
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Punam Rani, Sangeeta Malik, Arun Kumar |
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This paper reviews the literature on
reliability, availability, and
maintainability analysis of process
industrial systems. In today's automated
world, it is unfeasible to live
exclusive of reliable systems, so every
one of the working engineering system be
anticipated to remain operational with
maximum effectiveness for the longest
period of time, or reliable operation.
Throughout the years, the primary goal
has been to concentrate on the system
presentation in excess of an extended
period of time; in essence, these are
case studies on the system concert of
industrial systems. While achieving 100%
failure-free operation in production is
not practicable, industrial systems that
can be repaired can have their system
failures minimized. In this paper, an
effort has been made to compile the
necessary literature and offer some
helpful advice on how to broaden the
field for more beneficial outcomes on
system performance.
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Cite: Punam Rani, Sangeeta Malik, Arun
Kumar RELIABILITY, AVAILABILITY AND
MAINTAINABILITY (RAM) ANALYSIS OF SOME
PROCESS INDUSTRIES: A CRITICAL REVIEW OF
LITERATURE. Reliability: Theory &
Applications. 2025, September 3(86):
406-421, DOI: https://doi.org/10.24412/1932-2321-2025-386-406-421
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ANALYSIS OF JOINT
MULTIPLY TYPE-II CENSORED DATA USING THE
GIBBS SAMPLER ALGORITHM |
422-434 |
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Vishal Singh, Akanksha Gupta and S. K.
Upadhyay |
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This paper introduces a systematic
approach for analyzing data under joint
multiply type-II censoring. The study
assumes a one-parameter exponential
lifetime distribution and focuses on
estimating unknown parameters. The
maximum likelihood method is used to
obtain frequentist point estimates,
while a Bayesian framework is adopted to
draw the corresponding Bayes inferences.
To effectively handle censored data, an
extended Gibbs sampler algorithm is
employed, treating the unknown
observations as further unknowns and
estimating them accordingly. This
methodology ensures a comprehensive and
robust inference process by
simultaneously addressing parameter
uncertainty and the challenges posed by
the censored observations.
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Cite: Vishal Singh, Akanksha Gupta and
S. K. Upadhyay ANALYSIS OF JOINT
MULTIPLY TYPE-II CENSORED DATA USING THE
GIBBS SAMPLER ALGORITHM . Reliability:
Theory & Applications. 2025, September
3(86): 422-434, DOI: https://doi.org/10.24412/1932-2321-2025-386-422-434
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RELIABLE HYBRID
OPTIMIZATION FOR SUPPLY CHAIN INVENTORY
SYSTEMS |
435-454 |
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Ajay Singh Yadav, S. Viswanathan, Navin
Ahlawat, Bhavani Viswanathan, Anupam
Swami, Mohammed Abid |
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This study explores the optimization of
blood supply chain inventory management
through innovative approaches,
specifically Bee Colony Optimization (BCO)
and Genetic Algorithms (GA). The
research addresses challenges in
healthcare logistics, emphasizing the
integration of organizational units
involved in blood sourcing, production,
distribution, and marketing. Key
considerations include the potential
conflicts between cost minimization in
sourcing decisions and the focus on
throughput in production and
distribution. The study highlights the
significance of achieving an optimal
balance to ensure a reliable and
efficient blood supply for patient care.
Bee Colony Optimization and Genetic
Algorithms, inspired by natural
processes, offer promising solutions to
the complexities of blood inventory
management. BCO mimics collaborative
foraging behavior, creating optimal
paths marked by pheromones. Genetic
Algorithms replicate natural selection
to iteratively enhance solutions. The
research aims to provide valuable
insights into the application of these
algorithms, contributing to the
evolution of efficient blood supply
chain management. The anticipated
outcomes include improved healthcare
logistics, ensuring timely access to
blood products and enhancing patient
safety and outcomes.
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Cite: Ajay Singh Yadav, S. Viswanathan,
Navin Ahlawat, Bhavani Viswanathan,
Anupam Swami, Mohammed Abid RELIABLE
HYBRID OPTIMIZATION FOR SUPPLY CHAIN
INVENTORY SYSTEMS. Reliability: Theory &
Applications. 2025, September 3(86):
435-454, DOI: https://doi.org/10.24412/1932-2321-2025-386-435-454
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ALPHA-POWER-BURR-HATKE-EXPONENTIAL MODEL:
PROPERTIES, SIMULATIONS AND APPLICATIONS
BASED ON UNCENSORED AND PROGRESSIVE
TYPE-II-CENSORED SAMPLES |
455-472 |
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Adubisi O. D., Joshua T., David A. A. |
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This study introduced a novel
two-parameter model known as the alpha
power Burr Hatke exponential (APBHE)
model, characterized by constant,
increasing-constant, upside-down bathtub,
decreasing and increasing failure shapes.
Structural properties and basic
reliability functions are derived. The
Simulation study carried out for both
uncensored and progressive type-II
censored samples indicated that the
maximum likelihood estimation (MLE)
performed quite well in producing good
parameter estimates at finite sample
sizes and tend to the true parameter
value quicker than the maximum spacing
product (MBS) method with minimum bias.
Specifically, the censored schemes
simulation disclosed that the MSE and
bias values decrease as the sample size
increases for the various censoring
proportions. To demonstrate the
flexibility and relevance of the APBHE
model, a real-life bladder-cancer
dataset is examined and the APBHE model
achieved the best performance when
compared with other competing models.
Additionally, the log-APBHE model and
log-APBHE regression model functions are
presented for further explorations.
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Cite: Adubisi O. D., Joshua T., David
A. A. ALPHA-POWER-BURR-HATKE-EXPONENTIAL
MODEL: PROPERTIES, SIMULATIONS AND
APPLICATIONS BASED ON UNCENSORED AND
PROGRESSIVE TYPE-II-CENSORED SAMPLES.
Reliability: Theory & Applications.
2025, September 3(86): 455-472, DOI: https://doi.org/10.24412/1932-2321-2025-386-455-472
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MULTI- REFERENCE SKIP-
LOT SAMPLING OF TYPE 3 (MR-SkSP-3) |
473-484 |
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Meby Joseph Manoj, Azarudheen S. |
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In the current industrial sector, the
rate of defective products present in
the lots has been decreasing and most of
the products keeps up a good history of
quality throughout the production also.
Skip-lot sampling plans are the suitable
acceptance sampling plan for the
situations where the series of products
shows a stable and excellent quality.
The skip-lot sampling plans are still
widely used because of its reduced
sampling cost and efforts, because the
plan only needs to inspect a fraction of
the lots submitted after a continues
series of lots with excellent quality.
This approach makes the skip-lot plan
more cost-effective than the other
sampling plans, thus making it an
economically important plan. The current
study incorporated a modification on the
skip-lot sampling of type 3 and
designated it as multi- reference skip
lot sampling of type 3. The proposed
plan has the provision of having
multiple reference plans in normal and
skipping inspection of a skip-lot
sampling plan, unlike the traditional
skip-lot plans which has the same
reference plan in all phases. The
performance measures of the proposed
plan are derived using the power series
approach. A designing methodology to
determine the optimal parameters for the
plan using the unity value approach is
also described with the help of a
numerical illustration. Behaviour of the
operating characteristic curves for
varying set of parameters are also
analysed for the plan. Comparison of the
proposed plan is done between the
conventional plans using performance
measure values and graphical
representations. This analysis shows
that the new plan is able to effectively
optimize the preferences of producer and
consumer simultaneously, where the
traditional plans fail to. The analysis
is supported with the help of graphical
representations and tabulated values.
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Cite: Meby Joseph Manoj, Azarudheen S.
MULTI- REFERENCE SKIP- LOT SAMPLING OF
TYPE 3 (MR-SkSP-3). Reliability: Theory
& Applications. 2025, September 3(86):
473-484, DOI: https://doi.org/10.24412/1932-2321-2025-386-473-484
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ENHANCING ACCURACY IN
ESTIMATING POPULATION MEAN THROUGH
MODIFIED RATIO ESTIMATORS IN RANKED SET
SAMPLING |
485-494 |
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S. A. Sabo, A. A. Osi, I. Z. Musa, H. U.
Abubakar, A. Muhammad, U. Abubakar |
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This study aimed to improve the ratio
estimation under rank set sampling by
proposing some new modified estimators
using auxiliary information on the size
of the sample. The expressions for the
bias and mean squared error of the
proposed modified estimators are derived
up to the first order of approximation
using Tailor series expansion. A
theoretical efficiency comparison
between the proposed and competing
estimators was done and the conditions
upon which the proposed estimators
expect to outperform the competing
estimators were stated. Results from the
numerical work indicate that the new
proposed improved estimators are better
than the already existing ones, showing
a lower mean square error, coefficient
of variation, and a considerable gain in
efficiency. The new proposed estimators
emerge as the optimal choice,
outperforming the competing ones, and
should therefore be used in applications.
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Cite: S. A. Sabo, A. A. Osi, I. Z. Musa,
H. U. Abubakar, A. Muhammad, U. Abubakar
ENHANCING ACCURACY IN ESTIMATING
POPULATION MEAN THROUGH MODIFIED RATIO
ESTIMATORS IN RANKED SET SAMPLING.
Reliability: Theory & Applications.
2025, September 3(86): 485-494, DOI: https://doi.org/10.24412/1932-2321-2025-386-485-494
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SURVEY ON
NON-MARKOVIAN QUEUE WITH PHASE SERVICE
USING SUPPLEMENTARY VARIABLE TECHNIQUE |
495-518 |
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Binay Kumar, Sudeep Singh Sanga, Aditya
Kumar |
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In the present article, we provide a
comprehensive overview and literature
review on performance modeling of
queueing systems with phase service,
utilizing the supplementary variable
technique. We discuss the scenarios that
necessitate phase service and explain
how the supplementary variable technique
is applied to analyze non-Markovian
models. Additionally, we offer a summary
of the fundamental concepts and existing
literature on queueing systems with
phase service. Our review covers
research conducted over the past decade
(2014-2024) on queues featuring phase
service, including aspects such as bulk
arrival, service interruptions, and
discouragement. The review
systematically explores models
incorporating bulk arrivals, service
interruptions, customer discouragement,
and other complex operational features.
By consolidating recent advancements and
identifying common modeling approaches,
this work aims to provide valuable
insights for researchers and
practitioners engaged in the analysis
and design of advanced queueing systems.
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Cite: Binay Kumar, Sudeep Singh Sanga,
Aditya Kumar SURVEY ON NON-MARKOVIAN
QUEUE WITH PHASE SERVICE USING
SUPPLEMENTARY VARIABLE TECHNIQUE.
Reliability: Theory & Applications.
2025, September 3(86): 495-518, DOI: https://doi.org/10.24412/1932-2321-2025-386-495-518
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MATHEMATICAL AND
RELIABILITY MODELS OF MACHINE LEARNING
ALGORITHMS FOR EARLY BRAIN CANCER
DETECTION |
519-532 |
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Ajay Singh Yadav, Navin Ahlawat, Bhavani
Viswanathan, Garima Pandey, Anupam Swami,
Anjali Malik |
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Early detection of brain cancer is
critical for improving patient outcomes,
and this study explores the use of
Logistic Regression, Reliability
Modeling, and mathematical techniques
for better diagnostic accuracy. Logistic
Regression, a statistical model for
binary classification, is used to
predict tumor malignancy based on
imaging features, offering probabilistic
predictions that can guide clinical
decisions. Reliability Modeling
evaluates the performance and robustness
of diagnostic systems, ensuring accurate
detection despite varying conditions. By
combining these methods, we can improve
both the prediction accuracy and
reliability of diagnostic systems. The
research also integrates optimization
and statistical inference to refine
these models, ensuring they are both
accurate and statistically sound. Hybrid
models that combine deep learning with
Logistic Regression further enhance the
detection of brain tumors by leveraging
the strengths of both approaches. The
study underscores the potential of AI
and mathematical models to revolutionize
brain cancer diagnostics, offering more
reliable, interpretable, and efficient
tools for early detection and improved
patient outcomes.
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Cite: Ajay Singh Yadav, Navin Ahlawat,
Bhavani Viswanathan, Garima Pandey,
Anupam Swami, Anjali Malik MATHEMATICAL
AND RELIABILITY MODELS OF MACHINE
LEARNING ALGORITHMS FOR EARLY BRAIN
CANCER DETECTION. Reliability: Theory &
Applications. 2025, September 3(86):
519-532, DOI: https://doi.org/10.24412/1932-2321-2025-386-519-532
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IMPROVING THE QUALITY
OF INTERVAL PATTERN RECOGNITION BY
DIVIDING THE PATIENT SAMPLE IN MEDICAL
RESEARCH |
533-538 |
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Gurami Tsitsiashvili, Vera Nevzorova,
Pavel Dunts, Angelina Talko, Marina
Osipova |
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In this paper, we consider a way to
improve the quality of interval pattern
recognition by dividing the sample into
parts. This method is used to study
erythrocyte and platelet germs of
haematopoiesis for the ability to
positively treat haematological patients
from COVID-19. Along with this, this
method of improving the quality of
interval recognition is used to identify
predictors of "difficult" tracheal
intubation during artificial ventilation
during anaesthetic support of surgical
interventions. Despite the rather strong
difference between these medical tasks,
they are united in this research context
by the possibility of improving the
quality of recognition through a more
specialized study of each sub sample of
patients after dividing the sample into
parts.
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Cite: Gurami Tsitsiashvili, Vera
Nevzorova, Pavel Dunts, Angelina Talko,
Marina Osipova IMPROVING THE QUALITY OF
INTERVAL PATTERN RECOGNITION BY DIVIDING
THE PATIENT SAMPLE IN MEDICAL RESEARCH.
Reliability: Theory & Applications.
2025, September 3(86): 533-538, DOI: https://doi.org/10.24412/1932-2321-2025-386-533-538
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EFFICIENT ESTIMATION
OF POPULATION MEAN USING MEDIAN OF
AUXILIARY VARIABLE AND SIMULATION UNDER
SRS |
539-550 |
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RizwanYousuf |
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In this study, we propose two modified
ratio estimators for the estimation of
the population mean of a study variable
using the median of an auxiliary
variable. Theoretical expressions for
the bias and mean squared error (MSE) of
the proposed estimators are derived
under simple random sampling. We
establish the conditions under which
these estimators outperform existing
modified ratio estimators. To validate
the theoretical findings, both an
empirical study using natural population
data and a comprehensive simulation
study are conducted. The simulation
results consistently demonstrate the
superior efficiency of the proposed
estimators across varying sample sizes
and correlation structures. These
findings highlight the practical
applicability and robustness of the
proposed estimators in survey sampling.
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Cite: RizwanYousuf EFFICIENT ESTIMATION
OF POPULATION MEAN USING MEDIAN OF
AUXILIARY VARIABLE AND SIMULATION UNDER
SRS. Reliability: Theory & Applications.
2025, September 3(86): 539-550, DOI: https://doi.org/10.24412/1932-2321-2025-386-539-550
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ENHANCING SHORE
HARDNESS AND RELIABILITY OF SS 316L
REINFORCED PMMA NANOCOMPOSITES THROUGH
RESIN 3D PRINTING PROCESS OPTIMIZATION |
551-561 |
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Upender Punia, Ramesh Kumar Garg |
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Over the last ten years, 3D printing has
made great progress and expanded its
applicability in a number of industries,
including dentistry. Dental items
including temporary and permanent crowns,
bridges, drill guides, and jaw implants
may be made using resin 3D printing. To
create novel 3D-printable materials and
improve their functionality, a lot of
research is being done. The shore
hardness of 316L-reinforced PMMA
nanocomposites for dental applications
is examined in this work. Three
important process parameters—exposure
time (3-5 seconds), layer height (20-40
microns), and post-curing duration
(10-30 minutes)—are used to assess the
hardness of manufactured specimens.
Shore hardness is optimised using
Response Surface Methodology (RSM),
which yields a maximum shore hardness
of88.90 SHD at 4.75 seconds of exposure
time, 30.7 microns of slice height, and
23.2 minutes of post-curing time.
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Cite: Upender Punia, Ramesh Kumar Garg
ENHANCING SHORE HARDNESS AND RELIABILITY
OF SS 316L REINFORCED PMMA
NANOCOMPOSITES THROUGH RESIN 3D PRINTING
PROCESS OPTIMIZATION. Reliability:
Theory & Applications. 2025, September
3(86): 551-561, DOI: https://doi.org/10.24412/1932-2321-2025-386-551-561
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IMPACT OF FIBERS
WEIGHT PROPORTION AND SURFACE TREATMENTS
ON THE RELIABILITY OF HYBRID EPOXY
COMPOSITE |
562-572 |
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Manjeet Chahar, Rajneesh Kumar |
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Natural fiber-reinforced composites (NFRCs)
are attracting growing interest in many
technical applications owing to their
environmentally sustainable and
economical properties. This study
investigates the impact of weight
proportion of fibers and surface
treatments on the tensile strength of
hybrid epoxy composites reinforced with
hemp, jute, and bamboo. Prior to
composite fabrication, the fibers
underwent alkali and saline treatments
at different concentrations (3, 5, and 7
wt. %). The composites were fabricated
via the hand lay-up technique by varying
wt. proportion of fibers (10,15, and 20
wt. %). The tensile strength is
optimized using Response Surface
Methodology (RSM), which yields highest
tensile strength of 63.11 MPa at 14.24
wt. % of fibers fraction and 5.40 wt. %
concentration of alkali treatment.
Findings of this study demonstrate that
reliability of the hybrid composite
significantly enhanced due to
improvement in strength of the composite.
The treated hybrid composites have
favourable properties, rendering them a
feasible and sustainable option for
automobile components and other
lightweight structural applications.
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Cite: Manjeet Chahar, Rajneesh Kumar
IMPACT OF FIBERS WEIGHT PROPORTION AND
SURFACE TREATMENTS ON THE RELIABILITY OF
HYBRID EPOXY COMPOSITE. Reliability:
Theory & Applications. 2025, September
3(86): 562-572, DOI: https://doi.org/10.24412/1932-2321-2025-386-562-572
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COMPARISON OF
CLASSICAL AND BAYESIAN APPROACHES FOR
ESTIMATING THE SCALE PARAMETER OF THE
INVERSE POWER RAYLEIGH DISTRIBUTION |
573-586 |
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Aadil Ahmad Mir, S.P. Ahmad, Sofi
Mudasir Ahad |
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This manuscript investigates the
parameter estimation of the Inverse
Power Rayleigh Distribution (IPRD) using
both Classical and Bayesian approaches.
Parameters are estimated via Maximum
Likelihood Estimation (MLE) and Bayesian
methods under three prior assumptions:
Jeffreys prior, extended Jeffreys prior,
and quasi prior. Bayesian estimators,
along with their associated risks, are
evaluated using various symmetric and
asymmetric loss functions, including the
squared error loss function, Al-Bayyatis
new loss function, precautionary loss
function and entropy loss function. The
performance of the estimators is
assessed through simulated data based on
the mean squared error (MSE) criterion.
Results indicate that the Bayesian
approach generally provides more
accurate estimates with lower MSE
compared to the classical MLE method.
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Cite: Aadil Ahmad Mir, S.P. Ahmad, Sofi
Mudasir Ahad COMPARISON OF CLASSICAL AND
BAYESIAN APPROACHES FOR ESTIMATING THE
SCALE PARAMETER OF THE INVERSE POWER
RAYLEIGH DISTRIBUTION. Reliability:
Theory & Applications. 2025, September
3(86): 573-586, DOI: https://doi.org/10.24412/1932-2321-2025-386-573-586
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THE IMPACT OF RAM ON
SYSTEM PERFORMANCE: A REVIEW |
587-591 |
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Parveen Sihmar, Vikas Modgil, Sandeep
Kumar |
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One of the requirements that industrial
systems must meet is that they must
function effectively for a prolonged
period. The system's performance is a
vital component for failure-free
operation; yet, in actual fact, it is
extremely rare for any production system
to be completely failure-free. Over the
course of the past twenty-five years, a
comprehensive and critical literature
assessment of reliability,
maintainability, and availability (RAM)
approaches has been carried out. These
approaches have the potential to assist
in the enhancement of the performance of
complex systems. The review of a few
publications resulted in the provision
of comprehensive information regarding
the historical and contemporary
situation of RAM procedures in the
research field and enterprises. A review
of RAM tools and approaches can help in
doing qualitative and quantitative
analysis of complex systems. The author
of this research tried to focus on a few
of the key components of RAM methods.
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Cite: Parveen Sihmar, Vikas Modgil,
Sandeep Kumar THE IMPACT OF RAM ON
SYSTEM PERFORMANCE: A REVIEW.
Reliability: Theory & Applications.
2025, September 3(86): 587-591, DOI: https://doi.org/10.24412/1932-2321-2025-386-587-591
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THE QUASI-STATIONARY
DISTRIBUTION OF A COMPLEX TWO-UNIT
REPAIRABLE SYSTEM |
592-600 |
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Miriam Kalpana Simon, Jasmine Rathi S.,
Late Dr. K. Shankar Bhat |
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Like the first-busy-period in a queuing
system, the time-to-system-failure is an
important characteristic of a
reliability system. In some reliability
systems the time-to-system-failure may
be sufficiently large to allow the
residual life of the system to settle
down to a state of statistical
equilibrium. The conditional limit
distribution of the residual lifetime,
also known as the quasi- stationary
distribution, plays a vital role in the
statistical analysis of such systems. In
this work, the quasi-stationary
distribution for the residual lifetime
of a two-unit complex reparable system
is obtained using regenerative
stochastic process. The results of the
study are numerically illustrated
assuming exponential lifetime
distribution for the units.
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Cite: Miriam Kalpana Simon, Jasmine
Rathi S., Late Dr. K. Shankar Bhat THE
QUASI-STATIONARY DISTRIBUTION OF A
COMPLEX TWO-UNIT REPAIRABLE SYSTEM.
Reliability: Theory & Applications.
2025, September 3(86): 592-600, DOI: https://doi.org/10.24412/1932-2321-2025-386-592-600
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LIFO-BASED
OPTIMIZATION OF TWO-WAREHOUSE INVENTORY
SYSTEMS WITH DETERIORATING ITEMS |
601-613 |
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Amit Kumar, Ajay Singh Yadav, Dharmendra
Yadav, Bhavani Viswanathan |
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In this study, a two-warehouse inventory
model for the red wine industry is
presented, focusing on items that
deteriorate. The model takes into
account the effects of inflation and
operates on the LIFO (Last In, First Out)
distribution policy. The goal is to
minimize the total inventory cost,
including the cost of maintaining
inventory and the cost of purchasing new
inventory. The model assumes a constant
and known demand for red wine over time,
with no permitted shortages. The stock
system consists of warehouse A and
warehouse B, with starting stocks fixed
in each case. Inventory balance
equations track inventory levels at each
warehouse, taking into account transfers
between warehouses and customer demand.
The LIFO shipping policy is implemented
to determine the quantities transferred
between warehouses. Inflation is
factored into the model by adjusting the
cost of buying new inventory. This
adjustment may be based on historical
inflation rates or other relevant
factors. The objective function is to
minimize the total inventory cost,
taking into account inventory costs and
inflation-adjusted purchasing costs. The
model provides a framework for making
decisions about stock levels and
transfer rates between warehouses. By
optimizing these decisions, the model
aims to achieve cost savings while
ensuring that demand is met without
bottlenecks. The model results can serve
as a guide for inventory management
strategies in the red wine industry,
taking into account the specific
challenges presented by the spoiled
nature of the product and the impact of
inflation.
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Cite: Amit Kumar, Ajay Singh Yadav,
Dharmendra Yadav, Bhavani Viswanathan
LIFO-BASED OPTIMIZATION OF TWO-WAREHOUSE
INVENTORY SYSTEMS WITH DETERIORATING
ITEMS. Reliability: Theory &
Applications. 2025, September 3(86):
601-613, DOI: https://doi.org/10.24412/1932-2321-2025-386-601-613
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STOCHASTIC MODELING
AND ANALYSIS OF A PARALLEL SYSTEM WITH
DIFFERING UNIT QUALITIES AND
CATASTROPHIC FAILURES |
614-624 |
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Priya Baloda, Amit Kumar, Vikas Garg |
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In this paper, we conduct a stochastic
analysis of a system comprising of two
dissimilar units operating in parallel.
One unit, characterized by two distinct
types of failures, is considered high
merit, while the other unit, with only
one type of malfunction, is deemed low
merit. We introduce the concept of
catastrophic failure for the system. It
is assumed that a single serviceman is
responsible for both repair and
replacement tasks. A regenerative
point-based approach is employed to
estimate various reliability
characteristics. Additionally, we
analyze the proposed model graphically
to illustrate the effects of failure,
repair, and replacement rates on the
system's mean time to system failure (MTSF),
availability, and profit.
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Cite: Priya Baloda, Amit Kumar, Vikas
Garg STOCHASTIC MODELING AND ANALYSIS OF
A PARALLEL SYSTEM WITH DIFFERING UNIT
QUALITIES AND CATASTROPHIC FAILURES .
Reliability: Theory & Applications.
2025, September 3(86): 614-624, DOI: https://doi.org/10.24412/1932-2321-2025-386-614-624
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ANALYSIS OF METHODS
FOR ELIMINATION OF THE BRUSH-CONTACT
ASSEMBLY OF THE ASG OF WIND TURBINES |
625-633 |
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N.S. Mammadov, M. Marufov, K.M.
Mukhtarova |
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Traditional generator designs that use
brush-and-contact assemblies to transmit
electric current between rotating and
stationary parts of the device are
subject to significant drawbacks. The
main problems associated with the use of
brush-and-contact assemblies include
mechanical wear of brushes and slip
rings, sparking, electrical losses and
high operating costs, which leads to
reduced reliability and increased
maintenance costs. Elimination of
brush-and-contact assemblies is an
urgent task, since it allows to
significantly increase the reliability
of devices and simplify their operation,
especially in difficult climate
conditions and high wind turbine
installations. The article analyzes two
modern approaches to solving this
problem: installation of a brushless
exciter and use of a rotating
transformer. Each of these methods has
its own advantages and disadvantages.
The general electrical circuit of a
brushless exciter device based on an
asynchronized synchronous generator is
presented. The general electrical
circuit of an asynchronized synchronous
generator with a rotating transformer is
also presented. An innovative solution
is also considered, which involves
installing a battery on the rotating
part of the generator, which acts as a
contactless power source for the rotor
winding and provides energy storage.
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Cite: N.S. Mammadov, M. Marufov, K.M.
Mukhtarova ANALYSIS OF METHODS FOR
ELIMINATION OF THE BRUSH-CONTACT
ASSEMBLY OF THE ASG OF WIND TURBINES.
Reliability: Theory & Applications.
2025, September 3(86): 625-633, DOI: https://doi.org/10.24412/1932-2321-2025-386-625-633
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CONSTRUCTION OF
COMPLETE STOCHASTIC LIFE CYCLES OF
HIGHLY CRITICAL INFRASTRUCTURES |
634-645 |
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Sviatoslav Timashev, Anna Bushinskaya |
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The article describes a risk-based
approach to constructing the full life
cycle (LC) of HCI with accounting for
climate change. In this case, the
objective function (OF) of HCI risk
management as a function of time is
reduced to the generalized cost of
operating a strategically important
object in the time interval “'from (birth)
cradle / to grave". The life cycle,
built on the basis of these data, makes
it possible to evaluate and predict: (1)
the inherent design reliability of the
HCI, (2) the probabilities of all types
of failures of the HCI; (3) the monetary
consequences of these failures; (4)
risks associated with random times of
diagnostics, repairs and restoration of
HCI and with the moments of its failures;
(5) the overall risk of HCI at each
moment of its existence with accounting
for climate change.
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Cite: Sviatoslav Timashev, Anna
Bushinskaya CONSTRUCTION OF COMPLETE
STOCHASTIC LIFE CYCLES OF HIGHLY
CRITICAL INFRASTRUCTURES. Reliability:
Theory & Applications. 2025, September
3(86): 634-645, DOI: https://doi.org/10.24412/1932-2321-2025-386-634-645
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EXPLORING SOME NEW
CONTRIBUTION TO RAM AWADH DISTRIBUTION
WITH COMPARATIVE PROPERTIES AND ITS
APPLICATIONS |
646-658 |
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Manzoor A. Khanday, Rashid A. Ganaie,
Aboubakar Ahmat Alwali Bourma, T.
Vivekanandan, R. Shenbagaraja |
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In this study, a novel extension of the
Ram Awadh distribution referred to as
length biased Ram Awadh distribution is
proposed and systematically developed.
This distribution is constructed by
applying length-biased transformation to
the baseline Ram Awadh distribution,
making it more suitable for modeling
data where longer durations or larger
values are more likely to be observed. A
comprehensive exploration of the
distribution's statistical properties is
presented, including the derivation of
moments, harmonic mean, reliability
function, failure rate function, reverse
hazard rate function, order statistics,
entropy as well as the bonferroni and
Lorenz curves. Parameter estimation is
conducted through the maximum likelihood
estimation method, ensuring robustness
and efficiency. The practical utility
and goodness of fit of the proposed
model are demonstrated through its
application to three real-life datasets,
highlighting its flexibility and
improved performance in empirical
context.
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Cite: Manzoor A. Khanday, Rashid A.
Ganaie, Aboubakar Ahmat Alwali Bourma,
T. Vivekanandan, R. Shenbagaraja
EXPLORING SOME NEW CONTRIBUTION TO RAM
AWADH DISTRIBUTION WITH COMPARATIVE
PROPERTIES AND ITS APPLICATIONS.
Reliability: Theory & Applications.
2025, September 3(86): 646-658, DOI: https://doi.org/10.24412/1932-2321-2025-386-646-658
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A COMPARATIVE STUDY OF
GENERALIZED ARADHANA DISTRIBUTION WITH
SIGNIFICANT STATISTICAL PROPERTIES AND
APPLICATIONS |
659-671 |
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Rashid A. Ganaie, V. P. Soumya, R.
Shenbagaraja,Manzoor A. Khanday |
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This study introduces a novel extension
of the generalized Aradhana distribution,
termed the length biased generalized
Aradhana distribution. The proposed
distribution is formulated by applying
the length biased technique to the
baseline generalized Aradhana
distribution, enhancing its
applicability in reliability and
survival analysis. Fundamental
statistical properties, including
moments, order statistics, reliability
functions and entropy are rigorously
derived to characterize the
distribution's behavior. The parameters
of proposed model are estimated using
the maximum likelihood estimation method
to ensure statistical efficiency. To
assess its practical utility, the
distribution is applied to two
real-world lifetime data sets,
demonstrating its superior performance
and robustness compared to existing
models. These findings highlight the
significance and applicability of the
length biased generalized Aradhana
distribution in modeling lifetime data.
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Cite: Rashid A. Ganaie, V. P. Soumya,
R. Shenbagaraja,Manzoor A. Khanday A
COMPARATIVE STUDY OF GENERALIZED
ARADHANA DISTRIBUTION WITH SIGNIFICANT
STATISTICAL PROPERTIES AND APPLICATIONS.
Reliability: Theory & Applications.
2025, September 3(86): 659-671, DOI: https://doi.org/10.24412/1932-2321-2025-386-659-671
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ENHANCING PRODUCT
QUALITY AND OPERATIONAL EFFICIENCY
THROUGH STATISTICAL QUALITY CONTROL |
672-681 |
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M. A. Khanday, A. Jain, A. A. Khan, Y.
Ahmad, A. A. Rather |
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The foundation of success in the modern
business environment is maintaining
constant quality and efficiency across
supply chains. The paper presents a
clear and comprehensive analysis as it
delves into the complexities of quality
control in the supply chain for makeup
products. By utilizing a diverse range
of statistical techniques, such as
descriptive statistics, control chart
analysis, and ANOVA, and able to reveal
important information about defect rates
and the overall field of quality control
procedures. This research reveals the
complex interactions between different
elements that affect defect rates, with
a focus on the crucial functions that
lead time and shipping carriers play in
the supply chain for makeup products. By
means of a methodical and thorough
examination, we not only reveal the
stability that is innate to the
manufacturing process but also identify
critical areas that are ripe for
improvement. Determine areas for
improvement by carefully examining the
data; this will set the stage for
increased operational effectiveness and
higher standards of quality. This paper
bridges the gap between theoretical
understanding and real- world
applications, rather than just existing
in the domain of theoretical conjecture.
Provide participants in the makeup
product supply chain with practical
insights that can lead to observable
outcomes by combining academic accuracy
with real-world relevance. In order to
enable stakeholders to confidently and
precisely navigate the complexities of
quality control, this paper acts as a
beacon of guidance. Stakeholders can
enhance operational performance, reduce
risks, and foster a continuous
improvement culture by Furthermore, by
maintaining an intense focus on raising
customer satisfaction, this analysis
clears the path for long-term success in
the competitive and dynamic makeup
product market.
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Cite: M. A. Khanday, A. Jain, A. A.
Khan, Y. Ahmad, A. A. Rather ENHANCING
PRODUCT QUALITY AND OPERATIONAL
EFFICIENCY THROUGH STATISTICAL QUALITY
CONTROL. Reliability: Theory &
Applications. 2025, September 3(86):
672-681, DOI: https://doi.org/10.24412/1932-2321-2025-386-672-681
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ANALYSIS OF MODELING
METHODS OF LINEAR AND NONLINEAR
AUTOMATIC CONTROL SYSTEMS |
682-689 |
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S.M. Kerimova, S.J. Alimamedova |
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The article discusses the stability of
automatic control systems (ACS). The
stability of the automatic control
system is the main characteristic of the
automatic return of the system to its
initial state of equilibrium after
exposure to certain influencing factors
on this system. In other words, it is
the property of the system to maintain
its resistance to external influences
and its efficiency. The issue of
reliability is aimed at preventing
unforeseen and dangerous consequences of
system instability, especially in such
diverse fields as aviation, energy, and
industry. A stable system ensures more
accurate performance of the specified
functions and is less prone to probable
failure, and they can work for a long
time without human intervention. An
important place in the issue of
determining the stability of ACS is
occupied by the identification of errors
that occur mainly during transients
occurring in systems. The detected error
is determined by the difference between
the input signal (setpoint) and the
input signal. In addition, the error
that occurs in the system depends on
different types of input signals, so
these inputs can be stepwise, linear,
etc. they can be typical. It should be
noted that bias error analysis is useful
only for stable systems. That is, before
investigating an error in the system, it
is necessary to determine the stability
of this system. The article also
considered the issue of calculating the
error in the system with negative
feedback. Using the Matlab/Simulink
program, algorithms related to the
detection of an error in the ACS are
compiled. When studying the issues of
ACS stability, the issue of regulating
the gain coefficients of various types
through a PID (ProportionaTIntegral-Derivative)
regulator is being investigated.
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Cite: S.M. Kerimova, S.J. Alimamedova
ANALYSIS OF MODELING METHODS OF LINEAR
AND NONLINEAR AUTOMATIC CONTROL SYSTEMS
. Reliability: Theory & Applications.
2025, September 3(86): 682-689, DOI: https://doi.org/10.24412/1932-2321-2025-386-682-689
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THE POWER GENERALIZED
KAVYA MANOHARAN TRANSFORMATION:
APPLICATIONS IN RELIABILITY AND LIFETIME
REGRESSION |
690-704 |
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Jinet Mariya Jojy, Sajesh T. A., Nicy
Sebastian |
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A new class of distributions is
introduced through the exponentiated
generalization of the Kavya Manoharan
transformation, referred to as the Power
Generalized Kavya Manoharan (PGKM)
transformation. In parallel systems,
applying power transformations to the
distribution of individual components
yields the system's overall distribution.
This generalization enhances the model's
flexibility and accuracy. In this
context, we propose a transformation to
generate a novel class of distributions,
specifically by developing a
distribution based on the Inverse
Weibull distribution as the baseline. We
investigate the behaviour of the hazard
rates of these distributions, along with
other analytical properties. Reliability
measures for both single-component and
multi-component stress-strength models
are derived. The parameters of the
proposed model are estimated using the
maximum likelihood method, and
simulation studies confirm the
consistency of these estimates.
Additionally, the new life distribution
is applied to a real dataset,
demonstrating superior fit when compared
to various existing distributions in the
literature. The distribution is further
re-parametrized with location-scale
parameters and employed in a lifetime
regression analysis, with application
provided to a practical dataset.
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Cite: Jinet Mariya Jojy, Sajesh T. A.,
Nicy Sebastian THE POWER GENERALIZED
KAVYA MANOHARAN TRANSFORMATION:
APPLICATIONS IN RELIABILITY AND LIFETIME
REGRESSION. Reliability: Theory &
Applications. 2025, September 3(86):
690-704, DOI: https://doi.org/10.24412/1932-2321-2025-386-690-704
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INFERENCES FOR ALPHA
POWER TRANSFORMED INVERSE LINDLEY
DISTRIBUTION BASED ON ORDER STATISTICS
WITH APPLICATIONS |
705-725 |
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Sumit Kumar, Anju Goyal, Devendra Kumar,
Narinder Kumar |
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The alpha power-transformed inverse
Lindley distribution (APTIL) consist of
one shape and one scale parameter. In
some cases, the moments of the APTIL
distribution may not exist due to its
heavy tail, so we instead focus on the
concept of inverse moments. In this
paper, order statistics is used to
derive the expression for moments,
product moments and moment generating
function for this distribution. The
entropy of using order statistics for
the APTIL distribution is also derived.
Furthermore, tabulated values of the
inverse moments of order statistics are
provided for various sample sizes and
parameter combinations. Three classical
estimation techniques, viz., maximum
product spacing estimators, least
squares estimators, and weighted least
squares estimators, are considered for
parameter estimation and also evaluate
the model parameters based on Type-II
censored data. A Monte Carlo
simulation-based approach is employed to
assess the accuracy and validity of
these estimators and the ensuing results.
Finally, an empirical study using
available real-life data sets
demonstrates the utility of the
distribution.
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Cite: Sumit Kumar, Anju Goyal, Devendra
Kumar, Narinder Kumar INFERENCES FOR
ALPHA POWER TRANSFORMED INVERSE LINDLEY
DISTRIBUTION BASED ON ORDER STATISTICS
WITH APPLICATIONS. Reliability: Theory &
Applications. 2025, September 3(86):
705-725, DOI: https://doi.org/10.24412/1932-2321-2025-386-705-725
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IN FUZZY MENGER SPACE,
CERTAIN FPT USING OCCASIONALLY WEAKLY
COMPATIBLE MAPPING THAT USES A-CLAS
FUNCTION |
726-734 |
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Heera Ahirwar, Kavita Shrivastava |
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In this paper, we present new common
fixed point theorems in the setting of
fuzzy Menger spaces by considering
self-mappings that satisfy the condition
of occasional weak compatibility. The
analysis is enriched through the
incorporation of A-class functions,
which serve as control functions in the
formulation of contractive type
conditions. This approach allows for the
generalization and extension of several
known results in the field of fuzzy
fixed point theory. The structure of
fuzzy Menger spaces, combined with the
flexibility of A-class functions,
enables the establishment of sufficient
conditions for the existence and
uniqueness of common fixed points among
a family of self-mappings. To support
the theoretical results, we also provide
illustrative examples that demonstrate
the applicability and effectiveness of
the proposed theorems. The findings
contribute to the broader understanding
of fixed point results in fuzzy
environments and highlight the utility
of occasionally weakly compatible
mappings under generalized contractive
settings.
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Cite: Heera Ahirwar, Kavita Shrivastava
IN FUZZY MENGER SPACE, CERTAIN FPT USING
OCCASIONALLY WEAKLY COMPATIBLE MAPPING
THAT USES A-CLAS FUNCTION. Reliability:
Theory & Applications. 2025, September
3(86): 726-734, DOI: https://doi.org/10.24412/1932-2321-2025-386-726-734
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RELIABILITY ASSESSMENT
OF LOW-VOLT AGE NETWORKS UNDER
LIGHTNING-INDUCED OVERVOLTAGES
TRANSFERRED FROM MEDIUM-VOLTAGE SYSTEMS |
735-742 |
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I.A. Guseynova |
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This article investigates the
reliability implications of
lightning-induced overvoltages
transferred from medium-voltage (MV)
systems to low-voltage (LV) networks.
Special emphasis is placed on the role
of distribution transformers and the
importance of accurate modeling for
evaluating surge transfer mechanisms.
Simulations and experimental comparisons
reveal that conventional capacitive
Pi-circuits significantly overestimate
transferred voltages. The study
highlights the key parameters
influencing surge magnitudes, such as
earth resistance, transformer proximity,
line configuration, and insulator
flashovers. Based on analytical models
and real case studies, the paper
provides recommendations for enhancing
the surge immunity and operational
reliability of LV systems under
lightning conditions.
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Cite: I.A. Guseynova RELIABILITY
ASSESSMENT OF LOW-VOLT AGE NETWORKS
UNDER LIGHTNING-INDUCED OVERVOLTAGES
TRANSFERRED FROM MEDIUM-VOLTAGE SYSTEMS.
Reliability: Theory & Applications.
2025, September 3(86): 735-742, DOI: https://doi.org/10.24412/1932-2321-2025-386-735-742
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ENHANCING THE
RELIABILITY OF RELAY- CONTACTOR CONTROL
SYSTEMS IN INDUSTRIAL AND ENERGY
APPLICATIONS |
743-751 |
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Gultakin Hasanova, Sonakhanim Babayeva |
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Relay-contactor systems remain essential
components in power control and
automation circuits, particularly in
critical industrial and energy
infrastructure. Despite the increasing
use of solid- state and programmable
devices, electromechanical relays and
contactors are still widely employed due
to their robustness, electromagnetic
isolation, and high switching
capabilities. However, their reliability
is subject to various failure mechanisms
including contact wear, coil overheating,
and mechanical degradation. This paper
presents a systematic analysis of these
reliability challenges, supported by
statistical modeling, environmental
correction factors, and empirical data.
Advanced diagnostic techniques and
predictive maintenance strategies are
discussed, including the integration of
intelligent monitoring systems capable
of tracking temperature, contact
resistance, and response time. The study
also explores architectural solutions
for improving the redundancy and
resilience of DC auxiliary power systems,
focusing on protection automation. The
technical and economic benefits of
intelligent relay systems over
conventional ones are demonstrated.
Results indicate that adopting adaptive
reliability management and smart
diagnostics significantly reduces
failure rates and improves system
availability.
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Cite: Gultakin Hasanova, Sonakhanim
Babayeva ENHANCING THE RELIABILITY OF
RELAY- CONTACTOR CONTROL SYSTEMS IN
INDUSTRIAL AND ENERGY APPLICATIONS.
Reliability: Theory & Applications.
2025, September 3(86): 743-751, DOI: https://doi.org/10.24412/1932-2321-2025-386-743-751
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FRACTIONAL INTEGRAL
INEQUALITIES AND THEIR Q-EXTENSION |
752-757 |
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Farooq Ahmad, Ajjaz Maqbool, D.K. Jain,
R. Vijaykrishnaraj, Aafaq A. Rather, D.
Vedavathi Saraja, Syed M. Parveen,
Raeesa Bashir , Showkat Ahmad Bhat |
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This paper aims to establish novel
fractional integral inequalities for
synchronous functions associated with
the Chebyshev functional, incorporating
the Gauss hyper geometric function. By
employing advanced integral techniques,
we derive refined bounds that extend and
generalize existing results in the
literature. The final section explores
several special cases, particularly
fractional integral inequalities
involving Riemann-Liouville type
fractional integral operators.
Furthermore, we discuss potential
applications of these findings in
various mathematical and applied fields,
highlighting their significance in
fractional calculus and related domains.
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Cite: Farooq Ahmad, Ajjaz Maqbool, D.K.
Jain, R. Vijaykrishnaraj, Aafaq A.
Rather, D. Vedavathi Saraja, Syed M.
Parveen, Raeesa Bashir , Showkat Ahmad
Bhat FRACTIONAL INTEGRAL INEQUALITIES
AND THEIR Q-EXTENSION. Reliability:
Theory & Applications. 2025, September
3(86): 752-757, DOI: https://doi.org/10.24412/1932-2321-2025-386-752-757
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DESIGN OF SKIP LOT
SAMPLING PLAN (SKSP-3) WITH SINGLE
SAMPLING PLAN AS A REFERENCE PLAN USING
BOREL DISTRIBUTION |
758-768 |
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Jayalakshmi S., Gopinath M. |
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Skip-lot sampling plans (SkSPs) have
long been recognized as effective
strategies for minimizing inspection
efforts in quality control, especially
within high-volume manufacturing
settings. This study proposes a Skip-Lot
Sampling Plan of Type SkSP-3,
constructed using Single Sampling Plans
(SSPs) by attributes, under the
probabilistic framework defined by the
Borel distribution. Given its
suitability for modeling rare or
intermittent events, the Borel
distribution provides a solid foundation
for representing quality characteristics
in such contexts. The presentation of
the proposed SkSP-3 plan is assessed by
means of Operating Characteristic (OC)
curves and benchmarked against
corresponding SSPs under identical
conditions. The results reveal that the
SkSP-3 plan achieves notably smaller
sample sizes while preserving similar OC
behavior, particularly at low defect
levels. This work contributes to the
body of literature by presenting a
robust and cost-effective methodology
for designing SkSPs under Borel
distribution assumptions, thereby
enhancing inspection efficiency without
compromising quality standards.
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Cite: Jayalakshmi S., Gopinath M.
DESIGN OF SKIP LOT SAMPLING PLAN
(SKSP-3) WITH SINGLE SAMPLING PLAN AS A
REFERENCE PLAN USING BOREL DISTRIBUTION.
Reliability: Theory & Applications.
2025, September 3(86): 758-768, DOI: https://doi.org/10.24412/1932-2321-2025-386-758-768
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ANALYZING SOLUTIONS OF
FUZZY NABLA DYNAMIC EQUATIONS ON
TIMESCALES: A GENERALIZED HUKUHARA
APPROACH |
769-783 |
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|
Leelavathi R., Hari Kishore R., Mohana
Rupa S. V. D., Muneera A. |
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In this paper, we study linear
first-order fuzzy nabla dynamic
equations on time scales (LFNDET's)
under the framework of generalized
Hukuhara nabla differentiability and
also interpret various results of
LFNDET's by employing the Variation of
constant formula. A key result concerns
the generalized nabla Hukuhara
derivative for the product of a crisp
function and a fuzzy function on time
scales. Furthermore, we derive solutions
to these equations using various
approaches to generalized Hukuhara nabla
differentiability. The behavior of these
solutions highlights the importance and
applicability of the generalized fuzzy
nabla derivative in the context of nabla
dynamic equations on time scales.
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Cite: Leelavathi R., Hari Kishore R.,
Mohana Rupa S. V. D., Muneera A.
ANALYZING SOLUTIONS OF FUZZY NABLA
DYNAMIC EQUATIONS ON TIMESCALES: A
GENERALIZED HUKUHARA APPROACH.
Reliability: Theory & Applications.
2025, September 3(86): 769-783, DOI: https://doi.org/10.24412/1932-2321-2025-386-769-783
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EXPLORING REDUNDANCY
OPTIMIZATION TECHNIQUES FOR SYSTEM
PERFORMANCE |
784-800 |
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|
Parveen Kumar, Dalip Singh, Anil Kumar
Taneja |
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|
System reliability optimization remains
a dynamic and evolving challenge,
influenced by continuous advancements in
mathematical modeling, engineering
innovation, and management strategies.
This study includes documents on
reliability, availability,
maintainability, dependability,
testability, cost-benefit analysis,
life-cycle failures, maintenance
modeling, and asset integrity management.
However, this article is mainly
concerned with documents that focus on
redundancy optimization problems (i.e.,
k out of n system, warm, hot, cold
standby redundancy, system reliability
analysis in different failure and repair
conditions, redundancy allocation in
several system configurations, and so on)
that apply to Telecommunications,
Aerospace and Aviation, Industrial
Automation, Network Servers and IT
Systems, Transportation Systems. In
addition, documents on the Oil and Gas
Industry, Data Centers, and critical
Infrastructure that are part of process
industries are included. We analyze as
many documents as possible by combining
commonly used keywords. Additionally,
the paper identifies emerging trends
such as adaptive and hybrid redundancy
strategies and the integration of
intelligent techniques like Supplymentry
variable techniques, regenerative point
techniques, Genetic algorithm, and
machine learning for real-time
reliability management. By synthesizing
findings from recent literature, this
review aims to guide future research and
practical implementations, supporting
the design of cost-effective, robust,
and resilient systems for modern
computing environments.
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Cite: Parveen Kumar, Dalip Singh, Anil
Kumar Taneja EXPLORING REDUNDANCY
OPTIMIZATION TECHNIQUES FOR SYSTEM
PERFORMANCE . Reliability: Theory &
Applications. 2025, September 3(86):
784-800, DOI: https://doi.org/10.24412/1932-2321-2025-386-784-800
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TWO STAGE FLOW SHOP
SCHEDULING PROBLEM INCLUDING PROBABILITY
UNDER LR FUZZY NUMBER |
801-815 |
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Pooja Kaushik, Deepak Gupta, Sonia Goel |
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Often known as the hybrid flow shop (HFS),
the scheduling of flow shops with
several parallel machines per stage is a
challenging integrated problem that
arises in many real-world scenarios.
This study addresses bi stage flow shop
scheduling problem involving parallel
equipotential machines at each stage,
where processing times are characterized
as LR-type fuzzy numbers to encapsulate
inherent uncertainties. Recognizing the
criticality of minimizing the makespan
under imprecise conditions, we employ
four distinct reference functions to
compute fuzzy makespan, thereby offering
a diversified perspective on solution
robustness. Four distinct fuzzy ranking
(reference) functions are employed for
defuzzification and comparison. The
scheduling problem is solved using a
Branch and Bound (B&B) algorithm
tailored to accommodate fuzzy parameters
and parallel machine constraints.
Comparative analyses with an adapted
version of branch and bound method are
conducted to benchmark performance under
varying degrees of fuzziness. Results
underscore the efficacy and adaptability
of the proposed approach, revealing
nuanced improvements in makespan
estimation and scheduling performance
across varying fuzziness levels. This
investigation not only enriches the
theoretical landscape of fuzzy
scheduling but also provides practical
insights for complex manufacturing
systems operating under uncertainty.
This work not only extends classical
scheduling methodologies into the fuzzy
domain but also highlights the potential
of integrating multiple reference
functions within exact solution
frameworks. The objective is to minimize
the makespan under fuzzy conditions. To
handle the fuzziness in processing times,
A comparative analysis of the results
obtained using each reference function
is conducted to evaluate their
effectiveness in producing optimal or
near-optimal schedules. The study
highlights the impact of the choice of
reference function on the computational
efficiency and solution quality,
offering insights for better
decision-making in uncertain
manufacturing scenarios. These functions
serve to transform fuzzy numbers into
comparable crisp values, thereby
enabling traditional scheduling
algorithms to process the data
effectively. The focus of this research
is to evaluate the impact of each
reference function on the scheduling
performance and to analyze the variation
in results with respect to makespan
minimization. The findings offer
significant theoretical contributions to
fuzzy scheduling literature and
practical implications for industries
where uncertainty in processing times is
a critical factor.
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Cite: Pooja Kaushik, Deepak Gupta,
Sonia Goel TWO STAGE FLOW SHOP
SCHEDULING PROBLEM INCLUDING PROBABILITY
UNDER LR FUZZY NUMBER. Reliability:
Theory & Applications. 2025, September
3(86): 801-815, DOI: https://doi.org/10.24412/1932-2321-2025-386-801-815
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FERMATEAN
QUADRIPARTITIONED NEUTROSOPHIC FUZZY
GRAPH |
816-828 |
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V. Divya, J. Jesintha Rosline |
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A fuzzy graph is a mathematical
technique that represents relationship
of an objects with uncertainty or
imprecision, using nodes and edges with
membership degrees to indicate the
strength of connections. It provides an
important paradigm for modelling and
handling real world optimization tasks.
Neutrosophic graphs extend classical
graph theory to handle uncertain,
imprecise and inconsistent information,
enabling the modeling of complex
relationships with varying degrees of
truth, indeterminacy and falsity. This
framework provides a more nuanced
understanding of complex systems,
allowing for improved accuracy and
increased flexibility in decision-making,
network analysis and optimization
problems. Neutrosophic graphs can be
applied to various fields, including
multi-criteria decision-making, supply
chain management and logistics, where
uncertain or imprecise data is common.
The extension of Neutrosophic set is the
Quadripartitioned Neutrosophic Set. The
division of indeterminacy function of
the Neutrosophic set into the
contradiction and ignorance component is
termed as Quadripartitioned Neutrosophic
Set. Associated with each vertex are
values of truth, contradiction,
ignorance and falsity that reflects it
characteristics of a graph. Similarly,
for each edge, these values signify the
strength or reliability of the
relationship between the connected
vertices. Quadripartitioned Neutrosophic
Fuzzy graph gives an accurate
representation of uncertainty which
leads to a greater clarity of complex
systems and relationships. It has an
emerging applications in social network
analysis, image processing and decision
making systems. Fermatean Neutrosophic
Graph is a hybrid model of Fermatean and
Neutrosophic graph. This enhancement
provides an increased capacity to handle
uncertain and unclear data. In contrast
to traditional neutrosophic values, this
framework operates with truth,
indeterminacy and falsity membership
degrees constrained by the condition
that the sum of their third powers is
less than or equal to two. In this
article, a new graph is defined called
Fermatean Quadripartitioned Neutrosophic
Fuzzy Graph (FQNFG). We proposed the
order, size, complete, complement and
strong of Fermatean Quadripartitioned
Neutrosophic Fuzzy Graph. Furthermore,
the paper establishes operations for
FQNFG such as composition, Cartesian
product, Cross product and lexicographic
product are also studied.
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Cite: V. Divya, J. Jesintha Rosline
FERMATEAN QUADRIPARTITIONED NEUTROSOPHIC
FUZZY GRAPH. Reliability: Theory &
Applications. 2025, September 3(86):
816-828, DOI: https://doi.org/10.24412/1932-2321-2025-386-816-828
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RELIABILITY BASED AN
ATTRIBUTE CONTROL CHART USING
EXPONENTIATED EXPONENTIAL- POISSON
DISTRIBUTION UNDER HYBRID CENSORING |
829-840 |
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B. Gokila, A. Sheik Abdullah |
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The Exponentiated Exponential-Poisson (EEP)
distribution, an advanced extension of
traditional lifetime models, offers
greater adaptability in representing
product lifetimes by more precisely
capturing variations in failure rates.
To handle incomplete lifetime data, a
Hybrid censoring technique is employed,
combining elements of both Type-I and
Type-11 censoring to establish a more
robust methodology for lifetime analysis.
Naturally, np control charts are used to
monitor the count of defective units
within a sample. The primary aim is to
detect shifts in product lifetime
distributions, which are crucial for
quality control and reliability
assessment. However, this study
introduces a modification to the control
chart, shifting its focus from simply
counting failures to tracking the median
lifetime, thereby enhancing its
capability to identify changes in
product reliability over time. The
efficiency of the control chart is
measured using the Average Run Length (ARE),
which estimates the expected number of
observations before an out-of-control
signal is triggered. By carefully
adjusting the chart's parameters, the
study ensures that the in-control ARL
aligns closely with a predefined target,
thereby improving its reliability. This
research is dedicated to developing an
np control chart designed to monitor the
median lifetime of products that follow
the EEP distribution within a Hybrid
censoring Scheme. Numerical examples and
simulated data are provided to
illustrate its real-world applicability.
By optimizing control chart parameters
based on ARL, the study enhances
monitoring precision for product
reliability, making it a valuable tool
in industries where accurate lifetime
assessment is critical.
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Cite: B. Gokila, A. Sheik Abdullah
RELIABILITY BASED AN ATTRIBUTE CONTROL
CHART USING EXPONENTIATED EXPONENTIAL-
POISSON DISTRIBUTION UNDER HYBRID
CENSORING. Reliability: Theory &
Applications. 2025, September 3(86):
829-840, DOI: https://doi.org/10.24412/1932-2321-2025-386-829-840
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ENHANCING THE
RELIABILITY OF POWER SYSTEMS BY
OPTIMIZING LIGHTNING PROTECTION OF
OVERHEAD TRANSMISSION LINES |
841-852 |
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Elbrus Ahmedov, Kubra Mukhtarova |
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This paper addresses the reliability
issues of power systems caused by
lightning-induced overvoltages resulting
from lightning strikes to components of
overhead transmission lines (OHL). It is
demonstrated that lightning discharges
are one of the key causes of
transmission line outages and
significant economic losses. A method is
proposed to improve the efficiency of
lightning protection by upgrading the
design of lightning protection cables
using V-shaped metallic elements to
increase the protection zone.
Calculations were carried out to assess
the expansion of the protection zone
depending on the geometrical parameters
of the design. A mathematical model was
developed and implemented in the MATLAB
Simulink environment to analyze the
behavior of OHL under direct lightning
strikes to the shield wire and phase
conductors. The model takes into account
lightning current parameters, structural
characteristics of supports, grounding
device properties, and insulation
parameters. Simulation results showed a
significant influence of grounding
resistance on the level of resulting
overvoltages and the effectiveness of
lightning protection. The proposed
technical solutions can be used to
enhance the lightning resistance and
operational reliability of overhead
transmission lines, especially in
regions with high lightning activity.
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Cite: Elbrus Ahmedov, Kubra Mukhtarova
ENHANCING THE RELIABILITY OF POWER
SYSTEMS BY OPTIMIZING LIGHTNING
PROTECTION OF OVERHEAD TRANSMISSION
LINES. Reliability: Theory &
Applications. 2025, September 3(86):
841-852, DOI: https://doi.org/10.24412/1932-2321-2025-386-841-852
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ON RELIABILITY
STRESS-STRENGTH MODEL USES SHOCK-MODEL
APPROACH TO FOLLOW MUKHERJEE-ISLAM
DISTRIBUTION |
853-861 |
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Vijayakumar. B., M. Manoharan |
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A component or system exposed to shocks
will result in system or device damage.
The strength of a produced product is a
variable quantity that requires
modelling as a random variable. It is
necessary to evaluate the stress
conditions of the operating system.
Strength and stress are both thought of
as random variables, which is made clear
by the term "stress-strength model."
With the inter-arrival time following
the Mukherjee-Islam distribution and
strength following an exponential
distribution, we attempted to create a
model in this study. Graphs are used to
support numerical examples that are
provided.
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Cite: Vijayakumar. B., M. Manoharan ON
RELIABILITY STRESS-STRENGTH MODEL USES
SHOCK-MODEL APPROACH TO FOLLOW
MUKHERJEE-ISLAM DISTRIBUTION.
Reliability: Theory & Applications.
2025, September 3(86): 853-861, DOI: https://doi.org/10.24412/1932-2321-2025-386-853-861
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DESIGN AND FABRICATION
OF HIGH-GAIN, LOW CROSS-POLARIZATION
PLANAR VIVALDI ANTENNA FOR UWB
APPLICATIONS |
862-874 |
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Balvant J Makwana, Shahid S. Modasiya |
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This paper presents the design,
simulation, and experimental validation
of a corrugated Vivaldi antenna
optimized for ultra-wideband (UWB)
operation at high bandwidth. Fabricated
on glass epoxy substrate, the antenna
employs edge corrugations to minimize
cross-polarization while maintaining
high gain across the operational
bandwidth. Full-wave electromagnetic
simulations guided the design
optimization, with radiation patterns
and return loss parameters serving as
key performance metrics. A prototype was
fabricated and tested in an anechoic
chamber, yielding a measured high gain
with a very good peak gain over a wide
range of frequency. Cross-polarization
levels were effectively suppressed,
ranging from approximately very low at
both high and low frequencies. The close
agreement between simulated and measured
return loss parameters with impedance
matching better and radiation
characteristics validates the proposed
design methodology. The presented
approach confirms that cost-effective
glass epoxy substrates can achieve
performance comparable to specialized
high-frequency materials when combined
with strategic geometric modifications.
The design is well suited for UWB
applications in radar, wireless
communication, and microwave imaging
systems.
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Cite: Balvant J Makwana, Shahid S.
Modasiya DESIGN AND FABRICATION OF
HIGH-GAIN, LOW CROSS-POLARIZATION PLANAR
VIVALDI ANTENNA FOR UWB APPLICATIONS.
Reliability: Theory & Applications.
2025, September 3(86): 862-874, DOI: https://doi.org/10.24412/1932-2321-2025-386-862-874
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AIRPORT SAFETY
MANAGEMENT: A PROACTIVE MODEL BASED ON
RISK ASSESSMENT AND BENCHMARKING |
875-891 |
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Abdellah
Hanine, Abdellah El Barkany |
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This study presents a practical,
context-sensitive approach to managing
airport safety that combines the PDCA
cycle with benchmarking techniques
within a structured risk assessment
framework. Given that ensuring
operational safety in airports requires
precisely recognizing, classifying, and
successfully mitigating specific hazards,
this study addresses this issue by
creating a tailored risk assessment
table. This tool, designed specifically
for airport environments, clearly
categorizes hazards based on their
likelihood and severity and uses a novel
equation developed in this study to
correctly determine Safety Performance
Indicators (SPI) and Safety Performance
Targets (SPT). These indicators allow
safety managers to effectively track
performance trends, compare outcomes to
other airports, and align safety
policies with ICAO regulations. The
cyclical nature of repetitive
improvement in PDCA is assured, and
value is added through benchmarking by
applying tested best practices,
enhancing the quality of decisions. A
case study with airport safety
practitioners establishes the practical
applicability and value of this
methodology in risk prioritization and
pushing forward the drivers of
corrective action. Collectively, the
results demonstrate how this strategy
supports proactive risk control and
operational safety, and develops a
sustainable culture of continuous
improvement—a key component of effective
airport safety management.
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Cite: Hanine, A., El Barkany,
A. AIRPORT SAFETY MANAGEMENT: A
PROACTIVE MODEL BASED ON RISK ASSESSMENT
AND BENCHMARKING. Reliability: Theory &
Applications. 2025, September 3(86):
875-891, DOI: https://doi.org/10.24412/1932-2321-2025-386-875-891
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ON COPING WITH
CENSORING IN SURVIVAL DATA USING FUZZY
THEORY |
892-898 |
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Jaisankar, R., Haripriya, H. |
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Aim: The problem of censoring is the
main concern in Survival Analysis which
makes the analysis complex and may lead
to unreliable results like less precise
parameter/survival/hazard estimates,
wider confidence intervals, reduced
power to detect differences between
groups, sometimes especially when the
proportion of censored observations is
high. In particular, if the censoring is
informative that is reacted to the event,
serious bias may be expected to present
in the estimates. Omitting censored
observations prices with loss of
information and adding them is often
embedded with a lack of information. It
is proposed to implement fuzzy
methodology for dealing with censored
observations in Survival data so as to
minimize their impact on the survival/hazard
estimates. This paper suggests a
modified approach based on the Fuzzy
Theory, in which, the censored
observations could be incorporated
effectively. Methods: Many statistical
procedures are advised to tackle
censoring, in both parametric and
non-parametric realms. However, their
application mainly depend on the nature
of censoring, whether right or left or
interval censored. Even when their
applied, still some lacuna may persist
which could be completely eradicated
when there is no censoring. Different
types of fuzzy numbers are applied both
to the censored and uncensored
observations according to their nature
and the results of the same were tested
in case of the non-parametric procedure,
the Kaplan-Meier estimator, using log
rank test. Results: On the application
of the proposed methodology one may
obtain the survival probabilities which
are reasonably calculated for even
censored observations. The median
survival time observed by the
application of this methodology gives
lesser value than the median obtained by
the classical Kaplan eier method. The
survival curve obtained by the proposed
method is different from the survival
curve of the classical Kaplan eier
method and since the proposed
methodology addresses all points of time
and hence may give reliable estimates of
survival probability. Conclusion: When
compared with the classical Kaplan-Meier
method, the proposal method gives
survival probabilities which are
slightly differ from the estimate
obtained from non-fuzzy methodology.
Since the survival probabilities can be
calculated even for censored
observations using fuzzy numbers, it is
expected that the proposed modelling may
be better than the classical
Kaplan-Meier estimator.
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Cite: Jaisankar, R., Haripriya, H. ON
COPING WITH CENSORING IN SURVIVAL DATA
USING FUZZY THEORY. Reliability: Theory
& Applications. 2025, September 3(86):
892-898, DOI: https://doi.org/10.24412/1932-2321-2025-386-892-898
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BIOGEOGRAPHY-BASED
RELIABILITY OPTIMIZATION |
899-908 |
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Deepika Garg, Sarita Devi, Doorgeshwaree
Devi Heeramun, Nakul Vashishth |
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Biogeography-based optimization (BBO) is
an effective optimization algorithm
originally introduced by Dan Simon in
2008. It is inspired by the principles
of biogeography. It mimics the process
of migration and colonization of
different species, where the behavior of
species is determined by their habitats
and the available resources. However,
BBO can suffer from slow convergence and
premature convergence for
high-dimensional optimization problems.
To address these issues,
opposition-based learning (OBL) has been
integrated with BBO. OBL uses the
concept of generating an opposite
solution to an existing solution and
combining them to form a new search
direction. This helps to improve the
diversity of the population and
accelerate the convergence speed of the
algorithm. The combination of BBO and
OBL has shown promising results in
solving various optimization problems,
including engineering design, scheduling,
and feature selection. This approach has
proved to be efficient and robust,
making it an attractive alternative to
other optimization algorithms. In this
research study, the redundancy
Allocation Problem (RAP) is solved with
BBO and OBL-BBO. Computational results
confirm the robustness and superiority
of this new model over previous ones in
optimizing the reliability of the system.
Besides, the proposed algorithm OBL-BBO
outperforms the previous ones BBO in
finding good results.
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Cite: Deepika Garg, Sarita Devi,
Doorgeshwaree Devi Heeramun, Nakul
Vashishth BIOGEOGRAPHY-BASED RELIABILITY
OPTIMIZATION. Reliability: Theory &
Applications. 2025, September 3(86):
899-908, DOI: https://doi.org/10.24412/1932-2321-2025-386-899-908
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IMPROVING THE
RELIABILITY OF SOLAR ENERGY SYSTEMS
USING FLOATING PHOTOVOLTAIC TECHNOLOGIES |
909-919 |
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M.T.Babayev |
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This paper explores floating solar
panels (FSPs) as a promising and
cost-effective solution for enhancing
the reliability and sustainability of
solar power systems. The analysis
focuses on the technical, environmental,
and economic benefits of FSPs compared
to traditional land-based installations.
Floating systems offer improved
operational reliability and energy
efficiency due to natural cooling, land
conservation, lower environmental impact,
and reduced water evaporation —
particularly vital in regions with
limited freshwater resources. Deploying
FSPs on artificial reservoirs and
flooded quarries not only reduces
land-use pressure but also contributes
to lower capital and operational
expenditures. Case studies from
Azerbaijan and Japan demonstrate the
reliability, resilience, and ecological
viability of floating solar solutions
under various climatic conditions.
Although initial investments may be
higher, long-term assessments reveal
that FSPs can deliver more consistent
performance and greater
cost-effectiveness in regions with high
solar irradiance and available water
surfaces. The paper provides a
comprehensive overview of floating
photovoltaic technologies, highlighting
their role in improving the reliability
and stability of solar energy supply.
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Cite: M.T.Babayev IMPROVING THE
RELIABILITY OF SOLAR ENERGY SYSTEMS
USING FLOATING PHOTOVOLTAIC TECHNOLOGIES.
Reliability: Theory & Applications.
2025, September 3(86): 909-919, DOI: https://doi.org/10.24412/1932-2321-2025-386-909-919
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RELIABILITY-BASED
OPTIMIZATION OF TWO-WAREHOUSE SUPPLY
CHAIN MODELS |
920-933 |
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Ajay Singh Yadav, S. Viswanathan, Navin
Ahlawat, Bhavani Viswanathan, Anupam
Swami |
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This study presents a reliability-based
optimization framework for managing a
two-warehouse inventory system in the
dairy industry, specifically addressing
the complexities posed by product
spoilage, shortages, and inflation. The
proposed mathematical model integrates
key inventory management principles with
spoilage dynamics, shortage scenarios,
and economic inflation, under a
First-In-First- Out (FIFO) dispatching
policy. By prioritizing the shipment of
older stock, the model aims to reduce
spoilage and enhance product turnover.
It incorporates dairy product expiration
rates to determine optimal replenishment
and dispatch strategies while also
identifying and mitigating potential
operational bottlenecks. Additionally,
the influence of inflation on
inventory-related costs is embedded
within the model to reflect real-world
economic fluctuations. Through the
application of advanced optimization
algorithms implemented in MATLAB, the
model seeks to minimize total inventory
costs and improve supply chain
efficiency. Overall, this research
offers a comprehensive and practical
tool for enhancing inventory
decision-making in perishable goods
industries like dairy.
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Cite: Ajay Singh Yadav, S. Viswanathan,
Navin Ahlawat, Bhavani Viswanathan,
Anupam Swami RELIABILITY-BASED
OPTIMIZATION OF TWO-WAREHOUSE SUPPLY
CHAIN MODELS. Reliability: Theory &
Applications. 2025, September 3(86):
920-933, DOI: https://doi.org/10.24412/1932-2321-2025-386-920-933
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ANALYSIS OF M, MAP/PH/2
NON- PREEMPTIVE PRIORITY QUEUEING
INVENTORY SYSTEM WITH BREAKDOWN, REPAIR
AND (s, S) POLICY |
934-948 |
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G. Ayyappan, M. Thilakavathy |
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We analyze a non-preemptive priority
queueing model in this research that has
two heterogeneous servers, each of which
has its own queue. Queue 1 possesses a
low priority status with infinite
capacity and queue 2 possesses a high
priority status with finite capacity. We
made the assumption that arrival follows
M, MAP and service time follows
Phase-type distribution. Server 1 is
always available in the system; Server 2
is an unreliable server. With a (s, S)
policy, the inventory is filled up and
an exponential distribution is scheduled
for the replenishment time. Using the
matrix analytical approach, a stationary
probability vector was assessed, and a
stability criterion was created for our
system. Performance metrics are also
studied using this technique. Both two
and three-dimensional displays are used
to show the numerical examples.
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Cite: G. Ayyappan, M. Thilakavathy
ANALYSIS OF M, MAP/PH/2 NON- PREEMPTIVE
PRIORITY QUEUEING INVENTORY SYSTEM WITH
BREAKDOWN, REPAIR AND (s, S) POLICY .
Reliability: Theory & Applications.
2025, September 3(86): 934-948, DOI: https://doi.org/10.24412/1932-2321-2025-386-934-948
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ABOUT WAYS TO INCREASE
RELIABILITY AND ECONOMY OF STEAM BOILER
INSTALLATIONS OF BLOCK POWER PLANTS |
949-958 |
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Farzaliyev Y.Z. |
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The new method and algorithm of
management by reliability and
profitability of work of steam boiler
installations block power stations is
developed. The essence of a method is
reduced to definition of "weak parts»
and to formation of recommendations. In
a basis of a database and program model,
there are results of measurement and
calculation of technical and economic
parameters steam boiler installations.
And the method allows to formulate the
main directions of increasing the
efficiency of individual control steam
boiler installations and steam boiler
installations of power plants as a whole.
Improving the efficiency management
system of the steam boiler installations
allows, first of all, to reduce
operating costs. The developed method
allows us to consider the obtained
results as methodological support for
personnel in organizing the operation,
maintenance and repair of steam boiler
installation. Therefore, the relevance
of this problem is obvious
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Cite: Farzaliyev Y.Z. ABOUT WAYS TO
INCREASE RELIABILITY AND ECONOMY OF
STEAM BOILER INSTALLATIONS OF BLOCK
POWER PLANTS. Reliability: Theory &
Applications. 2025, September 3(86):
949-958, DOI: https://doi.org/10.24412/1932-2321-2025-386-949-958
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A NOVEL METHOD TO
ASSESSING PROCESS VARIATION WITH A
CONFIDENCE INTERVAL OF SAMPLE STANDARD
DEVIATION |
959-964 |
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Boya Venkatesu, G. Siva, Christophe
Chesneau, V. Sai Sarada |
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One of the great tools of statistical
process control for evaluating patterns
of variation in the process is the
control chart. In this article, we focus
on developing a new approach to
estimating process parameters in a
control chart using confidence intervals
(CIs) of sample standard deviations.
They have the property of providing
additional information about the quality
of the estimate. A Monte Carlo
simulation is used to investigate the
accuracy of the obtained CIs. The
performance of the classical and new
approaches is compared in terms of
standard error using simulated samples.
The simulation results show that the new
approach outperforms the classical
approach.
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Cite: Boya Venkatesu, G. Siva,
Christophe Chesneau, V. Sai Sarada A
NOVEL METHOD TO ASSESSING PROCESS
VARIATION WITH A CONFIDENCE INTERVAL OF
SAMPLE STANDARD DEVIATION. Reliability:
Theory & Applications. 2025, September
3(86): 959-964, DOI: https://doi.org/10.24412/1932-2321-2025-386-959-964
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DIFFERENT ESTIMATION
METHODS AND VALIDATION FOR THE EXTENSION
EXPONENTIAL DISTRIBUTION |
965-980 |
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Rochdi Nouadri, Nacira Seddik-Ameur,
Khaoula Aidi |
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This study investigates the extended
exponential distribution proposed by
Nadarajah and Haghighi, which can
effectively model data with a mode at
zero and accommodate varying hazard
rates—whether increasing, decreasing, or
constant. Unlike other distributions, it
allows for scenarios where the hazard
function increases while the probability
density function decreases monotonically.
The focus is on exploring alternative
estimation methods to maximum likelihood
estimation for this distribution,
including the maximum product of spacing,
Cramer-von Mises, Anderson-Darling,
Right-tail Anderson-Darling, Left-tail
Anderson-Darling, and Kolmogorov-
Smirnov tests. A novel approach using
initial data is proposed to develop an
effective goodness-of- fit criterion
tailored for validating this model.
Extensive simulations with thousands of
samples are conducted to assess the
performance of these estimation methods
and the practicality of the proposed
goodness-of-fit test. Real data
applications are also utilized to
demonstrate the applicability and
effectiveness of the extended
exponential distribution in real-world
scenarios. This research expands the
statistical modelling toolkit by
providing robust estimation techniques
and validation criteria specifically
designed for the characteristics of the
extended exponential distribution.
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Cite: Rochdi Nouadri, Nacira
Seddik-Ameur, Khaoula Aidi DIFFERENT
ESTIMATION METHODS AND VALIDATION FOR
THE EXTENSION EXPONENTIAL DISTRIBUTION.
Reliability: Theory & Applications.
2025, September 3(86): 965-980, DOI: https://doi.org/10.24412/1932-2321-2025-386-965-980
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CONSTRUCTION OF A NEW
ATTRIBUTE CONTROL CHART BASED ON
RAYLEIGH DISTRIBUTION UNDER HYBRID
CENSORING - A BAYESIAN APPROACH |
981-989 |
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T. Kavitha, M. Gunasekaran |
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Statistical Process Control (SPC) is a
quality control approach that makes use
of statistical tools to understand,
monitor, and improve a process. A
control chart is a tool for monitoring
process performance that consists of a
visual indication to detect anomalous
deviations because of assignable causes.
This chart compares the values of a
quality attribute to the control limits.
In the quality control process, the
control chart is often generated by
ignoring parameter uncertainty. The
identification of changes in the
parameter(s) within the probability
distribution of one or more
process-related variables is an
essential part of monitoring. Estimating
the parameters is essential since this
might have an impact on the control
chart's long-term performance in a
controlled or out-of-control condition.
This article provides a novel attribute
control chart in the form of a Bayesian
approach based on the Rayleigh lifetime
distribution and the Hybrid censoring
technique. A Bayesian approach will be
used to calculate the control chart
parameters and average run length. The
control chart parameters are determined
for various combinations of values, and
the performance of the developed control
chart is evaluated using the Average Run
Length (ARE). Numerical examples are
used to explain the proposed control
chart, and simulated data is used to
show how it might be used.
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Cite: T. Kavitha, M. Gunasekaran
CONSTRUCTION OF A NEW ATTRIBUTE CONTROL
CHART BASED ON RAYLEIGH DISTRIBUTION
UNDER HYBRID CENSORING - A BAYESIAN
APPROACH. Reliability: Theory &
Applications. 2025, September 3(86):
981-989, DOI: https://doi.org/10.24412/1932-2321-2025-386-981-989
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ENHANCING THE
RELIABILITY OF THERMAL POWER SYSTEMS
USING MEMBRANE-BASED WATER TREATMENT
TECHOLOGIES |
990-998 |
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Ahmadova J.A. |
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The reliability and efficiency of
thermal power plants (TPPs) are largely
determined by the quality of water
treatment systems that maintain a stable
water-chemical regime (WCR) for boilers
and auxiliary equipment. In scenarios
where seawater with high salinity and
variable composition is used as the
primary water source, conventional
treatment methods—such as ion exchange,
chemical coagulation, and thermal
desalination—prove inadequate and
resource-intensive. This study
investigates the application of a hybrid
membrane-based configuration comprising
ultrafiltration (UF), reverse osmosis (RO),
and membrane distillation (MD). The
proposed system enables the production
of high-purity demineralized water,
reduces operational risks, and lowers
energy consumption through the
utilization of low-grade waste heat.
Based on pilot data and modeled
performance, the UF-RO-MD cascade
achieves up to 99% desalination
efficiency with specific energy
consumption in the range of 1.9-2.5 kWh/m3
and a significant reduction in scaling
potential. A simplified case study is
provided to illustrate the high
effectiveness of membrane technologies
in enhancing the sustainability and
resilience of TPP operations, especially
in coastal regions with limited
freshwater availability.
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Cite: Ahmadova J.A. ENHANCING THE
RELIABILITY OF THERMAL POWER SYSTEMS
USING MEMBRANE-BASED WATER TREATMENT
TECHOLOGIES. Reliability: Theory &
Applications. 2025, September 3(86):
990-998, DOI: https://doi.org/10.24412/1932-2321-2025-386-990-998
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A
NOVEL ENERGY-EFFICIENT APPROACH TO
DETECT AND MITIGATE RPL ROUTING ATTACKS
IN IOT NETWORK |
999-1013 |
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Deepak Upadhyay, Hiteishi Diwanji |
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Communication networks are constantly at
risk from routing attacks, which have
the potential to disrupt the network
performance, information flow and
jeopardize network integrity. Network
resources and Energy consumption attacks
on the Internet of Things (IoT) are the
main targets to bring down the services
of Internet of Things devices with
attacks such as Denial of Service,
Jamming etc. Node mobility results in
frequent changes to network topology.
This increases energy consumption and
reduces node lifetimes, which can
disrupt overall network functionality.
To overcome these problems the author
has proposed a hybrid and lightweight A
Novel Energy-Efficient Approach to
Detect and Mitigate RPL (EEADM-RPL)
protocol considering control messages
with route metrics in different
detection and mitigation algorithm to
mitigate the Blackhole attack, Rank
attack and Sybil attacks under mobility
environment at a time. An attack
scenario created with the algorithms for
all attacks using control messages and
attributes of packets. The EEADM-RPL
protocol uses basic RPL control messages,
neighbor table, trust calculation, and a
minimum rank hysteresis objective
function to detect and eliminate the
attacks. This protocol is suitable for
industrial systems to handle
cyber-attack and for the Vulnerability
Assessment and Penetration Testing audit.
The Cooja simulator, part of the Contiki
operating system, simulates the attacks
without mobility and with mobility
demonstrates the effectiveness affecting
the network and the resources. The
outcomes of the simulation are compared
with those of current protocols.
According to the data, the proposed
protocol demonstrates improvements over
the conventional RPL protocols in
several metrics: the average parent
change ratio by 87.94%, the average
packet loss ratio by 69.17%, end-to-end
latency by 67.85%, and both energy
consumption and end-to-end delay by
13.07%.
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Cite: Deepak Upadhyay, Hiteishi Diwanji
A NOVEL ENERGY-EFFICIENT APPROACH TO
DETECT AND MITIGATE RPL ROUTING ATTACKS
IN IOT NETWORK. Reliability: Theory &
Applications. 2025, September 3(86):
999-1013, DOI: https://doi.org/10.24412/1932-2321-2025-386-999-1013
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EXPERT METHOD OF RANK
PENALTIES |
1014-1021 |
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Alexander Bochkov, Nikolay Zhigirev,
Alla Kuzminova |
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Voting methods include a variety of
systems and technologies designed to
facilitate the electoral process. These
methods can range from the use of
traditional paper ballots to modern
electronic systems, each with unique
features and functions. Heuristic peer
review methods use simplified
decision-making processes to evaluate
complex scenarios, especially in areas
such as usability and forecasting. These
methods improve efficiency and accuracy
by combining expert information with
heuristic principles to improve results
in a variety of applications. While
heuristic methods offer significant
advantages for expert evaluations, they
can also lead to errors if not applied
carefully, emphasizing the need for
balanced approaches to complex
evaluations. We propose an algorithm for
finding the most consistent decision of
experts in determining the leader in an
alternative ranking problem.
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Cite: Alexander Bochkov, Nikolay
Zhigirev, Alla Kuzminova EXPERT METHOD
OF RANK PENALTIES. Reliability: Theory &
Applications. 2025, September 3(86):
1014-1021, DOI: https://doi.org/10.24412/1932-2321-2025-386-1014-1021
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SYSTEM RELIABILITY AND
PROFITABILITY CONSIDERING CONCEPTS OF
WARRANTY AND INSURANCE: AN OVERVIEW |
1022-1039 |
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Kajal Sachdeva, Gulshan Taneja, Amit
Manocha |
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The concepts of reliability, warranty,
and insurance are interwoven in certain
respects. System warranties and
insurance coverage, whether provided by
the manufacturer or a third party,
reflect the system's potential
reliability and offer consumers a sense
of security. Conversely, enhancing
system reliability during the
development process can help reduce
warranty and insurance costs. The
purpose of this study is to compile the
existing literature and provide a
structured review of system reliability
evaluation, incorporating the concepts
of warranty, pricing, and insurance
policies. Synthesizes the ideas, models,
and methodologies that various authors
have included in their study. To achieve
this, a detailed review of 111 journal
articles published between 1992 and the
present was conducted. The primary focus
areas of the review include system
reliability, warranty policies,
insurance mechanisms, and cost analysis.
In addition, the study highlights
potential directions for future research
in this domain.
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Cite: Kajal Sachdeva, Gulshan Taneja,
Amit Manocha SYSTEM RELIABILITY AND
PROFITABILITY CONSIDERING CONCEPTS OF
WARRANTY AND INSURANCE: AN OVERVIEW.
Reliability: Theory & Applications.
2025, September 3(86): 1022-1039, DOI: https://doi.org/10.24412/1932-2321-2025-386-1022-1039
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ATTRIBUTE CONTROL
CHART BASED ON RAYLEIGH DISTRIBUTION: A
BAYESIAN APPROACH |
1040-1053 |
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M. Gunasekaran, T. Kavitha, S. M.
Karthik |
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Statistical Process Control is a quality
control approach that uses statistical
tools to assess, monitor, and optimize
processes. A control chart plays a
crucial role in this method by tracking
the performance of a process and
providing a visual signal to detect any
irregular deviations caused by specific
assignable factors. It compares the
values of a quality attribute against
predetermined control limits. In typical
quality control procedures, control
charts are often created without
considering parameter uncertainty.
However, it is essential to identify any
shifts in the parameters of the
probability distribution linked to one
or more variables associated with the
process to ensure effective monitoring.
Evaluating these parameters is vital, as
it can influence the long-term
functionality of the control chart in
both controlled and uncontrolled
environments. This article introduces an
innovative attribute control chart that
utilizes a Bayesian methodology based on
the Rayleigh lifetime distribution,
specifically applied under accelerated
life testing with a hybrid censoring
technique. The parameters for the
control chart will be established
through various combinations of values
using a Bayesian approach, while the
effectiveness of the control chart will
be evaluated through the Average Run
Length (ARL). Numerical examples will
illustrate the proposed control chart,
and simulated data will showcase its
potential application. The effectiveness
of the proposed control chart will be
quantified through ARLs for different
shift constants, sample sizes, and
additional parameters such as p, Lower
Control Limit, and Upper Control Limit.
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Cite: M. Gunasekaran, T. Kavitha, S. M.
Karthik ATTRIBUTE CONTROL CHART BASED ON
RAYLEIGH DISTRIBUTION: A BAYESIAN
APPROACH . Reliability: Theory &
Applications. 2025, September 3(86):
1040-1053, DOI: https://doi.org/10.24412/1932-2321-2025-386-1040-1053
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