HOW TO PROPERLY APPLY SYSTEMS OF ARTIFICIAL INTELLIGENCE

H. Schäbe, I.B. Shubinsky

The authors present their views on the essence of systems with artificial intelligence and point out the limitations to the use of those systems. Based on these considerations, an approach for the correct and effective use of artificial intelligence is proposed. A system with artificial intelligence (SAI) is in fact a very flexible statistical model with many parameters, which cannot be interpreted. Therefore, the use of an SAI is like a brute force attack using a very flexible statistical model to a problem. The sample which is used to train the SAI becomes much more important than the method itself. SAI can be used for safety applications, but the result of an SAI must be verified and that a proof of safety must be maintained. Mostly, this proof must be based on statistical arguments. A best approach for a use of a SAI is if it supports the developer for specific and well specified problem.

Cite: H. Schäbe, I.B. Shubinsky HOW TO PROPERLY APPLY SYSTEMS OF ARTIFICIAL INTELLIGENCE. Reliability: Theory & Applications. 2024, December 4(80): 31-35, DOI: https://doi.org/10.24412/1932-2321-2024-480-31-35 

31-35

APPLICATION OF THE DPSIR FRAMEWORK FOR SIBERIAN COMMUNITIES

Olga Derendiaeva, Valery Akimov

The development of Siberia is a priority for the Russian government as it has great economic potential. However, the benefits for local populations are unclear, as economic expansion affects traditional livelihoods and social development. The challenges faced by the local population are, to some extent, relevant for all traditional communities in the world. While a huge amount of research is devoted to ongoing socio-economic processes in developing countries, about the transformations in Russian Siberia. In this paper DPSIR approach used to identify driving forces, pressures, states, impact and responses within Siberian communities. New indicators were proposed for a policy analysis.

Cite: Olga Derendiaeva, Valery Akimov APPLICATION OF THE DPSIR FRAMEWORK FOR SIBERIAN COMMUNITIES. Reliability: Theory & Applications. 2024, December 4(80): 36-48, DOI: https://doi.org/10.24412/1932-2321-2024-480-36-48

36-48

DETERMINATION OF STABILITY AND RELIABILITY OF SHORTEST PATHS IN A GRAPH THROUGH LISTS OF LABELS IN DIJKSTRA’S ALGORITHM

G.Sh. Tsitsiashvili

In this paper, the problem of determining all shortest paths is solved in a weighted graph. For a weighted graph, the path length is defined as the sum of the lengths of its edges. This problem is solved by generalizing the well-known Dijkstra algorithm by introducing a list of labels. In the list of labels at each vertex of the graph, the first label determines the length of the shortest path. The second label is defined by a set of vertices, from which directed edges exit to the vertex in question. To reduce the required memory and determine the reliability of the shortest paths, the number of edges of the shortest paths entering the vertices of the graph is introduced and recursively calculated. The stability of shortest paths is calculated recursively, as the number of edges, paths entering the vertices of the graph and deviating from the minimum length by a given amount. These results extend to unweighed and planar graphs.

Cite: G.Sh. Tsitsiashvili DETERMINATION OF STABILITY AND RELIABILITY OF SHORTEST PATHS IN A GRAPH THROUGH LISTS OF LABELS IN DIJKSTRA’S ALGORITHM. Reliability: Theory & Applications. 2024, December 4(80): 49-54, DOI: https://doi.org/10.24412/1932-2321-2024-480-49-54

49-54

THE WEIGHTED SABUR DISTRIBUTION WITH APPLICATIONS OF LIFE TIME DATA

Suvarna Ranade, Aafaq A. Rather

In this paper, we propose a weighted version of Sabur distribution. The Stability of distribution are studied with structural properties, moments generating functions, likelihood ratio test, entropy measures, order statistics and Fisher’s information matrix. The new model provides flexibility to analyse complex real data. Application of model on real data sets shows that the weighted Sabur distribution is quite effective. In this paper we utilize Monte Carlo simulation to evaluate the effectiveness of estimators. We used our weighted Sabur distribution on two real data set, Anderson-Darling and Cramer-von Mises class of quadratic EDF statistics utilize to test whether a given sample of data is drawn from a weighted Sabur distribution.

Cite: Suvarna Ranade, Aafaq A. Rather THE WEIGHTED SABUR DISTRIBUTION WITH APPLICATIONS OF LIFE TIME DATA. Reliability: Theory & Applications. 2024, December 4(80): 55-67, DOI: https://doi.org/10.24412/1932-2321-2024-480-55-67

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STATISTICAL AND DEEP-LEARNING BASED DISASTER IDENTIFICATION MODELLING USING UNMANNED AERIAL VEHICLE SYSTEMS FOR EMERGENCY RESPONSE

Mustafa Kamal, Mohammad Faisal Khan, Shahnawaz Khan

Unmanned aerial vehicle systems offer a significant impact for the prediction of disaster identification and management by integrating both statistical and neural network techniques. Existing disaster response systems primarily rely on manual reporting or satellite imagery which are prone to delays and inefficiencies. The present study presents a statistical modelling using structural equation model integrated with deep learning-based model to enhance prediction accuracy. The model takes input variables such as unmanned aerial vehicle altitude, speed, area coverage, temperature, and population density to predict a disaster index. The structural equation model analysis revealed that all the input variables unmanned aerial vehicle altitude, speed, area coverage, temperature, and population density have a significant impact on disaster index. The proposed multi-layer perceptron model achieves an overall r2 score of 0.86, demonstrating its effectiveness in differentiating disaster severity. The study concludes that integrating unmanned aerial vehicle systems with statistical and deep learning techniques for disaster index is a feasible and impactful solution to mitigate human and economic losses during extreme events.

Cite: Mustafa Kamal, Mohammad Faisal Khan, Shahnawaz Khan STATISTICAL AND DEEP-LEARNING BASED DISASTER IDENTIFICATION MODELLING USING UNMANNED AERIAL VEHICLE SYSTEMS FOR EMERGENCY RESPONSE . Reliability: Theory & Applications. 2024, December 4(80): 68-82, DOI: https://doi.org/10.24412/1932-2321-2024-480-68-82

68-82

A CRITICAL REVIEW OF RAM METHODOLOGY: ANALYSIS AND PERFORMANCE EVALUATION IN INDUSTRIAL COMPLEXITIES

Pardeep Kumar, Dinesh Kumar, Rupesh Chalisgaonkar, Vipin Kumar Sharma, Santosh Kumar Rai

This paper investigates the reliability, availability and maintainability (RAM) characteristics of a in different systems of the process industries. Critical mechanical subsystems with respect to failure frequency, reliability and maintainability are identified for taking necessary measures for enhancing availability of the respective industries. As complexity of the systems increasing across the various sectors so performance evaluation becomes necessary for the smooth functioning of all the systems of respective industry. The study explores the evolution of RAM approaches over time, highlighting their significance in ensuring the efficient operation of intricate systems. It provides an overview of the historical development and current state of RAM practices in the complex system of the industries. A comprehensive review of academic literature from the past two decades, including books, journals, and scholarly articles, is conducted to expand the analysis, mainly focus on the evaluating RAM methodology in diverse industrial contexts, different complex system and other process industries.

Cite: Pardeep Kumar, Dinesh Kumar, Rupesh Chalisgaonkar, Vipin Kumar Sharma, Santosh Kumar Rai A CRITICAL REVIEW OF RAM METHODOLOGY: ANALYSIS AND PERFORMANCE EVALUATION IN INDUSTRIAL COMPLEXITIES. Reliability: Theory & Applications. 2024, December 4(80): 83-89, DOI: https://doi.org/10.24412/1932-2321-2024-480-83-89

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MANAGEMENT OF REGIONAL RESILIENCE THROUGH GOVERNANCE OF INFRASTRUCTURE OPERATIONAL RISK

Sviatoslav Timashev, Tatyana Kovalchuk

In this paper the notion of urban infrastructure resilience, expressed verbally and strictly in conditional probability terms, is formulated. It is then used to formulate several most important features of a smart city. This multidisciplinary and multifaceted approach is used to explain the concept of quantitative resilience in urban design, operation, managing urban risk and mitigating of the consequences of a natural or industrial disaster. The super urgent problem is formulated on how to connect the physical and spatial (core) resiliencies with the functional, organizational, economic and social resiliencies.  

90-104

MARSHALL-OLKIN EXPONENTIATED NADARAJAH HAGHIGHI DISTRIBUTION AND ITS APPLICATIONS

Nicy Sebastian, Jeena Joseph, Muhsina C. S., Sandra I. S.

In this paper, we introduce a new generalization of exponentiated Nadarajah Haghighi distribution, namely Marshall-Olkin exponentiated Nadarajah Haghighi (MOENH) distribution and study its properties. The stress-strength parameter estimation is also taken into account. Characterizations of the new distribution are obtained. The unknown parameters of the distribution are estimated using the maximum likelihood method. It is established how important this distribution is to the research of the minification process. Simulation studies are done, and sample path properties are explored. A real data set is fitted to the new distribution to demonstrate the model’s adaptability and effectiveness.

Cite: Nicy Sebastian, Jeena Joseph, Muhsina C. S., Sandra I. S. MARSHALL-OLKIN EXPONENTIATED NADARAJAH HAGHIGHI DISTRIBUTION AND ITS APPLICATIONS. Reliability: Theory & Applications. 2024, December 4(80): 105-119, DOI: https://doi.org/10.24412/1932-2321-2024-480-105-119

105-119

QUADRASOPHIC FUZZY MATRIX AND ITS APPLICATION

G. Aruna, J. Jesintha Rosline

Quadrasophic Fuzzy Set is one of the generalizations of Fuzzy set theory. In this artifact, a definition of the Quadrasophic Fuzzy Algebra and its characteristics are provided. The definition of a Quadrasophic Fuzzy Matrix is explored with the aid of Quadrasophic Fuzzy Algebra. The binary operators of Fuzzy Matrices are used to describe various kinds and specific operations on Quadrasophic Fuzzy Matrices. The theorems and results of Quadrasophic Fuzzy Matrix are demonstrated with pertinent examples and proofs. Additionally, the illustration of the identification of paddy illnesses is analyzed with the tool of Quadrasophic Fuzzy Matrix in the decision-making process.

120-131

BAYESIAN APPROACH FOR HEAVY-TAILED MODEL FITTING IN TWO LOMAX POPULATIONS

Vijay Kumar Lingutla, Nagamani Nadiminti

Heavy-tailed data are commonly encountered in various real-world applications, particularly in finance, insurance, and reliability engineering. This study focuses on the Lomax distribution, a powerful tool for modeling heavy-tailed phenomena. We investigate the estimation of parameters in two Lomax populations characterized by a common shape parameter and distinct scale parameters. Our analysis employs both Maximum Likelihood Estimation (MLE) and Bayesian estimation techniques, recognizing the absence of closed-form solutions for the estimators. We utilize the Newton-Raphson method for numerical evaluation of the MLE and implement Lindley’s approximation for Bayesian estimators with different priors, under symmetric loss function. Additionally, we estimate posterior densities using Gibbs sampling and bootstrapping methods to manage uncertainty. A Monte Carlo simulation study is conducted to assess the performance of the proposed estimators, providing insights into their behavior under various scenarios. This paper also discusses the application of these methodologies through a real-life example, demonstrating the practical utility of the proposed estimation techniques for analyzing heavy-tailed data.

132-150

DOUBLE SAMPLING INSPECTION PLAN UNDER ZERO-ONE FAILURE SCHEME FOR GENERALIZED INVERTED EXPONENTIAL DISTRIBUTION

S. Singh, A. Kaushik

This article presents a double acceptance sampling plan for products whose lifetimes follow a generalized inverted exponential distribution. The plan uses a zero-one failure scheme, where a lot is accepted if there are no failures observed in the first sample, and it is rejected if more than one failure occurs. In cases where there is only one failure from the first sample, a second sample is drawn and tested for the same duration as the first sample. To ensure that the true median lifetime is longer than the specified lifetime at a given consumer’s confidence level, the minimum sample sizes of the first and second samples are determined. The operating characteristics of the plan are analyzed for various ratios of the true median lifetime to the specified lifetime. Finally, an example is given to explain the results. The example shows how the double acceptance sampling plan can be used to determine the sample size and acceptance criteria for a product with a specified lifetime and a given consumer’s confidence level. The results of the example demonstrate the effectiveness of the plan in ensuring that the true median lifetime of the product is longer than the specified lifetime at the desired level of confidence.

151-161

DISCRETE-TIME QUEUEING ANALYSIS OF POWER-SAVING MECHANISMS IN LTE DRX SYSTEMS WITH DIFFERENTIATED VACATION AND DISASTER

A Mohammed Shapique, A Vaithiyanathan

This paper investigates the power-saving mechanisms of Discontinuous Reception (DRX), a technique used in wireless communication networks to reduce energy consumption. By employing a discrete-time Geo/Geo/1 queueing model with differentiated vacations and system disasters, we aim to more accurately capture the intermittent nature of data arrivals, often overlooked in continuous-time models. Our research addresses the existing gap in the literature by providing a more realistic representation of DRX behaviour. Understanding the performance and characteristics of DRX is crucial for optimizing energy efficiency and improving the overall performance of wireless networks. This paper contributes to this understanding by deriving steady-state probabilities, calculating key performance metrics, and visualizing the system behaviour through graphical analysis.

Cite: A Mohammed Shapique, A Vaithiyanathan DISCRETE-TIME QUEUEING ANALYSIS OF POWER-SAVING MECHANISMS IN LTE DRX SYSTEMS WITH DIFFERENTIATED VACATION AND DISASTER. Reliability: Theory & Applications. 2024, December 4(80): 162-175, DOI: https://doi.org/10.24412/1932-2321-2024-480-162-175

162-175

SIMULATIONS AND BAYESIAN ESTIMATION OF TRUNCATED EXPONENTIAL LOG-TOPP-LEONE GENERALIZED FAMILY WITH APPLICATION TO SURVIVAL TIME DATA

Usman Abubakar, Abdulhameed A. Osi, Ahmed Shuaibu, Liyasu A. Salisu

Due to the requirements for the flexible statistical model to fit the lifetime data, we extended the truncated exponential topp-leone family due to its bounded interval, and introduced a truncated exponential log topp-leone generalized family of distributions. we examine some properties including survival function, hazard rate function, residual lifetime, reverse residual lifetime, moment, moment generating function, Shannon entropy, quantile, and parameter estimation using maximum likelihood, maximum product spacing, and bayesian estimation. Two simulation studies were conducted to investigate the properties (i.e. mean, variance, skewness, and kurtosis), and behavior of the maximum likelihood estimate using mean, bias, and RMSE. Finally, we apply the data on the survival times of breast cancer patients and suggest that the family of the proposed distribution outperforms other standard distributions based on information criteria and goodness of fit.

Cite: Usman Abubakar, Abdulhameed A. Osi, Ahmed Shuaibu, Liyasu A. Salisu SIMULATIONS AND BAYESIAN ESTIMATION OF TRUNCATED EXPONENTIAL LOG-TOPP-LEONE GENERALIZED FAMILY WITH APPLICATION TO SURVIVAL TIME DATA. Reliability: Theory & Applications. 2024, December 4(80): 176-189, DOI: https://doi.org/10.24412/1932-2321-2024-480-176-189

176-189

SINE GENERALIZED ODD LOG-LOGISTIC FAMILY OF DISTRIBUTIONS: PROPERTIES AND APPLICATION TO REAL DATA

Abdulhameed A. Osi, Usman Abubakar, Lawan A. Isma’il

In this research, we introduce and analyze a new family of distributions called the sine generalized odd log-logistic-G family. This is driven by the reality that no single distribution can effectively model all types of data across different fields. Consequently, there is a need to develop distributions that possess desirable properties and are flexible enough to accommodate data with diverse characteristics. We explore its statistical properties, including the survival function, hazard function, moments, moment-generating function, and order statistics. A special case of the family of distributions is also presented. The maximum likelihood estimation method is used to obtain estimators of the family of distributions and the performance of the maximum likelihood estimators is evaluated in terms of bias and root mean squared errors through two simulation studies. Additionally, we demonstrate the practicality of this family using two real data sets, where it consistently provides better fits compared to other competitive distributions.

Cite: Abdulhameed A. Osi, Usman Abubakar, Lawan A. Isma’il SINE GENERALIZED ODD LOG-LOGISTIC FAMILY OF DISTRIBUTIONS: PROPERTIES AND APPLICATION TO REAL DATA. Reliability: Theory & Applications. 2024, December 4(80): 190-200, DOI: https://doi.org/10.24412/1932-2321-2024-480-190-200

190-200

DOCKER CONTAINER PLACEMENT IN DOCKER SWARM CLUSTER BY USING WEIGHTED RESOURCE OPTIMIZATION APPROACH

Jalpa M Ramavat, Dr Kajal S Patel

The use of Docker containers and their orchestration tools is rapidly improving as Web application deployment shifts from a server- or VM-based approach to a container-based approach. Docker Swarm is a flexible and simple container orchestration tool. it is widely used by application developers for the deployment of their applications in a containerized environment. Docker Swarm uses the default spread strategy for placing new containers on cluster nodes. This strategy distributes containers evenly on all nodes of the cluster, but it will not consider the current resource utilization of nodes or heterogeneous resource availability on cluster nodes. Again, all task containers are treated similarly, irrespective of their specific resource-oriented nature. This paper proposes the weighted resource optimization algorithm for calculating the weighted score of each node. Score depends on CPU and memory weight for a given task and the availability of that resource on the node. The task container is placed on the node with the highest score. This approach improves CPU and memory load balancing in a Docker cluster and also improves the completion time of the task container as compared to the spread strategy.

Cite: Jalpa M Ramavat, Dr Kajal S Patel DOCKER CONTAINER PLACEMENT IN DOCKER SWARM CLUSTER BY USING WEIGHTED RESOURCE OPTIMIZATION APPROACH. Reliability: Theory & Applications. 2024, December 4(80): 201-213, DOI: https://doi.org/10.24412/1932-2321-2024-480-201-213

201-213

A NEW ROBUST LIU REGRESSION ESTIMATOR FOR HIGH-DIMENSIONAL DATA

Muthukrishnan. R, Karthika Ramakrishnan

Aim: To provide a new Liu regression procedure for predictive modeling in cases of multicollinearity and with/without outliers. Methods: Regression analysis is employed in many statistical research domains for both estimation and prediction. Liu and Robust Estimators were developed in a classical linear regression model to address the issues of multicollinearity and outliers, respectively. In order to jointly handle the issues of multicollinearity and outliers, this research paper explores a new Robust Liu regression estimator based on the MM estimator, which is then demonstrated using real and simulated data sets. The performances of various regression estimators such as Least Square, Ridge, Liu and the Robust Liu are compared based on the Mean Square Error criterion. Findings: According to the computed error measure, the study concludes that the Robust Liu regression estimator provides more reliable results than the other mentioned regression procedures in situations where datasets have both multicollinearity and outliers.

Cite: Muthukrishnan. R, Karthika Ramakrishnan A NEW ROBUST LIU REGRESSION ESTIMATOR FOR HIGH-DIMENSIONAL DATA. Reliability: Theory & Applications. 2024, December 4(80): 214-219, DOI: https://doi.org/10.24412/1932-2321-2024-480-214-219

214-219

DETECTION AND UTILIZATION OF THERMAL RESERVES IN OPERATION OF OBSOLETE POWER UNITS OF THERMAL POWER STATIONS

Farzaliyev Y.Z., Farhadzadeh E.M.

This article deals with economic aspects, i.e. identification of reserves of thermal efficiency of obsolete equipment in the example of power units of thermal power plants, which have a useful life exceeding 50%. As a result of operation of such equipment, useful heat required for power generation is lost. The developed new approach allows to detect in time those reserves, which are not possible with the use of energy characteristics due to wear and tear of the equipment and in the end these reserves will remain latent. With the help of the new approach when comparing it with the intuitive one, by which the technical staff wastes more time, it is shown that by taking into account the actual technical condition, reliability and efficiency of equipment operation it is possible to achieve the desired result. The results showed themselves brilliantly when distributing the load between power units of a thermal power station. The exploitation data for solving the problem are technical and economic indicators that characterize the wear and tear of the equipment

Cite: Farzaliyev Y.Z., Farhadzadeh E.M. DETECTION AND UTILIZATION OF THERMAL RESERVES IN OPERATION OF OBSOLETE POWER UNITS OF THERMAL POWER STATIONS. Reliability: Theory & Applications. 2024, December 4(80): 220-227, DOI: https://doi.org/10.24412/1932-2321-2024-480-220-227

220-227

A GRAPHICAL STUDY ON THE MISSING DATA OF CENTRAL COMPOSITE DESIGN WITHIN A SPHERICAL REGION

A.R. Gokul, M. Pachamuthu

Robust missing observations have emerged as a crucial study area in statistical research. Response Surface Methodology (RSM), a recognized and extensively utilized area in experimental design, has determined that the absence of observations in an experiment can introduce complexity and interfere with the estimation of parameters. Previous literature reviews reveal that most studies on missing Central Composite Design (CCD) data were conducted using optimality and minimax loss criteria. Our study explores the spherical region of interest in the missing observation of CCD, represented through Variance Dispersion Graph (VDG) and Fraction of Design Space (FDS) graphs. Practitioners primarily focus on the region of interest rather than employing various alpha values. We investigate the predictive capabilities of each factorial, axial, and center missing design point against different radii(r) and fractions of the design space region, and we also measure relative G- and D- efficiency. We scrutinize various factors (k) from two to seven, including five center runs. Our research explores the region of interest in operating the experiment under robust conditions through visual aids of VDG and FDS graphs.

Cite: A.R. Gokul, M. Pachamuthu A GRAPHICAL STUDY ON THE MISSING DATA OF CENTRAL COMPOSITE DESIGN WITHIN A SPHERICAL REGION. Reliability: Theory & Applications. 2024, December 4(80): 228-239, DOI: https://doi.org/10.24412/1932-2321-2024-480-228-239

228-239

ANALYSIS OF A THREE-NODE SERIES QUEUE WITH ENCOURAGED ARRIVAL

Ismailkhan E, R.Jeyachandhiran, P.Thangaraja, R.Karuppaiya

This article deals with the three node series queues with encouraged arrival. We increase the expected number of subscribers by using encouraged arrival in this study. Performance metrics is developed by analytic method. After developing the governing-equations and utilizing the Burke’s theorem, we resolve the steady-state probabilities and performance metrics of the three-node series queuing system. The study of learning series queues has received substantial interest in a variety of sectors, including manufacturing lines, computer systems, tollgates, telecommunications, and others. Researchers are becoming interested in the series queuing model because of its real-world application. A series queue is a line that runs through a chain of service stations, with subscribers always going along a single track from station to station studied a finite series queue and the view of approximate decomposition.

Cite: Ismailkhan E, R. Jeyachandhiran, P. Thangaraja, R. Karuppaiya ANALYSIS OF A THREE-NODE SERIES QUEUE WITH ENCOURAGED ARRIVAL. Reliability: Theory & Applications. 2024, December 4(80): 240-249, DOI: https://doi.org/10.24412/1932-2321-2024-480-240-249

240-249

ANALYSIS OF TWO VACATION POLICIES UNDER RETRIAL ATTEMPTS, MARKOVIAN ENCOURAGED ARRIVAL QUEUING MODEL

Rajeswaran K, Rajendran P, Sanjay K, Shivali S, Ismailkhan E

In this study, Markovian queuing models, which follow encouraged arrival rates and exponential service rates, are used in a variety of systems, including manufacturing, production, telecommunications, computers, and transportation. Everyone has a hectic schedule and little free time in the modern world. Because the customer’s arrival is unpredictable, they cannot complete their task in the allotted time because they cannot predict it. The encouraged arrival, idle server state, busy server state, vacation state, and breakdown and repair state conditions for a single-server Markovian queuing system were all taken into consideration. Vacation time grows acceleratory, and vacation policies abound. This Markovian-encouraged arrival queuing model takes into account customer impatience and retrial efforts to ensure service completion. We calculate the combined probability of these states and compare first-come, first-served with bulk service. The different performance measures have also been explained.

Cite: Rajeswaran K, Rajendran P, Sanjay K, Shivali S, Ismailkhan E ANALYSIS OF TWO VACATION POLICIES UNDER RETRIAL ATTEMPTS, MARKOVIAN ENCOURAGED ARRIVAL QUEUING MODEL. Reliability: Theory & Applications. 2024, December 4(80): 250-257, DOI: https://doi.org/10.24412/1932-2321-2024-480-250-257

250-257

EVALUATION OF REPETITIVE DEFERRED SAMPLING PLAN FOR TRUNCATED LIFE TESTS BASED ON PERCENTILES USING KUMARASWAMY EXPONENTIATED RAYLEIGH DISTRIBUTION

Neena Krishna P. K. Jayalakshmi. S

This paper focuses on the designing of the Repetitive Deferred sampling plan for truncated life test for percentiles using Kumaraswamy Exponentiated Rayleigh distribution. A truncated life test may be conducted to evaluate the smallest sample size to insure certain percentile life time of products. The main objective of the proposed sampling plan is to minimize the sample size because the analogous inspection time and inspection cost will be reduced. The operating characteristic function values are calculated according to various quality levels and the minimum ratios of the true average life to the specified average life at the specified producer’s risk are derived. Certain real-life examples are provided.

Cite: Neena Krishna P. K. Jayalakshmi. S EVALUATION OF REPETITIVE DEFERRED SAMPLING PLAN FOR TRUNCATED LIFE TESTS BASED ON PERCENTILES USING KUMARASWAMY EXPONENTIATED RAYLEIGH DISTRIBUTION. Reliability: Theory & Applications. 2024, December 4(80): 258-266, DOI: https://doi.org/10.24412/1932-2321-2024-480-258-266

258-266

SOLVING GENERALIZED FUZZY LEAST COST PATH PROBLEM OF SUPPLY CHAIN NETWORK

Pratibha, Rajesh Dangwal

Optimal route selection for delivering product is the major concern for organizations related to supply chain management. The choice of route is crucial as it has a big impact on an organization’s finances. In this research, an optimum solution with inaccurate and hazy parameters to a fuzzy least cost route issue is presented. Costs can be represented by time, distance or other criteria that could represent edge weights and these are defined by the user. In this paper we are using term cost as activity time. More specifically, the cost value is taken as Generalized hexagonal fuzzy numbers. The paper discusses optimal route selection problem to reduce distance-driven costs. By using ranking method optimal cost value obtained in form of crisp numbers. Also, for the validation of our result and obtained optimal cost in form of fuzzy number, we use fuzzy dynamic programming. We obtain an improved result using our ranking algorithm. Additionally, a comparison is provided. A numerical example for comparison analysis with previous publications is provided, utilising appropriate graphical layout and tables, to elucidate both approaches.

Cite: Pratibha, Rajesh Dangwal SOLVING GENERALIZED FUZZY LEAST COST PATH PROBLEM OF SUPPLY CHAIN NETWORK. Reliability: Theory & Applications. 2024, December 4(80): 267-286, DOI: https://doi.org/10.24412/1932-2321-2024-480-267-286

267-286

REVIEW OF CENSORING SCHEMES: CONCEPTS, DIFFERENT TYPES, MODEL DESCRIPTION, APPLICATIONS AND FUTURE SCOPE

Ninan P Oomme, Jiju Gillariose

Survival analysis is one of the key techniques utilized in the domains of reliability engineering, statistics, and medical domains. It focuses on the period between the initialization of an experiment and a subsequent incident. Censoring is one of the key aspects of survival analysis, and the techniques created in this domain are designed to manage various censoring schemes with ease, ensuring accurate and insightful time-to-event data analysis. The statistical efficiency of parameter estimates is improved by accurately incorporating censoring information by making use of the available data. This paper reviews the concepts, model descriptions, and applications of conventional and hybrid censoring schemes. The introduction of new censoring schemes from conventional censoring schemes has evolved by rectifying the drawbacks of the previous schemes, which are explained in detail in this study. The evolution of hybrid censoring schemes through the combination of various conventional censoring schemes, the data structures, concepts, methodology, and existing literature works of hybrid censoring schemes are reviewed in this work.

Cite: Ninan P Oomme, Jiju Gillariose REVIEW OF CENSORING SCHEMES: CONCEPTS, DIFFERENT TYPES, MODEL DESCRIPTION, APPLICATIONS AND FUTURE SCOPE. Reliability: Theory & Applications. 2024, December 4(80): 287-300, DOI: https://doi.org/10.24412/1932-2321-2024-480-287-300

287-300

PERFORMANCE MODELING OF CRYSTALLIZATION SYSTEM IN SUGAR PLANT USING RAMD APPROACH

Ravi Choudhary, Vijay Singh Maan, Ashish Kumar, Monika Saini

The aim of the present study is to investigate reliability, availability, maintainability, and dependability (RAMD) of crystallization system of a sugar production plant. Previous studies attentive on the reliability and availability analysis of sugar plants specially its subsystems like evaporation units. This study is focus on the RAMD analysis of the crystallization system of sugar plant having four subsystems with different number of components. Failure and repair rates of all subsystems are taken as exponentially distributed. The transition diagram and Chapman- Kolmogorov differential equations for each subsystem are derived by using Markov birth-death process. For all four subsystems, reliability, availability, mean time between failure (MTBF), mean time to repair (MTTR), and dependability ratio are computed using simple probabilistic concepts. The effect of change in failure rates of subsystem in system performance is also observed. It is shown that the crystallization subsystem found to be more sensitive among four subsystems from reliability point of view. This study can be helpful to system designer for further modeling/designing of reliable systems and enhancement in system’s performance through planning efficient maintenance strategies.

Cite: Ravi Choudhary, Vijay Singh Maan, Ashish Kumar, Monika Saini PERFORMANCE MODELING OF CRYSTALLIZATION SYSTEM IN SUGAR PLANT USING RAMD APPROACH. Reliability: Theory & Applications. 2024, December 4(80): 301-312, DOI: https://doi.org/10.24412/1932-2321-2024-480-301-312

301-312

RELIABILITY ANALYSIS OF OFFSHORE PLATFORM SUPPORT STRUCTURES UNDER EXTREME WAVE LOADS: A CASE STUDY APPROACH

Seymur Bashirzade, Okan Ozcan, Rafail Garibov

Wave loads are critical factor for the design and safe operation of offshore structures. The accurate determination of these loads is essential to ensure the structural reliability and operational efficiency of such platforms at sea. This study develops analytical expressions for calculating wave loadings that affect the support of various Condeep-type offshore structures. In this regard, wave load calculations for the Draugen Monopile Condeep platform, previously constructed in Norway, were analyzed in the context of a case study. The results of this assessment provide useful information regarding the characteristics of wave loads and their relevance to the overall structural analysis.  Furthermore, the investigation also covers recommendations for design and safety improvements that consider the calculated wave loads and the assessment of the structural reliability. Study is expected to contribute to the knowledge base surrounding offshore engineering practices and improve resilience and functionality against dynamic wave forces.

Cite: Seymur Bashirzade, Okan Ozcan, Rafail Garibov RELIABILITY ANALYSIS OF OFFSHORE PLATFORM SUPPORT STRUCTURES UNDER EXTREME WAVE LOADS: A CASE STUDY APPROACH. Reliability: Theory & Applications. 2024, December 4(80): 313-324, DOI: https://doi.org/10.24412/1932-2321-2024-480-313-324

313-324

EXPERIMENTAL AND NUMERICAL INVESTIGATION OF STRESS CONCENTRATION FACTOR FOR POLYGONAL DISCONTINUITIES IN A FINITE PLATE

Rashmiben H. Patel, Dr. Bhaveshkumar P. Patel

Structural steel is widely utilized in the construction engineering sector to build a variety of buildings, including flyovers, skyscrapers, plants, heavy machinery vehicle structures, etc., in different combinations. Due to their wide range of applications, particularly in the automotive and aerospace industries, plates with different kinds of holes are also significant parameters for mechanical design. To satisfy the requirements in the final structure design, these holes are formed into plates. However, these holes concentrate stress, which gradually weakens the structure's mechanical strength. The present study aims to reduce this stress concentration of compressed plates having polygonal holes of varying shapes and sizes. The stress concentration factor around polygonal holes in polycarbonate plates, subject to uniaxial compression loads, is investigated experimentally and numerically. To obtain solutions, three approach are adopted; the finite element method, DOE RSM (Response Surface Methodology) and photoelasticity are used as the experimental method. The study's conclusions are presented here in the form of numerical and graphical data, along with a comparison between the outcomes and the photo-elasticity test results.

Cite: Rashmiben H. Patel, Dr. Bhaveshkumar P. Patel EXPERIMENTAL AND NUMERICAL INVESTIGATION OF STRESS CONCENTRATION FACTOR FOR POLYGONAL DISCONTINUITIES IN A FINITE PLATE. Reliability: Theory & Applications. 2024, December 4(80): 325-342, DOI: https://doi.org/10.24412/1932-2321-2024-480-325-342

325-342

LEHMANN TYPE-II PERK DISTRIBUTION: PROPERTIES AND APPLICATIONS

Venugopal Haridoss, Sudheep Jose, Thomas Xavier

The Lehmann type-II Perk distribution is a flexible statistical model with a wide range of appli- cations in fields such as reliability analysis, survival modeling, and data fitting. This distribution is notable for its distinct properties, including specific patterns in hazard rates and implications for stochastic ordering. Estimating the distribution parameters is essential for effective model fitting and making inferences. The parameters are estimated using the maximum likelihood estimation method, and confidence intervals are determined using normal approximation. To evaluate the performance of these estimation methods, Monte-Carlo simulation studies are conducted, demonstrating their accuracy and efficiency. The Lehmann type-II Perk distribution provides a robust framework for analyzing complex data sets and deriving reliable statistical conclusions.

Cite: Venugopal Haridoss, Sudheep Jose, Thomas Xavier LEHMANN TYPE-II PERK DISTRIBUTION: PROPERTIES AND APPLICATIONS. Reliability: Theory & Applications. 2024, December 4(80): 343-352, DOI: https://doi.org/10.24412/1932-2321-2024-480-343-352

343-352

STOCHASTIC BEHAVIOUR OF AN ELECTRONIC SYSTEM SUBJECT TO MACHINE AND OPERATOR FAILURE

S. Malik, Komal, R. K. Yadav, Anju

A stochastic model is developed by assuming the human (operator) redundancy in cold standby. For constructing this model, one unit is taken as electronic system which consists of hardware and software components and another unit is operator (human being). The system can be failed due to hardware failure, software failure and human failure. The failed hardware component goes under repair immediately and software goes for upgradation. The operator is subjected to failure during the manual operation. There are two separate service facilities in which one repairs/upgrades the hardware/software component of the electronic system and other gives the treatment to operator. The failure rates of components and operator are considered as constant. The repair rates of hardware/software components and human treatment rate follow arbitrary distributions with different pdfs. The state transition diagram and transition probabilities of the model are constructed by using the concepts of semi-Markov process (SMP) and regenerative point technique (RPT). These same concepts have been used for deriving the expressions (in steady state) for reliability measures or indices. The behavior of some important measures has been shown graphically by taking the particular values of the parameters.

Cite: S. Malik, Komal, R. K. Yadav, Anju STOCHASTIC BEHAVIOUR OF AN ELECTRONIC SYSTEM SUBJECT TO MACHINE AND OPERATOR FAILURE. Reliability: Theory & Applications. 2024, December 4(80): 353-363, DOI: https://doi.org/10.24412/1932-2321-2024-480-353-363

353-363

UNBIASED EXPONENTIAL TYPE ESTIMATORS OF POPULATION MEAN USING AUXILIARY VARIABLE AS AN ATTRIBUTE IN DOUBLE SAMPLING

Sajad Hussain

In this paper, unbiased ratio-cum-product exponential type estimators for estimating the population mean have been introduced, specifically within the framework of a double sampling plan. The large sample properties of these estimators are investigated by deriving their bias and mean square error (MSE) expressions. The findings indicate that, under optimal conditions, the proposed estimators are not only unbiased but also more efficient than traditional methods, including the sample mean and the double sampling ratio and product type estimators developed by Naik and Gupta [11] and Singh et al. [17]. To further substantiate the theoretical results, we conducted a numerical study, which demonstrates the practical effectiveness of the proposed estimators in improving estimation accuracy.

Cite: Sajad Hussain UNBIASED EXPONENTIAL TYPE ESTIMATORS OF POPULATION MEAN USING AUXILIARY VARIABLE AS AN ATTRIBUTE IN DOUBLE SAMPLING. Reliability: Theory & Applications. 2024, December 4(80): 364-373, DOI: https://doi.org/10.24412/1932-2321-2024-480-364-373

364-373

OPTIMIZING AN INVENTORY MODEL FOR PERISHABLE PRODUCTS WITH PRODUCT RELIABILITY AND TIME DEPENDENT DEMAND USING PENTAGONAL-FUZZY NUMBER

Upasana Rana, Tanuj Kumar

Enhancing inventory control for perishable goods is challenging since their shelf life is short and their demand is constantly changing. The current research examines into a more advanced inventory model for perishable goods, where demand is affected by both time and the reliability the product. The model occupies a pentagonal-fuzzy environment to assist with inherent uncertainties with these kinds of systems. This gives a more accurate picture of how demand fluctuates over time. Using analytical optimization techniques, the model targets to minimize total inventory costs, consisting of ordering cost, holding cost, and deterioration cost while maintaining high service levels. The total cost function is defuzzified using the Graded Mean Integration Representation (GMIR) method. The study’s results, which were verified by numerical evaluations, demonstrate that the model is better at cost reduction and boosting dependability than other models using the MATLAB software. This research contributes a robust framework for handling perishable inventory with uncertain situations, which has a major impact on optimizing the supply chain.

Cite: Upasana Rana, Tanuj Kumar OPTIMIZING AN INVENTORY MODEL FOR PERISHABLE PRODUCTS WITH PRODUCT RELIABILITY AND TIME DEPENDENT DEMAND USING PENTAGONAL-FUZZY NUMBER. Reliability: Theory & Applications. 2024, December 4(80): 374-384, DOI: https://doi.org/10.24412/1932-2321-2024-480-374-384

374-384

INVENTORY MODEL FOR PROBABILISTIC DETERIORATION WITH RELIABILITY-DEPENDENT DEMAND AND TIME USING CLOUDY-FUZZY ENVIRONMENT

Ashish Negi, Ompal Singh

Inventory control is vital in supply chain management, especially for perishable goods. The paper depicts a probabilistic inventory model for robust products where deterioration and demand change over time and depend on reliability. This paper also talks about the conventional back-order reliability inventory model in a fuzzy, cloudy environment. This is because products deteriorate and demand fluctuates all the time. This study shows a novel approach to modeling inventory that deals with these problems. It does this by including uniform distribution deterioration, demand that depends on both time and product reliability, and cloudy-fuzzy numbers to show uncertainty. Although we start with the crisp model and fuzzifying it to obtain a decision under the cloudy fuzzy demand rate (which is an extension of dense fuzzy) demand rate, before putting it to use in practice. For ranking the fuzzy numbers, a new defuzzification method was used. Subsequently, extensive analysis is done to compare the crisp, general fuzzy solutions to the cloudy fuzzy solutions. The numerical examples and graphical are examined to demonstrate that the novel approach is useful in the model itself. The suggested model aims to maintain high service reliability while minimizing the total cost of inventory. Numerical analyses indicate that the model is effective, exhibiting that it can lower costs and improve reliability compared to older models using MATLAB software. This study builds a strong framework for managing inventory in supply lines for perishable goods, which opens up opportunities for more progress in this area.

Cite: Ashish Negi, Ompal Singh INVENTORY MODEL FOR PROBABILISTIC DETERIORATION WITH RELIABILITY-DEPENDENT DEMAND AND TIME USING CLOUDY-FUZZY ENVIRONMENT. Reliability: Theory & Applications. 2024, December 4(80): 385-403, DOI: https://doi.org/10.24412/1932-2321-2024-480-385-403

385-403

OPTIMIZATION OF A TWO-WAREHOUSE INVENTORY MANAGEMENT FOR DETERIORATING ITEMS WITH TIME AND RELIABILITY-DEPENDENT DEMAND UNDER CARBON EMISSION CONSTRAINTS

Krishan Kumar Yadav, Ajay Singh Yadav, Shikha Bansal

The main objective of this study is to demonstrate how a company’s inventory management can be significantly impacted by its ability to provide reliable, high-quality products and to balance stock availability in order to maintain customer satisfaction. Such measures can ultimately lead to an increase in a company’s market share, efficiency, and profitability. In order to analyze the impact of reliability and time-based demand rate on inventory management system, an economic order quantity (EOQ) model with two-warehouse is established. Complete backlog allows for the consequences of constant degradation and shortages. The holding and degradation costs are considered while analyzing the effect of carbon emissions. This study’s primary goal is to optimize overall cost while maintaining item reliability and total cycle time. Analytical optimization is used to yield an algorithm for the inventory model that determines the optimal output. A numerical example-based sensitivity analysis using MATLAB Software version R2021b is also presented to illustrate the effect of carbon emission and validation of the model.

Cite: Krishan Kumar Yadav, Ajay Singh Yadav, Shikha Bansal OPTIMIZATION OF A TWO-WAREHOUSE INVENTORY MANAGEMENT FOR DETERIORATING ITEMS WITH TIME AND RELIABILITY-DEPENDENT DEMAND UNDER CARBON EMISSION CONSTRAINTS. Reliability: Theory & Applications. 2024, December 4(80): 404-418, DOI: https://doi.org/10.24412/1932-2321-2024-480-404-418

404-418

RECTIFYING INSPECTION FOR DOUBLE SAMPLING PLANS WITH FUZZY LOGIC UNDER ZERO-INFLATED POISSON DISTRIBUTION USING IN PYTHON

Kavithanjali S , Sheik Abdullah A, Kamalanathan R

Acceptance sampling is a statistical quality control technique used in manufacturing to determine whether to accept or reject a batch of products based on the number of defects obtain in a sample. Among the various sampling plans, the double sampling plan more effective because it often delivers more reliable results in selecting quality lots than other plans. In most of the real-life situation, it is not easy found the product as strictly defective or non-defective. In some situation, quality of the product can be classified several types which are expressed as good, almost good, bad, not so bad and so on. This is causes fuzzy logic comes into play. Fuzzy set theory is most powerful mathematical tool, it can deal incomplete and imprecise information. In this paper Double Sampling Plans (DSPs) are derived when non conformities are said imprecise and these imprecisions are model through ZIP distribution. It analyzes, the effectiveness of these sampling plans by comparing vital metrics such as Average Outgoing Quality (AOQ) and Average Total Inspection (ATI) using both fuzzy and crisp environments. These findings are appraised as both numerically and graphically, showing that whether the process quality is either extremely good or very bad, the AOQ curve will be lower, the plan's able to effectively control product quality.

Cite: Kavithanjali S , Sheik Abdullah A, Kamalanathan R RECTIFYING INSPECTION FOR DOUBLE SAMPLING PLANS WITH FUZZY LOGIC UNDER ZERO-INFLATED POISSON DISTRIBUTION USING IN PYTHON. Reliability: Theory & Applications. 2024, December 4(80): 419-430, DOI: https://doi.org/10.24412/1932-2321-2024-480-419-430

419-430

ACCEPTANCE SAMPLING PLAN BASED ON TRUNCATED LIFE TESTS FOR RAYLEIGH DISTRIBUTION

C.Geetha, Pachiyappan D, Srividhya K

This paper addresses the problem of designing an acceptance sampling plan for a truncated life test where the lifetime of the product follows a generalized Rayleigh distribution. The study identifies the minimum sample sizes needed to ensure the specified mean life for various acceptance numbers, confidence levels, and ratios of the fixed experiment time to the specified mean life. The operating characteristic values of the sampling plans, along with the producer's risk, are discussed. Additionally, tables are provided to facilitate the application of these sampling plans, and a numerical example is included to illustrate the use of these tables.

Cite: C. Geetha, Pachiyappan D, Srividhya K ACCEPTANCE SAMPLING PLAN BASED ON TRUNCATED LIFE TESTS FOR RAYLEIGH DISTRIBUTION . Reliability: Theory & Applications. 2024, December 4(80): 431-435, DOI: https://doi.org/10.24412/1932-2321-2024-480-431-435

431-435

USING SENSORS TO MONITOR THE CONDITION AND SAFETY OF ELECTRICAL EQUIPMENT

I.N. Rahimli, A.L. Bakhtiyarov, G.K. Abdullayeva

The article explores the important role those modern sensors play in ensuring the safety and efficient operation of electrical equipment. Advances in sensor technologies make it possible to effectively monitor the condition of equipment, identify potential problems and prevent accidents. The article examines the principles of operation of sensors, their diversity and application in various areas of the electric power industry. Particular attention is paid to predictive maintenance technologies, which allow optimizing resources and increasing the reliability of electrical equipment. Ultimately, the use of sensors to monitor the condition and safety of electrical equipment leads to reduced risk of accidents and increased efficiency of electrical power systems.

Cite: I.N. Rahimli, A.L. Bakhtiyarov, G.K. Abdullayeva  USING SENSORS TO MONITOR THE CONDITION AND SAFETY OF ELECTRICAL EQUIPMENT . Reliability: Theory & Applications. 2024, December 4(80): 436-440, DOI: https://doi.org/10.24412/1932-2321-2024-480-436-440

436-440

DIAGNOSTICS OF ELECTRICAL EQUIPMENT AT THERMAL PLANTS

R.K. Karimova, H.S. Piriyev

Diagnostics of electrical equipment at thermal power plants plays a key role in ensuring reliable operation of power systems. This article examines methods and technologies for diagnosing electrical equipment at thermal power plants and their significance for ensuring the reliability of power systems. The work analyzes the main approaches to diagnostics, including non-destructive methods, equipment condition monitoring and the use of modern technical means, such as infrared thermography and ultrasound diagnostics. Particular attention is paid to the importance of these methods for ensuring the uninterrupted operation of thermal power systems and minimizing the likelihood of emergency situations, which is important for ensuring energy security and economic efficiency.

Cite: R.K. Karimova, H.S. Piriyev DIAGNOSTICS OF ELECTRICAL EQUIPMENT AT THERMAL PLANTS. Reliability: Theory & Applications. 2024, December 4(80): 441-447, DOI: https://doi.org/10.24412/1932-2321-2024-480-441-447

441-447

ENHANCING REDUNDANT SYSTEM PERFORMANCE: A STOCHASTIC MODEL FOR OPTIMIZED INSPECTION STRATEGIES POST-FAILURE

Purnima Sonker, R.K. Bhardwaj

This paper delves into the strategic utilization of inspections to determine the appropriate action for components within redundant systems following unit and switch failures. Post-failure, the timely execution of repair and replacement procedures is paramount for restoring system functionality. By assigning inspection tasks to servers, this paper aims to evaluate the condition of system components and make informed decisions regarding repair or replacement. It addresses the standardization of inspection processes and subsequent repair/replacement protocols for industrial systems encountering failures. Introducing a model, the study endeavors to bolster system reliability and availability by addressing failures caused by faults through inspection and subsequent repair/replacement actions. Employing a quantitative approach, it provides insights into maintaining system reliability and availability via a stochastic framework. By integrating unit and switch inspections into the analysis, the paper proposes a strategic approach to optimizing redundant system operations, facilitating effective decision-making concerning repair and replacement strategies post- failure.

Cite: Purnima Sonker, R.K. Bhardwaj ENHANCING REDUNDANT SYSTEM PERFORMANCE: A STOCHASTIC MODEL FOR OPTIMIZED INSPECTION STRATEGIES POST-FAILURE. Reliability: Theory & Applications. 2024, December 4(80): 448-460, DOI: https://doi.org/10.24412/1932-2321-2024-480-448-460

448-460

PROFIT ANALYSIS OF REPAIRABLE WARM STANDBY SYSTEM UNDER IMPERFECT SWITCH

Nishant Yadav, Shiv Kant, Shashi Kant, Arunita Chaukiyal, Bindu Jamwal

In this paper, the performance of two non-identical units repairable system are analyzed by using regenerative point graphical technique. Generally, the system has one operative unit and one warm standby unit. Fuzzy concept is used to find the reliability measures under imperfect switch. Regenerative point graphical technique and semi Markov process are used to evaluate the reliability measures. Primary, secondary and tertiary circuits are used to describe the base state. The system is repaired by the available technician when any unit is failed or switch is under imperfect mode. The priority in repair is given to switch before working units. In this paper, the failure time and repair time follow general distributions. The tables are used to explore the reliability measures such that mean time to system failure, availability and profit values.

Cite: Nishant Yadav, Shiv Kant, Shashi Kant, Arunita Chaukiyal, Bindu Jamwal PROFIT ANALYSIS OF REPAIRABLE WARM STANDBY SYSTEM UNDER IMPERFECT SWITCH. Reliability: Theory & Applications. 2024, December 4(80): 461-467, DOI: https://doi.org/10.24412/1932-2321-2024-480-461-467

461-467

BAYESIAN INFERENCE OF WEIBULL-PARETO DISTRIBUTION UNDER DOUBLE TYPE I HYBRID CENSORED DATA

Khawla Boudjerda

This paper investigates the estimation of parameters, reliability, and failure rate functions of the Weibull- Pareto distribution using double type I hybrid censored data. We begin by applying the maximum likelihood method to derive point estimates for the distribution parameters. Subsequently, we explore Bayesian estimation techniques, obtaining Bayesian estimators under various loss functions to enhance robustness. To compute these estimators, we utilize Markov Chain Monte Carlo (MCMC) methods, facilitating effective sampling from complex posterior distributions. We employ Pitman closeness criteria to compare the performance of Bayesian estimators against those derived from maximum likelihood estimation, providing a comprehensive evaluation of their accuracy and efficiency. Additionally, a real data example is presented to illustrate the practical application of our methodologies. The results underscore the advantages of the Bayesian approach, particularly in scenarios characterized by hybrid censoring, while also contributing to the broader understanding of reliability analysis in statistical modeling.

Cite: Khawla Boudjerda BAYESIAN INFERENCE OF WEIBULL-PARETO DISTRIBUTION UNDER DOUBLE TYPE I HYBRID CENSORED DATA. Reliability: Theory & Applications. 2024, December 4(80): 468-480, DOI: https://doi.org/10.24412/1932-2321-2024-480-468-480

468-480

ESTIMATION OF RELIABILITY ON SEQUENTIAL ORDER STATISTICS FROM (k, n) SYSTEM

K. Glory Prasanth, A. Venmani

The focus of this paper is to introduce a reliability model for differently structured independent sequential (k, n) systems. In such a system, the failure of any component possibly influences the other components such that their underlying failure rate is parametrically adjusted with respect to the number of preceding failures. The system works if and only if at least k out of the n components works. By considering the different models of sequential (k, n) system, we obtain the reliability assuming that the system failure time belongs to exponential/gamma distribution with location and scale parameters. These results are important because the distributions can model diverse time-to- failure behavior. As the result it is found that the reliability decreases with increase in time by shifting location and scale parameters. This indicates that the reliability for different models of sequential (k, n) system are as expected.

Cite: K. Glory Prasanth, A. Venmani ESTIMATION OF RELIABILITY ON SEQUENTIAL ORDER STATISTICS FROM (k, n) SYSTEM. Reliability: Theory & Applications. 2024, December 4(80): 481-495, DOI: https://doi.org/10.24412/1932-2321-2024-480-481-495

481-495

PREVENTIVE MAINTENANCE POLICIES WITH RELIABILITY THRESHOLDS FOR TABLE SAW MACHINE

Udoh Nse, Etim Andrew, Uko Iniobong

Preventive maintenance policies are essential practical guide for effective maintenance of industrial machines. In this study, system reliability is estimated and used as the condition variable on reliability-based preventive maintenance models to formulate preventive maintenance policies for Table Saw machine which has an increasing hazard rate. Inventory holding cost is introduced as part of the repair cost to complement the actual cost of maintenance. The inter-failure times of the machine was modeled as Weibull distribution and the shape parameters estimate were obtained. Three preventive maintenance policies were obtained for the machine from respective preventive maintenance models with predetermined fixed level of reliability, variable reliability and a combination of both. Result from the third policy with critical reliability level which combines both fixed and unfixed reliability levels is noted as the optimal preventive maintenance policy for the machine in terms of extended lifespan and minimum maintenance cost.

Cite: Udoh Nse, Etim Andrew, Uko Iniobong PREVENTIVE MAINTENANCE POLICIES WITH RELIABILITY THRESHOLDS FOR TABLE SAW MACHINE. Reliability: Theory & Applications. 2024, December 4(80): 496-509, DOI: https://doi.org/10.24412/1932-2321-2024-480-496-509

496-509

OPTIMIZATION OF THE TWO UNIT SYSTEMS WITH DEGRADATION AND PREVENTIVE MAINTENANCE IN ONE UNIT USING DEEP LEARNING ALGORITHMS

Shakuntla Singla, Komalpreet Kaur

This study presents a comprehensive behavioral examination of a two-unit organization integrating preventive maintenance strategies and the introduction of degradation in single unit following complete failure. The research explores the intricate dynamics influencing the system's reliability, availability, and performance. The impact of preventive maintenance on reducing unexpected failures and enhancing overall system robustness is investigated, alongside the added complexity introduced by degradation modeling using three methods ADAM, SGD and RMS Prop. The interplay between preventive maintenance and degradation is analyzed, emphasizing the critical role of optimization in achieving effective system performance. Trade-off analysis reveals the delicate balance between maintenance costs and savings from avoiding failures, guiding decision-makers in determining the most cost-effective strategies. Sensitivity analysis identifies key parameters influencing system behavior, aiding in informed decision-making and robust system design. Consideration of life-cycle costs provides a holistic economic perspective, evaluating both short-term and long-term implications of maintenance and operational choices. This model is train in three methods (ADAM, SGD, and RMS Prop), In MTSFof Adam is better than other two methods. In Expected Number of Inspections by repair man of SGD is better than other two methods. In Recall (Busy Period) of Adam is better than other two methods. In Precision (Availability of the System) of RMS Prop is better than other two method.

Cite: Shakuntla Singla, Komalpreet Kaur OPTIMIZATION OF THE TWO UNIT SYSTEMS WITH DEGRADATION AND PREVENTIVE MAINTENANCE IN ONE UNIT USING DEEP LEARNING ALGORITHMS. Reliability: Theory & Applications. 2024, December 4(80): 510-524, DOI: https://doi.org/10.24412/1932-2321-2024-480-510-524

510-524

A NOVEL APPROACH TO DISTRIBUTION GENERATION WITH APPLICATIONS IN ELECTRICAL ENGINEERING

Nuzhat Ahad, S.P. Ahmad, J.A. Reshi

Many fields use standard distributions to model lifetime data. However, datasets from areas such as engineering and medical sciences frequently deviate from these standard distributions. This highlights the necessity for developing new distribution models that can accommodate significant variations in data patterns to better align with real-world observations. In this manuscript, we introduce a novel technique called the PNJ Transformation technique (named using the initials of its authors) for generating probability distributions. Using this technique, we developed a new and improved version of the Power function (PF) distribution, named the PNJ Power function (PNJ-PF) distribution. The PNJ-PF distribution offers superior flexibility compared to PF Distribution in terms of probability density function (pdf) and hazard rate function. We investigated the statistical properties of the PNJ-PF distribution and describe the maximum likelihood estimation (MLE) procedure for its parameters. To demonstrate the effectiveness and adaptability of the PNJ-PF distribution, we apply it to a simulated and two real-life datasets and compared proposed model fit with the traditional Power function model and other competitive models based on the various goodness-of-fit measures, such as the Akaike Information Criterion (AIC), Bayesian Information Criterion(BIC), Corrected AIC, Hannan−Quinn Information Criterion (HQIC) and these results are also justified graphically, further demonstrating the superiority and flexibility of the PNJ-PF distribution.

Cite: Nuzhat Ahad, S.P. Ahmad, J.A. Reshi A NOVEL APPROACH TO DISTRIBUTION GENERATION WITH APPLICATIONS IN ELECTRICAL ENGINEERING. Reliability: Theory & Applications. 2024, December 4(80): 525-540, DOI: https://doi.org/10.24412/1932-2321-2024-480-525-540

525-540

NEW GENERALIZATION OF INVERTED EXPONENTIAL DISTRIBUTION: PROPERTIES AND ITS APPLICATIONS

Tabasum Ahad, S.P. Ahmad

In this paper, we introduce a new extension of the inverted exponential distribution called as "SMP Inverted Exponential" (SMPIE) distribution through the SMP technique. Various statistical properties of this new distribution have been illustrated, including survival function, hazard function, quantile function, moments, moment generating function, entropy, and order statistics. Method of maximum likelihood estimation is used to evaluate the parameters of the proposed distribution. A simulation study is carried out for illustration of the performance of estimates. Two real-life data sets are incorporated to illustrate the utility and flexibility of the proposed distribution as compared to other existing probability distributions.

Cite: Tabasum Ahad, S.P. Ahmad NEW GENERALIZATION OF INVERTED EXPONENTIAL DISTRIBUTION: PROPERTIES AND ITS APPLICATIONS. Reliability: Theory & Applications. 2024, December 4(80): 541-551, DOI: https://doi.org/10.24412/1932-2321-2024-480-541-551

541-551

AN ANALYSIS OF RELIABILITY IN MANUFACTURING INDUSTRIES

Shakuntla Singla, Sonia, Shilpa Rani

This paper offers an initial evaluation of the organizational and structural relationships among reliability and best warranty programme. In the producing sectors because of automation, plant potential has been extended with inside the system industries. This enables in growing productiveness in addition to the best of the material, but every computerized industry, massive funding remains the top anxiety. Consequently, it additionally anticipated the running structures ought to work for a long time and defective-free. In the time being, it turns into essential to present right care of running machines. Operation of those features and using precise strategies in those regions and the obstacles to their reputation has additionally been discussed. The contemporary paper offers the evaluation of the consistency evaluation. Consistency evaluation of numerous structures is evaluated in specific system productions just like the sugar production, updraft energy productions, milk productions, mining, petroleum productions, etc. The series of reliability and best expenses records and its use with the aid of using pinnacle control in decision-making regarding destiny upgrades have additionally been covered. The specific tactics are used by investigators in numerous grounds to test the overall activity of the running machine. These tactics are genomic procedure, fault tree evaluation, deficiency and impact evaluation, petrify-nets, dependability, accessibility, maintainability and deprivation modeling strategies etc. The growth has been shown from the overall performance of the structures mainly totally depend upon numerous records through the above tactics.

Cite: Shakuntla Singla, Sonia, Shilpa Rani AN ANALYSIS OF RELIABILITY IN MANUFACTURING INDUSTRIES. Reliability: Theory & Applications. 2024, December 4(80): 552-559, DOI: https://doi.org/10.24412/1932-2321-2024-480-552-559

552-559

MODELING OF ARC OVERVOLTAGE DEPENDENCE ON GROUND CIRCUIT RESISTANCE AND PHASE CAPACITANCE

Orujov Najaf İsmail, Guliyev Huseyngulu Bayram, Alimammadova Sara Javanshir

The need to control the arc overvoltage during the insulation under load test in neutral insulated networks requires the determination of dependencies between single-phase non-stationary ground and parameters characterizing the faults. In most cases, the identification and realization of such dependencies is observed with a number of difficulties. Therefore, for practical conditions, simple mathematical models should be developed that allow knowing the dependencies between these parameters. In this work, the problem of determining the relationship between the overvoltage generated in the neutral isolated network as a result of artificial non-stationary earth faults, the earth fault resistance and the phase capacitance of the network with respect to the earth was considered. For this purpose, using the least squares method, a regression equation was obtained for the dependence of the frequency of overvoltage on the ground fault resistance and the phase capacitance of the network with respect to the ground, and a corresponding 3D image was constructed.

Cite: Orujov Najaf İsmail, Guliyev Huseyngulu Bayram, Alimammadova Sara Javanshir MODELING OF ARC OVERVOLTAGE DEPENDENCE ON GROUND CIRCUIT RESISTANCE AND PHASE CAPACITANCE . Reliability: Theory & Applications. 2024, December 4(80): 560-569, DOI: https://doi.org/10.24412/1932-2321-2024-480-560-569

560-569

METHODOLOGY OF ASSESSING SOCIAL DAMAGE FROM LONG-TERM SMOKE DURING FIRES IN MOUNTAIN FOREST BELTS OF RUSSIA

D.S. Kovaleva, A.A. Dolgov

The article describes a methodology for assessing social damage during fires in mountain forest belts of the Russian Federation, associated with an increase in the overall mortality of the population as a result of long-term and intense smoke in urbanized areas. The relevance of the topic and the demand for the results are associated with the growing number of forest fires, including in mountainous areas, with changing consequences, both for the ecology of regions and human economic activity, and for the life and health of the population, changing consistent long-term smoke pollution of urbanized areas. Recently, many countries have been paying more and more attention to the pollution of the atmosphere of populated areas, namely, air quality is a determining factor for the health and life expectancy of the population. The methodology presented in the article allows us to estimate the concentration of fine particles in space at a given distance from a forest fire and to estimate the possible social damage associated with the formation of general mortality as a result of smoke pollution. An example of testing this methodology is given using the example of long-term smoke in Moscow in 2010.

Cite: D.S. Kovaleva, A.A. Dolgov METHODOLOGY OF ASSESSING SOCIAL DAMAGE FROM LONG-TERM SMOKE DURING FIRES IN MOUNTAIN FOREST BELTS OF RUSSIA. Reliability: Theory & Applications. 2024, December 4(80): 570-580, DOI: https://doi.org/10.24412/1932-2321-2024-480-570-580

570-580

ANALYSIS OF THE EFFECT OF TEMPERATURE ON SOLAR PANELS AND THEIR COOLING METHODS

I.M. Marufov, S.Y. Shikhaliyeva

One of the most widely used renewable energy sources is solar energy, and it is predicted to continue to be so in the future. Recently, a great increase has been observed both in the study of the working principle of photovoltaic (electricity generated by the effect of light) devices and in increasing their efficiency. Solar cells change as a result of temperature fluctuations. The purpose of the article is the effect of temperature on the efficiency of solar panels and their cooling methods. The novelty. Solar cells change as a result of temperature fluctuations. Methods. Taking into account that the cooling system is implemented by spraying water, we can determine when the cooling starts at the moment when the temperature reaches the maximum by building a mathematical model. Results. In this article, the relationships between solar radiation, efficiency and temperature are determined under different conditions. Practical value. Based on the heating and cooling models, it was determined that starting the cooling process when the temperature of the panels reaches 45 0C is the most convenient method.

Cite: I.M. Marufov, S.Y. Shikhaliyeva ANALYSIS OF THE EFFECT OF TEMPERATURE ON SOLAR PANELS AND THEIR COOLING METHODS. Reliability: Theory & Applications. 2024, December 4(80): 581-585, DOI: https://doi.org/10.24412/1932-2321-2024-480-581-585

581-585

MARKOV CHAIN MODEL FOR COMPARISON OF PRICE MOVEMENT OF FRUITS IN SALEM DISTRICT, TAMILNADU

Kamalanathan R, Sheik Abdullah A, Kavithanjali S

Statistical forecasting requires mathematical models and techniques to predict future outcomes based on historical data. Markov chains are statistical models that can be utilized to analyze the movement of prices in agriculture price, financial market price, business process, fuel prices and etc., They are particularly relevant in the context of price movements because they provide a framework for understanding and predicting the future state of a system based on its current state. In a Markov chain process, there are a set of states and we progress from one state to another based on a fixed probability. In these decades many articles are showed that modeling a market as a random walk was applicable and that a market may be viewed as having the Markov property. The objective of this paper is to construct the Markov chain model for daily fruit price movement in Salem District, Tamil Nadu. Two models are highlighted, where the price movement is considered as being in a state of gain, loss and no change and large gain, or small gain or loss, or large loss and no change. Ten different types of fruits are considered which are cultivated Salem areas and above two models are used to analyze the price movement of each fruit. These models were used to obtain transitional probabilities, steady state probabilities and mean recurrence times. Our results indicate that the pattern of price movement of Banana is similar to price movements of other fruits, in both models. The investor is encouraged to invest in the fruit market at any time in away which leads to a greater chance of getting more gain than loss.

Cite: Kamalanathan R, Sheik Abdullah A, Kavithanjali S MARKOV CHAIN MODEL FOR COMPARISON OF PRICE MOVEMENT OF FRUITS IN SALEM DISTRICT, TAMILNADU. Reliability: Theory & Applications. 2024, December 4(80): 586-598, DOI: https://doi.org/10.24412/1932-2321-2024-480-586-598

586-598

OPTIMIZING HIDDEN MARKOV MODELS WITH FUZZIFICATION TECHNIQUES

Vyshnavi. M, Muthukumar. M

This work explores using fuzzified techniques to enhance the performance of Hidden Markov Models (HMMs) in handling uncertainties and imprecise inputs. We construct and evaluate three types of fuzzy HMMs: the Trapezoidal fuzzy HMM, the Sigmoidal fuzzy HMM, and the Gaussian fuzzy HMM. As part of our process, parameter estimations are calculated and models are chosen based on AIC, BIC, AICc, and HQIC criteria. Each state's mean, variance, and stationary distribution are calculated and examined to evaluate the predictability and stability of the models. We use the Viterbi technique to identify the most likely state sequences for the next five years. According to the results, the Gaussian Fuzzy HMM offers superior predicted accuracy and durability when compared to the other models. This paper emphasizes the advantages of using fuzzy membership functions in HMMs and provides the foundation for future research in different areas, such as agricultural data prediction.

Cite: Vyshnavi. M, Muthukumar. M OPTIMIZING HIDDEN MARKOV MODELS WITH FUZZIFICATION TECHNIQUES. Reliability: Theory & Applications. 2024, December 4(80): 599-610, DOI: https://doi.org/10.24412/1932-2321-2024-480-599-610

599-610

A SHORTAGES MULTI WAREHOUSE HAVING IMPERFACT ITEMS AND DIFFERENT DISCOUNT POLICY

Krishan Pal, Ajay Singh Yadav, Seema Agarwal

A multi-warehouse shortage model has been developed where demand is assumed to be deterministic. In reality, machines run for long periods during production and random failures may occur as the system transitions from a controlled to an uncontrolled state. During this time the production system produces defective products. Demand is assumed to be deterministic. Retailers offer a quantity discount per unit on the selling price of an item and in return receive a quantity- based discount on the purchase price of the item. A retailer has limited storage capacity and therefore requires additional space with unlimited storage capacity. This additional space is called a rented warehouse and its storage cost is higher than accompany- owned warehouse. The objective of this model is to study a multiple inventory model of defective items under quantity- based discounts, where defective items can be sorted and sold in a single batch with decision variables set to the optimal order quantity and optimal inventory and shipment quantity to increase overall profits to maximize the value for the retailer. A solution procedure for determining the optimal solution is presented and a numerical example is given to illustrate this study. A sensitivity analysis is also performed to examine the effect of changing parameter values on the optimal solution.

Cite: Krishan Pal, Ajay Singh Yadav, Seema Agarwal A SHORTAGES MULTI WAREHOUSE HAVING IMPERFACT ITEMS AND DIFFERENT DISCOUNT POLICY. Reliability: Theory & Applications. 2024, December 4(80): 611-621, DOI: https://doi.org/10.24412/1932-2321-2024-480-611-621

611-621

SELECTION OF BEST ENERGY STORAGE TECHNOLOGY USING ELECTRE III-BWM METHOD UNDER LINGUISTICS NEUTROSOPHIC FUZZY APPROACH

Sasirekha D, Senthilkumar P

Renewable energy provides more environmentally friendly sources of energy, which reduces the demand for fossil fuels and is therefore necessary to reach zero emissions of carbon. But the need for systems that are capable of capturing and storing this energy is expanding as the world gets a growing amount of electricity from these forms of renewable energy. In present-day society, renewable energy storage is widely used, and governments are concentrating on developing suitable storage technologies together with a plan for upcoming energy storage reduction. Energy storage technologies have been proposed as potential solutions for this issue due to their ability to store energy and lower energy consumption. Aspects of technology, economy, society, and environment are the four main criteria used in this study to examine different energy storage techniques. The most effective strategy was identified in this paper. In this study, we use the ELECTRE-III approach to suggest the optimal storage technology under the linguistic neutrosophic fuzzy set. Finally, a numerical example of this area of study is provided. A comparison and sensitivity analysis are shown for the effectiveness of the proposed method.

Cite: Sasirekha D, Senthilkumar P SELECTION OF BEST ENERGY STORAGE TECHNOLOGY USING ELECTRE III-BWM METHOD UNDER LINGUISTICS NEUTROSOPHIC FUZZY APPROACH. Reliability: Theory & Applications. 2024, December 4(80): 622-634, DOI: https://doi.org/10.24412/1932-2321-2024-480-622-634

622-634

OPTIMALITY PREDICTION OF SECOND ORDER BOX-BEHNKEN DESIGN ROBUST TO MISSING OBSERVATION

A.R. Gokul, M. Pachamuthu

The study of robust missing observations has gained prominence in statistical research. In particular, the Response Surface Methodology (RSM), a widely applied approach in experimental design, faces challenges when dealing with missing data. This paper investigates two design variants: the three- level second-order Box-Behnken design (BBD) with one missing observation and the Small Box- Behnken Design (SBBD), which involves fewer experimental runs than the standard BBD. We evaluate prediction performance using a fraction of design space (FDS) plot, revealing the distribution of scaled prediction variance (SPV) values across the design space. Additionally, we assess the efficiency of design model parameters using information-based criteria (A, D, and G relative efficiency). Our analysis spans k factors, ranging from k = 3 to 9. The findings guide practitioners in selecting optimal design points for efficient parameter estimation and accurate prediction within the context of missing observations. This comparative study sheds light on the trade-offs between BBD and SBBD, providing valuable insights for experimental design practitioners.

Cite: A.R. Gokul, M. Pachamuthu OPTIMALITY PREDICTION OF SECOND ORDER BOX-BEHNKEN DESIGN ROBUST TO MISSING OBSERVATION. Reliability: Theory & Applications. 2024, December 4(80): 635-647, DOI: https://doi.org/10.24412/1932-2321-2024-480-635-647

635-647

METHODOLOGY FOR ASSESSING THE RELIABILITY OF AGS BASED ON RENEWABLE ENERGY SOURCES

N.S. Mammadov, K.M. Mukhtarova

With the introduction of renewable energy sources, in particular wind power and photovoltaic installations, in the autonomous generation systems, the problem of reliability of the equipment used and the entire energy complex becomes one of the main ones. It is necessary to develop and improve methods for analyzing and calculating reliability, which will make it possible at the design stage to take into account the probabilistic characteristics of renewable energy resources, reliability indicators and operating experience of the equipment used. The article discusses the scheme of an autonomous energy complex based on renewable energy sources. A graph of the dependence of failure rate on recovery time is presented. This paper discusses various methods for assessing the reliability of autonomous generation systems based on renewable energy sources: analytical methods, state space method (Markov process theory), Monte Carlo method, fault tree method and state enumeration method. The advantages and disadvantages of these methods are considered.

Cite: N.S. Mammadov, K.M. Mukhtarova METHODOLOGY FOR ASSESSING THE RELIABILITY OF AGS BASED ON RENEWABLE ENERGY SOURCES. Reliability: Theory & Applications. 2024, December 4(80): 648-653, DOI: https://doi.org/10.24412/1932-2321-2024-480-648-653

648-653

A NEW EXTENSION OF KUMARASWAMY DISTRIBUTION FOR IMPROVED DATA MODELING: PROPERTIES AND APPLICATIONS

Mahvish Jan, S.P. Ahmad

In this manuscript, we have introduced a new model of the Kumaraswamy distribution known as SMP Kumaraswamy (SMPK) distribution using SMP technique. The SMPK distribution has the desirable feature of allowing greater flexibility than some of its well-known extensions. A comprehensive account of statistical properties along with the estimation of parameters using classical estimation method is presented. Furthermore, a simulation study is carried out to assess the behavior of estimators based on their biases and mean square errors. Finally, we consider two real-life data sets; we observe that the proposed model outperforms other competing models using goodness of fit measures.

Cite: Mahvish Jan, S.P. Ahmad A NEW EXTENSION OF KUMARASWAMY DISTRIBUTION FOR IMPROVED DATA MODELING: PROPERTIES AND APPLICATIONS. Reliability: Theory & Applications. 2024, December 4(80): 654-665, DOI: https://doi.org/10.24412/1932-2321-2024-480-654-665

654-665

STOCHASTIC OPTIMIZATION OF PERISHABLE INVENTORY INCORPORATING PRESERVATION, FRESHNESS INDEX, EXPIRY DATE AND OPTIMISING PROMOTIONAL STRATEGIES FOR EFFECTIVE MANAGEMENT

Kajal Sharma, Lalji Kumar, Uttam Kumar Khedlekar

Inventory management is a critical aspect of supply chain efficiency and can be influenced by various factors such as advertising, pricing, and preservation policies. Recent research has proposed a model that considers critical variables such as fluctuations in pricing, advertising tactics, and preservation expenses within uncertain scenarios to improve inventory management. The study provides valuable insights into advertising dynamics, optimal pricing strategies, and the impact of preservation costs on decision-making. Decision-makers can apply these insights to enhance the efficiency of their supply chains in a competitive environment. The study emphasizes the importance of flexibility while aligning inventory practices with corporate sustainability goals. Although the model’s applicability may be context-specific, the findings contribute to discussions on inventory management strategies while acknowledging certain assumptions made during the study. Proper advertising, pricing, and preservation policies can increase awareness, attract customers, and maintain quality, influencing product demand. This research proposes a model to improve inventory management, considering variables such as pricing fluctuations, advertising tactics, and preservation expenses in uncertain scenarios. The study provides insights into advertising dynamics, optimal pricing strategies, and how preservation costs influence decision-making. Decision-makers can apply these insights to improve supply chain efficiency. The study stresses the importance of flexibility in a competitive environment and aligning inventory practices with corporate sustainability goals. The findings contribute to discussions on inventory management strategies, but the model’s applicability may be context-specific, and the study makes certain assumptions.

Cite: Kajal Sharma, Lalji Kumar, Uttam Kumar Khedlekar STOCHASTIC OPTIMIZATION OF PERISHABLE INVENTORY INCORPORATING PRESERVATION, FRESHNESS INDEX, EXPIRY DATE AND OPTIMISING PROMOTIONAL STRATEGIES FOR EFFECTIVE MANAGEMENT. Reliability: Theory & Applications. 2024, December 4(80): 666-685, DOI: https://doi.org/10.24412/1932-2321-2024-480-666-685

666-685

A NEW GENERALIZATION OF AREA BIASED DISTRIBUTION WITH PROPERTIES AND ITS APPLICATION TO REAL LIFE DATA

P. Pandiyan, R. Jothika

This paper proposed a new generalization of the Samade distribution. The term "area biased Samade distribution" refers to the recently created distribution model. After studying the various structural features, entropies, order statistics, moments, generating functions for moments, survival functions, and hazard functions were calculated. The parameters of the suggested model are estimated using the maximum likelihood estimation technique. Ultimately, a fitting of an application to a real-life blood cancer data set reveals a good fit.

Cite: P. Pandiyan, R. Jothika A NEW GENERALIZATION OF AREA BIASED DISTRIBUTION WITH PROPERTIES AND ITS APPLICATION TO REAL LIFE DATA. Reliability: Theory & Applications. 2024, December 4(80): 686-699, DOI: https://doi.org/10.24412/1932-2321-2024-480-686-699

686-699

ANALYSIS OF AN ENCOURAGED ARRIVAL QUEUING MODEL WITH SERVERS REPEATED VACATIONS AND BREAKDOWNS

Jenifer Princy P, K Julia Rose Mary

The behavior of customers plays a vital role in realizing the nature of a queue. If there is a favor for customers from the side of service facility the arrival rate increases than usual. Also the positive perspective about the service providers also encourages more number of customers to join the system. The arrival rate of the customers follow Poisson distribution. This paper analyses a queuing model with those encouraged customers who urges to join the system. Here the customers are served in batches according to the general bulk service rule along with the phenomenon that the servers undergo repeated vacations until they find minimum number of customers to start the service. In addition this paper interprets the scenario that if there is a breakdown in the service facility, the waiting line of the customers increases which causes a greater impact on the effectiveness of the service providers favoring the customers. On account of this situation the steady state probability solutions and some performance measures are evaluated along with a numerical illustration.

Cite: Jenifer Princy P, K Julia Rose Mary ANALYSIS OF AN ENCOURAGED ARRIVAL QUEUING MODEL WITH SERVERS REPEATED VACATIONS AND BREAKDOWNS. Reliability: Theory & Applications. 2024, December 4(80): 700-709, DOI: https://doi.org/10.24412/1932-2321-2024-480-700-709

700-709

IMPROVING THE RELIABILITY OF RECOGNIZING POTENTIALLY HAZARD UNDERWATER OBJECTS

Artyukhin Valerii, Vyalyshev Alexander, Zinoviev Sergey, Tuzov Fedor

The process of recognizing an underwater object and detecting potentially hazardous underwater object is very important in underwater operations. To facilitate the work of the side scan sonar operator, this paper proposes to increase the reliability of recognizing hydroacoustic images of potentially hazardous underwater objects in automatic mode. Based on the analysis of sonar images received from the side scan sonar, an image of an object is formed, which is then recognized (classified) as belonging to a certain class of objects. Five classes of recognized objects are defined. A convolutional neural network used to determine whether an underwater potentially dangerous object belongs to one of the classes is described. Filters for initial sonar images for acceleration of neural network operation are defined. Algorithms and software for forming an image of the object and making a decision on its belonging to one or another class are developed. It is shown that the use of convolutional neural network allows to determine the correct class of the object with an accuracy of 91%

Cite: Artyukhin Valerii, Vyalyshev Alexander, Zinoviev Sergey, Tuzov Fedor IMPROVING THE RELIABILITY OF RECOGNIZING POTENTIALLY HAZARD UNDERWATER OBJECTS. Reliability: Theory & Applications. 2024, December 4(80): 710-718, DOI: https://doi.org/10.24412/1932-2321-2024-480-710-718

710-718

THE INVERSE LOMAX ODD-EXPONENTIATED EXPONENTIAL DISTRIBUTION WITH INDUSTRIAL APPLICATIONS

Jamilu Yunusa Falgore, Yahaya Abubakar, Sani Ibrahim Doguwa, Aminu Suleiman Mohammed, Abdussamad Tanko Imam

Based on the limitations of the Inverse Lomax distribution and exponential distribution as outlined in the literature, a new extension of the exponential distribution is introduced in this paper. Some statistical properties of the ILOEED such as mean, variance, skewness, quantile function, moment, moment generating function, as well as kurtosis were demonstrated. The shapes of the hazard function of the proposed distribution suggest that it can be used to fit a dataset with increasing and bath-tube shapes. A simulation study for three different cases was also presented. The result of the simulation for three different cases (I, II, and III) indicated that ILOEED’s estimates are consistent. Lastly, an application to Industry datasets was demonstrated based on the ILOEED. Having minimum values of the Goodness-of-fit criteria and Goodness-of-fit statistics, the ILOEED can be recommended to fit these three datasets, in preference to other distributions considered in this paper.

Cite: Jamilu Yunusa Falgore, Yahaya Abubakar, Sani Ibrahim Doguwa, Aminu Suleiman Mohammed, Abdussamad Tanko Imam THE INVERSE LOMAX ODD-EXPONENTIATED EXPONENTIAL DISTRIBUTION WITH INDUSTRIAL APPLICATIONS. Reliability: Theory & Applications. 2024, December 4(80): 719-736, DOI: https://doi.org/10.24412/1932-2321-2024-480-719-736

719-736

REGRESSION-TYPE IMPUTATION SCHEME UNDER SUBSAMPLING WITH EQUAL CHANCE OF RANDOM NON-RESPONSE AT FIRST STAGE

Abubakar Ibrahim, Yahaya Abubakar, Garba Jamilu, Aliyu Yakubu

The study addresses the challenges of estimating the population mean in two-stage cluster sampling, where there is an equal chance of random non-response at the first-stage unit. The researchers propose some regression-type imputation schemes and regression-type estimators that incorporate measurement error parameters for both the study and supplementary variables. The properties of the proposed estimators were derived and numerically compared using a simulated sample population. The proposed estimators outperformed the existing estimators consider in the study. The researchers conclude that their proposed methodology can be practically applied, using the actual responses of the respondents and including the measurement error parameters to estimate the finite population mean.

Cite: Abubakar Ibrahim, Yahaya Abubakar, Garba Jamilu, Aliyu Yakubu REGRESSION-TYPE IMPUTATION SCHEME UNDER SUBSAMPLING WITH EQUAL CHANCE OF RANDOM NON-RESPONSE AT FIRST STAGE. Reliability: Theory & Applications. 2024, December 4(80): 737-754, DOI: https://doi.org/10.24412/1932-2321-2024-480-737-754

737-754

M/M(A,B)/1 MULTIPLE WORKING VACATIONS QUEUING SYSTEM WITH HETEROGENOUS ENCOURAGED ARRIVAL

Prakati. P, Julia Rose Mary. K

The concept of Queuing system is most commonly used in our everyday life. It is essential to characterize the practical queuing characteristics in order to improve the performance of the queuing model. This study investigates M/M(a,b)/1/MWV queuing model with heterogeneous encouraged arrival occurring in the regular busy period. The considered model follows General bulk service rule and if the system is not in use, or when it is vacant, the server goes on vacation, thus there occurs multiple working vacations which are exponentially distributed. In this study, a model of multiple working vacation queues in which with heterogeneous encouraged arrivals following Poisson process is examined. With the mentioned conditions, the explicit formulations for the steady state probabilities and the performance measures of the proposed model are derived. Also, some particular cases have been developed and compared with existing models. Finally, the numerical impact of various parameters on performance attributes are also analysed.

Cite: Prakati. P, Julia Rose Mary. K M/M(A,B)/1 MULTIPLE WORKING VACATIONS QUEUING SYSTEM WITH HETEROGENOUS ENCOURAGED ARRIVAL. Reliability: Theory & Applications. 2024, December 4(80): 755-764, DOI: https://doi.org/10.24412/1932-2321-2024-480-755-764

755-764

TRIANGULAR AND SKEW-SYMMETRIC SPLITTING METHOD FOR SOLVING FUZZY STOCHASTIC LINEAR SYSTEM

A. Shivaji, B. Harika, D. Rajaiah, L.P. Rajkumar

Based on the Triangular and Skew Symmetric (TSS) splitting method, a novel iterative approach is proposed to solve a class of fuzzy regularized linear system of equations with fuzzy coefficient stochastic rate matrix. The non-homogeneous fully fuzzy linear system is same as the non-homogeneous linear system which is derived from the homogeneous linear system with stochastic rate matrix and steady state vector. An iterative procedure is developed for finding a unique non-trivial solution. Numerical results shown that the proposed method is effective and efficient when compared with the existing classical methods.

Cite: A. Shivaji, B. Harika, D. Rajaiah, L.P. Rajkumar TRIANGULAR AND SKEW-SYMMETRIC SPLITTING METHOD FOR SOLVING FUZZY STOCHASTIC LINEAR SYSTEM. Reliability: Theory & Applications. 2024, December 4(80): 765-773, DOI: https://doi.org/10.24412/1932-2321-2024-480-765-773

765-773

IMPACT OF PREVENTIVE MAINTENANCE AND FAILURE RATE ON A COMPLEXLY CONFIGURED SYSTEM: A SENSITIVE ANALYSIS

Shakuntla Singla, Diksha Mangla, Shilpa Rani, Umar Muhammad Modibbo

The availability of uninterrupted performance time has become essential for any industry seeking to maximize profits while incurring minimal maintenance costs. However, the system's components become weary as a result of the constant burden, resulting in decreased system efficiency and automatic full failure in the end. Complete failure is not always manageable; it might result in a significant loss of profit or productivity. In this regard, preventative maintenance is critical to ensuring that the industry runs smoothly, even with lower efficiency. Preventive maintenance is required in any sector to satisfy the demands of maximum profit and low cost for good output. This study examines the reliability of a complexly organized system of three units, A, B and C in order to determine its sensitivity to the effects of deteriorated rate and preventative maintenance rate over time. The three units are further made up of subunits which are in series or parallel configuration. The mathematical design work is based on the Markov process and the Laplace transformation. Different system parameters such as mean time to system failure, Available performance time, reliability, and profit, are analysed with respect to time and various rates. Further, A sensitivity analysis is used to explore how the rate of deterioration and preventative maintenance affects the system over time. Various malfunction and repair rates effect the system parameters in increasing or decreasing manner and sensitive analysis evaluated the impact of one unit on another or whole system. Here is a numerical example generated with the help of an appropriate model; the results are visually represented which concluded that with the passage of time reliability and other system parameters of system decreased under the influence of different rates. Utilizing the service cost, Profit is analysed which help to estimate the overall gain by the presented system. Also, by sensitive analysis it is concluded that out of three units A, B and C, Unit C has more effect as compared to B and C which is shown graphically. The purposed study can elaborate the profit after examined the reliability indices which become a key point for different industries like as diary plant, fertilizer plant etc. to have good outcomes with less maintenance cost.

Cite: Shakuntla Singla, Diksha Mangla, Shilpa Rani, Umar Muhammad Modibbo IMPACT OF PREVENTIVE MAINTENANCE AND FAILURE RATE ON A COMPLEXLY CONFIGURED SYSTEM: A SENSITIVE ANALYSIS. Reliability: Theory & Applications. 2024, December 4(80): 774-791, DOI: https://doi.org/10.24412/1932-2321-2024-480-774-791

774-791

ENHANCING PRECISION IN STRATIFIED SAMPLING USING MATHEMATICAL PROGRAMMING APPROACH

Mushtaq A. Lone, S. A. Mir, Kaisar Ahmad, Aafaq A. Rather, Danish Qayoom, S. Ramki

This article addresses the challenges of determining the optimal allocation of sample sizes in stratified sampling design to minimize the cost function. Researchers employed the iterative procedure of Rosen’s Gradient projection method and obtained optimal allocation of non-linear programming problem through manual calculation, which are often susceptible to human errors, such as rounding or arithmetic mistakes especially for complex nonlinear programming problems. R software performs calculations with high precision and consistency. In this paper, we demonstrate how to solve the non-linear programming problem by using iterative based procedure of Rosen’s Gradient projection method through R software.

Cite: Mushtaq A. Lone, S. A. Mir, Kaisar Ahmad, Aafaq A. Rather, Danish Qayoom, S. Ramki ENHANCING PRECISION IN STRATIFIED SAMPLING USING MATHEMATICAL PROGRAMMING APPROACH. Reliability: Theory & Applications. 2024, December 4(80): 792-796, DOI: https://doi.org/10.24412/1932-2321-2024-480-792-796

792-796

SAMPLE SIZE DETERMINATION PROCEDURES IN CLINICAL TRIALS: A COMPARATIVE ANALYSIS FOR RELIABLE AND VALID RESEARCH RESULTS

Faizan Danish, G.R.V. Triveni, Rafia Jan, Aafaq A. Rather, Danish Qayoom, Kaiser Ahmad

Accurate sample size determination is paramount in clinical trials assuring the consistency and validity of research studies. This comparative analysis delves into the various procedures employed for sample size estimation in clinical trials and assesses their effectiveness in producing reliable results. By numerous formulas and methods, this study seeks to identify best practices for optimizing sample sizes, thereby enhancing the statistical power of clinical trials. This research paper aims to conduct a comparative analysis of different formulae commonly employed in determining sample sizes evaluating their strengths, limitations, and applicability across various research scenarios. Several formulae have been considered with varying parameters, and the sample size was calculated and presented in different graphs.

Cite: Faizan Danish, G.R.V. Triveni, Rafia Jan, Aafaq A. Rather, Danish Qayoom, Kaiser Ahmad SAMPLE SIZE DETERMINATION PROCEDURES IN CLINICAL TRIALS: A COMPARATIVE ANALYSIS FOR RELIABLE AND VALID RESEARCH RESULTS. Reliability: Theory & Applications. 2024, December 4(80): 797-816, DOI: https://doi.org/10.24412/1932-2321-2024-480-797-816

797-816

OPTIMAL AND ECONOMIC DESIGN OF CHAIN SAMPLING PLAN FOR ASSURING MEDIAN LIFE UNDER NEW COMPOUNDED BELL WEIBULL LIFE TIME MODEL

M. Muthumeena, S. Balamurali

The methodology to design, one of the cumulative results plans called chain sampling plan, is proposed in this paper which ensures the median lifetime of the products under the complementary bell Weibull model. For costly and destructive testing, usually single sampling plan with zero acceptance number is used. But chain sampling plan is an alternative to zero acceptance number single sampling plans. A comparative analysis of proposed plan's OC curve outperforms in discrimination between the lots of varying quality, when compared to the single sampling plan. The advantages of the proposed plan by comparing the performance of the OC curve with other lifetime distributions are also discussed. Tables are constructed to select the optimal parameters for the various combinations of lifetime distributions. The implementation of the proposed plan in industrial scenarios is also explained by using a real time data. Finally, an economic design of the proposed sampling plan is discussed by considering some cost models to minimize the total cost.

Cite: M. Muthumeena, S. Balamurali OPTIMAL AND ECONOMIC DESIGN OF CHAIN SAMPLING PLAN FOR ASSURING MEDIAN LIFE UNDER NEW COMPOUNDED BELL WEIBULL LIFE TIME MODEL. Reliability: Theory & Applications. 2024, December 4(80): 817-834, DOI: https://doi.org/10.24412/1932-2321-2024-480-817-834

817-834

TWO-STAGE GROUP ACCEPTANCE SAMPLING PLAN FOR HALF-NORMAL DISTRIBUTION

C. Geetha, S. Jayabharathi, Mohammed Ahmar Uddin, Pachiyappan D

This paper proposes a time-truncated life test based on a two-stage group acceptance sampling plan for the percentile lifetime following a half-normal distribution. The optimal parameters for this plan are determined to simultaneously satisfy both producer’s and consumer’s risks for a given experimentation time and sample size. The efficiency of the proposed sampling plan is evaluated by comparing the average sample number with that of existing sampling plans. Industrial examples are provided to illustrate the application of the proposed sampling plan.

Cite: C. Geetha, S. Jayabharathi, Mohammed Ahmar Uddin, Pachiyappan D TWO-STAGE GROUP ACCEPTANCE SAMPLING PLAN FOR HALF-NORMAL DISTRIBUTION. Reliability: Theory & Applications. 2024, December 4(80): 835-841, DOI: https://doi.org/10.24412/1932-2321-2024-480-835-841

835-841

A NEW COMPACT DETECTION MODEL FOR LINE TRANSECT DATA SAMPLING

Ishfaq S. Ahmad, Rameesa Jan

A new parametric model is proposed in line transect sampling for perpendicular distances density functions. It is simple, compact and monotonic non increasing with distance from transect line and also satisfies the shoulder condition at the origin. Numerous interesting statistical properties like shape of the probability density function, moments, and other related measures are discussed. Method of Moments and Maximum Likelihood Estimation is carried out. Applicability of the model is demonstrated using a practical data set of perpendicular distances and compared with other models using some goodness of fit tests.

Cite: Ishfaq S. Ahmad, Rameesa Jan A NEW COMPACT DETECTION MODEL FOR LINE TRANSECT DATA SAMPLING. Reliability: Theory & Applications. 2024, December 4(80): 842-849, DOI: https://doi.org/10.24412/1932-2321-2024-480-842-849

842-849

A NEW ATTRIBUTE CONTROL CHART BASED ON EXPONENTIATED EXPONENTIAL DISTRIBUTION UNDER ACCELERATED LIFE TEST WITH HYBRID CENSORING

Gunasekaran Munian

In this article, we propose a new attribute np control chart for monitoring the median lifetime of the products under accelerated life test with hybrid censoring scheme assuming that the lifetime of the products  follows  an  exponentiated  exponential  distribution.  The  optimal parameters  for constructing the proposed control chart are determined so that the average run length for the in- control process is as closest to the prescribed average run length as possible. The control chart parameters are estimated for various set of values, and the developed control chart's performance is analysed using the average run length. The proposed control chart is illustrated with numerical examples, and its applicability is demonstrated with simulated data.

Cite: Gunasekaran Munian A NEW ATTRIBUTE CONTROL CHART BASED ON EXPONENTIATED EXPONENTIAL DISTRIBUTION UNDER ACCELERATED LIFE TEST WITH HYBRID CENSORING. Reliability: Theory & Applications. 2024, December 4(80): 850-860, DOI: https://doi.org/10.24412/1932-2321-2024-480-850-860

850-860

CHARACTERIZATION OF GENERALIZED DISTRIBUTIONS BASED ON CONDITIONAL EXPECTATION OF ORDER STATISTICS

Abu Bakar, Haseeb Athar, Mohd Azam Khan

Characterization of probability distributions plays a significant role in the field of probability and

statistics and attracted many researchers these days. Characterization refers to the process of identifying distributions uniquely based on certain statistical properties or functions. The various characterization results have been established by using different methods. The paper aims to characterize two general forms of continuous distributions using the conditional expectation of order statistics. Further, the results obtained are applied to some well-known continuous distributions. Finally, some numerical calculations are performed.

Cite: Abu Bakar, Haseeb Athar, Mohd Azam Khan CHARACTERIZATION OF GENERALIZED DISTRIBUTIONS BASED ON CONDITIONAL EXPECTATION OF ORDER STATISTICS. Reliability: Theory & Applications. 2024, December 4(80): 861-872, DOI: https://doi.org/10.24412/1932-2321-2024-480-861-872

861-872

A STOCHASTIC RELIABILITY MODELING APPROACH FOR MULTIPLE SYSTEM SUBSCALES

Alena Breznická, Ľudmila Timárová, Pavol Mikuš

The article discusses the approach of stochastic simulation of the reliability of technical systems.

Stochastic simulation works with variables that are expected to change with a certain probability. A stochastic model creates a projection of a model that is based on a set of random outputs. These are recorded, then the projection is repeated with a new set of random variables. Repetition takes place many times, which can be thousands or more repetitions. At the end of the process, the distribution of these outputs shows not only the most probable values and estimates, but also their limits, which are reasonable to expect. The presented paper presents the possibilities of simulation using the Matlab software package and illustrates the simulation experiment on a specific case of monitored reliability variables.

Cite: Alena Breznická, Ľudmila Timárová, Pavol Mikuš A STOCHASTIC RELIABILITY MODELING APPROACH FOR MULTIPLE SYSTEM SUBSCALES. Reliability: Theory & Applications. 2024, December 4(80): 873-881, DOI: https://doi.org/10.24412/1932-2321-2024-480-873-881

873-881

A PRODUCTION INVENTORY MODEL WITH TIME-DEPENDENT DEMAND, PRODUCTION AND DETERIORATION OVER A FINITE PLANNING HORIZON WITH TWO STORAGES

Neha Chauhan, Ajay Singh Yadav

The complexities of time-dependent demand, production rates, and deterioration over a limited planning horizon are taken into consideration in our comprehensive production inventory model, which has two distinct storage facilities. In our approach, these elements work together to provide a unified framework that maximizes inventory management strategies while staying within realistic bounds. Specifically, considering the effects of both short- and long-term deterioration, we look into how various demand trends and production capacity affect stock levels and storage decisions. Organizations can lower the risk of rotting and enable dynamic modifications to production schedules by employing a dual-storage method to assess inventory allocation in greater detail. Our model makes use of advanced optimization techniques to offer useful insights into how to meet fluctuating demand while controlling the expenses of manufacturing, storage, and inventory. We demonstrate the model’s efficacy and adaptability through numerical simulations and sensitivity analyses, offering managers a valuable instrument to enhance operational efficiency in scenarios including time-varying variables. This research improves the field by offering a strong solution framework for inventory management in complex scenarios with dual storage considerations, paving the way for more reliable and effective production strategies.

Cite: Neha Chauhan, Ajay Singh Yadav A PRODUCTION INVENTORY MODEL WITH TIME-DEPENDENT DEMAND, PRODUCTION AND DETERIORATION OVER A FINITE PLANNING HORIZON WITH TWO STORAGES. Reliability: Theory & Applications. 2024, December 4(80): 882-895, DOI: https://doi.org/10.24412/1932-2321-2024-480-882-895

882-895

A CLASS OF CONTROL CHARTS FOR PROCESS LOCATION PARAMETER OF EXPONENTIAL DISTRIBUTION

Sharada V. Bhat, Shradha Patil
 

Control charts are essential in production processes to maintain quality of the products. Inspite of numerous control charts existing for process location under normal model, there is a need for developing control charts when situations demand production process under other distributions. In this paper, a class of control charts based on various midranges is proposed for monitoring location parameter of an ongoing process when process variables follow exponential distribution. The midranges are defined and their distributions are obtained. The performance of some members of the proposed class are evaluated in terms of their power, average run length (ARL), median run length (MRL) and standard deviation of run length (SDRL). Also, optimality and effectiveness of members of the class are discussed along with their illustration through an example. tinent examples and proofs. Additionally, the illustration of the identification of paddy illnesses is analyzed with the tool of Quadrasophic Fuzzy Matrix in the decision-making process.

Cite: Sharada V. Bhat, Shradha Patil A CLASS OF CONTROL CHARTS FOR PROCESS LOCATION PARAMETER OF EXPONENTIAL DISTRIBUTION. Reliability: Theory & Applications. 2024, December 4(80): 896-908, DOI: https://doi.org/10.24412/1932-2321-2024-480-896-908

896-908

GENERALIZATION OF RAYLEIGH DISTRIBUTION THROUGH A NEW TRANSMUTATION TECHNIQUE

Aliya Syed Malik, S.P. Ahmad

In our research paper, we introduce an innovative statistical distribution known as the New Transmuted Rayleigh Distribution. This distribution serves as a versatile expansion of the traditional Rayleigh distribution and has been developed using a novel transmutation technique. We provide an in-depth analysis of several statistical properties of this new distribution. The resulting model has the ability to represent complex shapes, making it suitable for a wide range of applications. Our manuscript thoroughly examines the fundamental characteristics of the new model, outlining the methodology for estimating its unknown parameters through maximum likelihood estimation. Additionally, we demonstrate the practical significance of the model by applying it to an empirical dataset and conclusively establishing its superiority over some existing prominent models.

Cite: Aliya Syed Malik, S.P. Ahmad GENERALIZATION OF RAYLEIGH DISTRIBUTION THROUGH A NEW TRANSMUTATION TECHNIQUE. Reliability: Theory & Applications. 2024, December 4(80): 909-918, DOI: https://doi.org/10.24412/1932-2321-2024-480-909-918

909-918

MEASUREMENT AND DETERMINATION OF STRENGTH OF LOAD-BEARING STRUCTURES MATERIALS BY SHEAR TEST METHOD

Alena Rotaru

The strength of load-bearing and enclosing structures largely depends on the parameters of their materials. Complex shear testing of concrete is a non-destructive method used to determine the parameters and quality of the mixtures used with high accuracy. This concrete testing method has become widespread due to its versatility and convenience. The material strength is tested by directly impacting the concrete of the structure and causing its partial shearing. During the test, the force needed to tear off a fragment of the structure using a leafed anchor embedded in the bore hole is determined. This method can provide more accurate data on the concrete strength to make a decision on the need for further operation of the building. The concrete test to be shear tested must be located at a sufficient distance from pre-stressed rods. In addition, the test area should not be subjected to heavy operational loads.

Cite: Alena Rotaru MEASUREMENT AND DETERMINATION OF STRENGTH OF LOAD-BEARING STRUCTURES MATERIALS BY SHEAR TEST METHOD. Reliability: Theory & Applications. 2024, December 4(80): 919-923, DOI: https://doi.org/10.24412/1932-2321-2024-480-919-923

919-923

METHODS AND TOOLS OF INTELLIGENT SUPPORT FOR FORECASTING THE TECHNICAL CONDITION OF CRITICAL SYSTEMS

Oleg Abramov, Dmitry Nazarov

A variant of an expert-statistical approach to solving the problem of forecasting parametric deviations of critical systems condition is proposed. Issues of development of specialized software (case-based reasonong approach) with the necessary problem orientation (forecasting degradation of technical condition) and allowing to improve the quality of forecast are discussed. An approach to case describing using an ontological model of degradation processes with allowing to take into account both external influences, and internal processes characteristic of specific types of elements, is proposed.

Cite: Oleg Abramov, Dmitry Nazarov METHODS AND TOOLS OF INTELLIGENT SUPPORT FOR FORECASTING THE TECHNICAL CONDITION OF CRITICAL SYSTEMS. Reliability: Theory & Applications. 2024, December 4(80): 924-930, DOI: https://doi.org/10.24412/1932-2321-2024-480-924-930

924-930

A NEW ALGORITHM FOR MODELING ASYMMETRICAL DATA – AN EMPIRICAL STUDY

K.M. Sakthivel, Vidhya G

In the current era, it is quite challenging to find symmetric data, as the form of most real-world data is asymmetric, meaning it tends to slant towards one side or another. These types of data emerge from various fields, including finance, economics, medicine, and reliability. Traditional statistical models often fail to handle such type of data as most of the statistical procedures are developed under normality assumptions. Therefore, the usual way of modeling these data results in incorrect predictions or leads to wrong decisions. There is no familiar methodology available in the research for modeling asymmetric data. Hence, there is a need to address this research gap as an emerging area of research in statistical modeling. In this paper, we propose a new systematic approach called the Model Selection Algorithm for modeling asymmetric data. In this algorithm, we incorporate various statistical tools and provide a guideline for a step-by-step procedure. Further, we have applied maximum likelihood estimation for parameter estimation, and model selection criteria such as Cramer Von Mises, Anderson Darling, and Kolmogorov Smirnov tests. We used real-time data to demonstrate the effectiveness of the algorithm.

Cite: K.M. Sakthivel, Vidhya G A NEW ALGORITHM FOR MODELING ASYMMETRICAL DATA – AN EMPIRICAL STUDY. Reliability: Theory & Applications. 2024, December 4(80): 931-946, DOI: https://doi.org/10.24412/1932-2321-2024-480-931-946

931-946

A FUZZY LOGIC APPROACH TO DESIGNING A DOUBLE SAMPLING PLANS FOR ZERO INFLATED POISSON DISTRIBUTION USING IN PYTHON

Kavithanjali S, Sheik Abdullah A

Acceptance sampling plan by attributes is a statistical measure used in quality control in various production process. It is mainly determined for identifying whether the lot or the batch of the product is accepted or rejected based on the number of defective items in the sample. Appropriate sampling plan provides defect-free lot. There are several sampling plans are available for determine the sample size. Among the sampling plan, double sampling plan is more effective because it is always giving best result in lot selection compared with other sampling plan. In most of the practical situation, it is very hard to found the product as strictly defective or non-defective. In some situation, quality of the product can be classified several types which are expressed as good, almost good, bad not so bad and so on. This causes ambiguity deficiency in proportion value of lot or process. In mathematical tools, fuzzy set or fuzzy logic is one of the powerful modeling, which has incomplete and imprecise information. The fuzzy set theory is adopted to cope the vagueness in these linguistic expressions for the accepting sampling. In this article double sampling plans, are determined when non-conformities are fuzzy number and being modeled based on Zero-Inflated Poisson (ZIP) distribution. The Operating Characteristic (OC) function and Average Sample Number (ASN) function are evaluated both numerically and graphically in fuzzy and crisp environments.

Cite: Kavithanjali S, Sheik Abdullah A A FUZZY LOGIC APPROACH TO DESIGNING A DOUBLE SAMPLING PLANS FOR ZERO INFLATED POISSON DISTRIBUTION USING IN PYTHON. Reliability: Theory & Applications. 2024, December 4(80): 947-957, DOI: https://doi.org/10.24412/1932-2321-2024-480-947-957

947-957

CHARACTERISTIC FEATURES OF CONTROL METHODS IN ELECTROMECHANICAL DEVICES

G.V. Mamedova

Modern electromechanical devices for continuous process control are used in a variety of industrial applications. A control system or electromechanical device used to control the speed and torque of AC motors by varying the frequency and supply voltage converts alternating current of one frequency to alternating current of another frequency. The power section and the control device are the main elements of the control system. The main elements of a control system or electromechanical device are the power part (electrical energy converter) and the control device (controller). Modern frequency converters have a modular architecture, which expands the capabilities of the device, and also, in most cases, allows the installation of additional interface modules for input-output channels. The control device (microcontroller) is controlled by software and is controlled by the main parameters (speed or torque).

Cite: G.V. Mamedova CHARACTERISTIC FEATURES OF CONTROL METHODS IN ELECTROMECHANICAL DEVICES. Reliability: Theory & Applications. 2024, December 4(80): 958-966, DOI: https://doi.org/10.24412/1932-2321-2024-480-958-966

958-966

A STUDY ON CONVENTIONAL BULK QUEUES IN QUEUEING MODEL

Keerthiga S, Indhira K

The study on bulk arrival and batch service queueing models is discussed in this article. The mathematical logic of queueing models is crucial in many industries, especially in production lines, to minimize congestion issues. This survey seeks to review and model different occurrences in the area of bulk queues with vacations, breakdowns, and repairs. This research goals to provide enough information to analysts, researchers, and industry professionals to simulate congestion problems and create various performance measures to improve the queueing model.

Cite: Keerthiga S, Indhira K A STUDY ON CONVENTIONAL BULK QUEUES IN QUEUEING MODEL. Reliability: Theory & Applications. 2024, December 4(80): 967-979, DOI: https://doi.org/10.24412/1932-2321-2024-480-967-979

967-979

PROFIT ANALYSIS OF REPAIRABLE WARM STANDBY SYSTEM

Shiv Kant, Shashi Kant, Mohit Yadav, Arunita Chaukiyal, Bindu Jamwal

In the generation of science and technology, every company wants to increase the reliability of their products. So, they used the concept of warm standby redundancy, timely repair of the failed unit. This paper aims to explore the system of two non identical units where the primary unit is operative and the secondary unit is in warm standby mode. When the primary unit fails due to any fault then secondary unit starts working immediately. Here, times of failure of unit and times of repair of unit follow general distributions. Such types of systems are used in companies to prevent losses. The system’s behaviour is calculated by using concepts of mean time to system failure, availability, busy period of the server, expected number of visits made by the server and profit values using the semi Markov process and regenerative point technique. Tables are used to explore the performance of the system.

Cite: Shiv Kant, Shashi Kant, Mohit Yadav, Arunita Chaukiyal, Bindu Jamwal PROFIT ANALYSIS OF REPAIRABLE WARM STANDBY SYSTEM. Reliability: Theory & Applications. 2024, December 4(80): 461-467, DOI: https://doi.org/10.24412/1932-2321-2024-480-980-986