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Editorial IN MEMORIAM: NOZER D. SINGPURWALLA
Nozer D. Singpurwalla died on July 22, 2022 at his home in Washington, DC, surrounded by family. Nozer was born in Hubli, India. As a young man, he immigrated to the United States, where he obtained a M.S. in Engineering from Rutgers University, and a Ph.D. in Engineering from New York University. He met Norah Jackson, who had recently immigrated from England, at a dance at Disneyland, and they married in 1969. Nozer and Norah lived most of their married life in Arlington, Virginia, where they raised their two children, Rachel and Darius. Nozer had a curious and creative mind and took much pleasure in his long and happy career as an academic. He spent most of his career at The George Washington University, where he was Distinguished Research Professor and Professor of Statistics. He published a wide variety of books and articles focusing on reliability theory, Bayesian statistics, and risk analysis. He supervised many PhD students and received numerous professional awards, including recognitions as a Fellow of the Institute of Mathematical Statistics, the American Statistical Association, and the American Association for the Advancement of Science, and an Elected Member of the International Statistical Institute. Nozer had a way with words and always enjoyed a spirited debate. He loved classical music, history and politics, and world travel with his family. He is survived by his wife, Norah (née Jackson), his sister, Khorshed Tantra, and her family, his children, Rachel (Peter) and Darius (Jennifer), and his beloved grandchildren, Veronika and Cyrus. There will be a private family memorial in his honor.
A. Lakshmana Rao, S. Arun Kumar, K. P. S. Suryanarayana INVENTORY MODEL WITH EXPONENTIAL DETERIORATION AND SHORTAGES FOR SEVERAL LEVELS OF PRODUCTION
The EPQ models are mathematical models which represent the inventory situation in a production or manufacturing system. In production and manufacturing units, the EPQ model is extremely significant and also be utilized for scheduling the optimal operating policies of market yards, warehouses, godowns, etc. In this research study, we provide inventory model of economic production for deteriorating commodities at multiple levels, in which various production stages are mentioned as well as deterioration rates follow exponential distributions. After a specific period of time, it is feasible to swap production rates from one to another, which is advantageous by starting with a production of low rate, an enormous amount of manufacturing articles is avoided at the outset, resulting in lower holding costs. Variation in output level allows for customer happiness as well as potential profit. The goal of this study is to determine the best production time solution so as to reduce total cost of the entire cycle. Finally, numerical illustrations and parameter sensitivity analyses have been used to validate proposed inventory system's results.
DOI: https://doi.org/10.24412/1932-2321-2022-369-20-30
M. I. Uspensky SOFTWARE CONTRIBUTION TO THE AVAILABILITY OF MICROPROCESSOR-BASED RELAY PROTECTION
An important characteristic of relay protection functioning is availability of microprocessor relay protection software. An approach to estimation of such parameter and correlation between it and hardware availability on the example of 110/35/10 kV distribution network microprocessor protection is considered in the paper. The behavioral nature of the availability under research, reasons and a share of various kinds of the error leading to failure of program execution, variants of program volume definition, some solution approaches to the task at hand, including methods of Jelinsky-Moranda, and also examples of assessing the ratio of these availabilities are considered. An algorithm for the software evaluation used is presented. The influence of different conditions on such evaluation is shown. Applications of different approaches to software readiness estimation for the above types of protection based on data during debugging of protection programs are given.
DOI: https://doi.org/10.24412/1932-2321-2022-369-31-39
Pradeep Chaudhary, Surbhi Masih, Rakesh Gupta
The paper deals with the analysis of a system model consisting of two non-identical units arranged in a parallel configuration. If a unit fails it goes to repair. After its repair, the repaired unit is sent for post repair to complete its repair. A single repairman is always available with the system to repair a failed unit and for post repair of repaired unit. A post repaired unit always works as good as new. Failure time of both the units is assumed to be correlated random variables having their joint distribution as bivariate exponential (B.V.E.). The repair time distribution of both the units are taken as general with different c.d.fs whereas the post repair time distribution of both the units are taken as exponential with different parameters.
DOI: https://doi.org/10.24412/1932-2321-2022-369-40-51
Akhila K Varghese, V. M. Chacko ESTIMATION OF STRESS-STRENGTH RELIABILITY FOR AKASH DISTRIBUTION
In this paper, we consider the estimation of the stress–strength parameter R = P[Y < X], when X and Y are following one-parameter Akash distributions with parameter 𝜃! and 𝜃" respectively. It is assumed that they are independently distributed. The maximum likelihood estimator (MLE) of R and its asymptotic distribution are obtained. Asymptotic distributions of the maximum likelihood estimator is useful for constructing confidence interval of P[Y < X]. The Bootstrap confidence interval of P[Y < X] is also computed. The illustrative part consists of the analysis of two real data sets, (i) simulated and (ii) real.
DOI: https://doi.org/10.24412/1932-2321-2022-369-52-58
M. Kalaivani, R. Kannan
The focus of this paper is to estimate the reliability characteristics of a linear consecutive k-out-of-n: F system with n linearly ordered components. The components are independent and identically distributed with exponentiated Weibull lifetimes. The system fails if and only if at least k successive components fail. In such a system, the reliability function and mean time to system failure are obtained by maximum likelihood estimation method using uncensored failure observations. The asymptotic confidence interval is determined for the reliability function. The results are obtained by Monte Carlo simulation to compare the performance of the systems using various sample sizes and combination of parameters. The procedure is also illustrated through a real data set.
DOI: https://doi.org/10.24412/1932-2321-2022-369-59-71
Mohammed Lahlou, Bouchra Saadouki, Abderrazak En-naji, Fatima Majid, Nadia Mouhib
During operation, most mechanical structures are subjected to time-varying stresses, which leads to their failure of serious accidents. The lifetime of a mechanical structure is broken down into three stages: stage I; the initiation, stage II; the slow propagation and stage III; the brutal propagation. The objective of this paper is to determine the damage and the lifetime of a pressure equipment by establishing a numerical modeling by finite elements on different specimens (SENT, SENB, DENT, CT) using the calculation code CASTEM. The material studied is P265GH steel commonly used as boiler plate and pressure vessels. The results show that the damage severity of the SENT specimen is more important, followed by the DENT specimen, then the CT specimen and finally SENB.
DOI: https://doi.org/10.24412/1932-2321-2022-369-72-81
D.Madhulatha, K. Srinivasa Rao, B. Muniswamy
Economic production quantity (EPQ) models are more important for scheduling production processes in particular batch production in which the production uptime and production downtime are decision variables. This paper addresses the development and analysis of an EPQ model with random production and Weibull decay having stock dependent demand. The random production is more appropriate in several production processes dealing with deteriorated items. The instantaneous state of on hand inventory is derived. With appropriate cost considerations the total cost function is derived and minimized for obtaining optimal production uptime, production downtime and production quantity. The model sensitivity with respect to changes in parameters and costs is also studied and observe that the production distribution parameters and deteriorating distribution parameters have significant influence on optimal operating policies of the model. This model is extended to the case of without shortages and observed that allowing shortages reduce total product cost. It is further observed that the demand being a function of on hand inventory can reduce inventory cost than other patterns of demand.
DOI: https://doi.org/10.24412/1932-2321-2022-369-82-96
S. Suganya, K. Pradeepa Veerakumari
This paper justify the scheming technique of new system of skip-lot sampling plan of type SkSP-T with Special type Double Sampling plan as Reference plan Using Fuzzy Logic Techniques. The designing methodology includes the evaluation of Acceptable Quality Level, Limiting Quality Level, Operating ratio and the Operating Characteristic (OC) Curves are constructed for using various Fuzzy parametric values. Also draw the Fuzzy OC Band for new proposed plan. FOC band specify the fuzzy probability of acceptance value with corresponding fraction of nonconforming items of this sampling plan.
DOI: https://doi.org/10.24412/1932-2321-2022-369-97-107
Nse Udoh, Iniobong Uko, Akaninyene Udom
Proper maintenance of non-repairable systems is essential for optimum utilization of systems to prevent lost production runs, cost inefficiencies, defective output which leads to customer dissatisfaction and unavailability of the facility for future use. This work proposes new preventive replacement maintenance models with constant-interval preventive replacement time with associated cost of replacement maintenance. Improved results of economic values with respect to optimal replacement time at minimum cost were obtained for radio transmitter system with sudden but non-constant failure rate when compared to some existing models. Other parameters and maintenance probabilities of the system were also obtained including; reliability, hazard rate and availability to ascertain the operational condition of the system.
DOI: https://doi.org/10.24412/1932-2321-2022-369-108-120
Neelam Singla, Sonia Kalra ANALYSIS OF A TWO-STATE PARALLEL SERVERS RETRIAL QUEUEING MODEL WITH BATCH DEPARTURES
This paper deals with the transient state behavior of an M/M/1 retrial queueing model contains two parallel servers with departures occur in batches. At the arrival epoch, if all servers are busy then customers join the retrial group. Whereas, if the customers find any of one server is free then they join the free server and start its service immediately. Here, we assume that primary customers arrive according to Poisson process. The retrial customers also follow the same fashion. Service time follows an exponential distribution. Explicit time dependent probabilities of exact number of arrivals and exact number of departures when both servers are free or when one server is busy or when both servers are busy are obtained by solving the difference differential equation recursively. Some important verification and conversion of two-state model into single state are also discussed. Some of the existing results in the form of special cases have been deduced.
DOI: https://doi.org/10.24412/1932-2321-2022-369-121-130
Adilakshmi Siripurapu, Ravi Shankar Nowpada Fuzzy Project Planning and Scheduling with Pentagonal Fuzzy Number
In optimization approaches such as assignment issues, transportation problems, project schedules, artificial intelligence, data analysis, network flow analysis, an uncertain environment in organizational economics, and so on, ranking fuzzy numbers is essential. This paper introduces a new fuzzy ranking in Pentagonal fuzzy numbers. Each activity’s duration is expressed as a Pentagonal fuzzy number in the project schedule. The new ranking function transforms every Pentagonal fuzzy number into a crisp number (normal number). We calculated the fuzzy critical path using a new algorithm. These approaches are illustrated with a numerical example.
DOI: https://doi.org/10.24412/1932-2321-2022-369-131-138
Priyanka Patel, Dr. Amit Nayak
Surveillance is the monitoring of behavior, actions, or information, with the purpose of collecting, influencing, controlling, or guiding evidence. Despite the technical traits of cutting-edge science, it is difficult to detect abnormal events in the surveillance video and requires exhaustive human efforts. Anomalous events in the video remain a challenge due to the occlusions of objects, different densities of the crowd, cluttered backgrounds & objects, and movements in complex scenes and situations. In this paper, we propose a new model called time distributed convolutional neural network long shortterm memory Spatiotemporal Autoencoder (TDSTConvLSTM), which uses a deep neural network to automatically learn video interpretation. Convolution neural network is used to extract visual features from spatial and time distributed LSTM use for sequence learning in temporal dimensions. Since most anomaly detection data sets are restricted to appearance anomalies or unusual motion. There are some anomaly detection data-sets available such as the UCSD Pedestrian dataset, CUHK Avenue, Subway entry-exit, ShanghaiTech, street scene, UCF-crime, etc. with varieties of anomaly classes. To narrow down the variations, this system can detect cyclists, bikers, skaters, cars, trucks, tempo, tractors, wheelchairs, and walkers who are walking on loan (off the road) which are visible under normal conditions and have a great impact on the safety of pedestrians. The Time distributed ConvLSTM has been trained with a normal video frame sequence belonging to these mentioned classes. The experiments are performed on the mentioned architecture and with benchmark data sets UCSD PED1, UCSD PED2, CUHK Avenue, and ShanghaiTech. The Pattern to catch anomalies from video involves the extraction of both spatial and temporal features. The growing interest in deep learning approaches to video surveillance raises concerns about the accuracy and efficiency of neural networks. The time distributed ConvLSTM model is good compared to benchmark models.
DOI: https://doi.org/10.24412/1932-2321-2022-369-139-161
Rama Shanker, Reshma Upadhyay, Kamlesh Kumar Shukla
A two-parameter quasi Suja distribution which contains Suja distribution as particular case has been proposed for extreme right skewed data. Its statistical properties including moments, skewness, kurtosis, hazard rate function, mean residual life function, stochastic ordering, mean deviations, Bonferroni and Lorenz curves, Renyi entropy measures, and stress-strength reliability have been derived and studied. The estimation of parameters using method of moments and maximum likelihood has been discussed. A simulation study has been presented to know the performance of maximum likelihood estimation. The goodness of fit of the proposed distribution has been presented.
DOI: https://doi.org/10.24412/1932-2321-2022-369-162-178
Rupali Kapase, Vikas Ghute Estimation of the Change Point in the Mean Control Chart for Autocorrelated Processes
Control charts are the most popular monitoring tools used to monitor changes in a process and distinguish between assignable and chance causes of variations. The time that a control chart gives an out-of-control signal is not the real time of change. The actual time of change is called the change point. Knowing the real time of change will help and simplify finding the assignable causes of the signal which may be the result of the shift in the process parameters. In this paper, we propose a maximum likelihood estimator of the process change point when a Shewhart X " chart with autocorrelated observations signals a change in the process mean. The performance of the proposed change point estimator when used with X " chart with AR(1) process is investigated using simulation study. The results show that the performance of the proposed estimator has good properties in the aspect of expected length and coverage probability. We illustrate the use of proposed change point estimator through an example.
DOI: https://doi.org/10.24412/1932-2321-2022-369-179-189
Er. Sudhir Kumar, Dr. P.C. Tewari
This work seeks to propose a Petri nets-based technique for evaluating the performability features of ash handling system of a coal-based thermal power plant. The impact of failure and repair parameters on system performance has been determined. For the modelling of the system Stochastic Petri Nets (SPN) an extended version of Petri nets is applied. The recommended methodology used in this study allows for a better understanding of the system's performance behavior under various operating situations. The study provides Decision Support System which will assist managers in making informed decisions about inventory and spare parts for plant operations.
DOI: https://doi.org/10.24412/1932-2321-2022-369-190-201
Jyotishree Ghosh, D. Pawar, S.C. Malik Analysis of Triple-Unit System with Operational Priority
Reliability of three non-identical unit system is analyzed for various measures. Initially, main unit is operational, one is warm standby and other is cold standby. Single repair facility is present with the system. Operational priority is given to main unit over standby units. Failure times of all the components are exponentially distributed whereas repair time follows Weibull distribution. All the random variables are statistically independent. Semi-Markov process and regenerative point technique are used to analyze mean time to system failure, availability, busy period and expected number of visits by the server. System model’s profit is analyzed for arbitrary values and are shown graphically.
DOI: https://doi.org/10.24412/1932-2321-2022-369-202-210
Ibrahim Yusuf, Nafisatu Muhammad Usman, Abdulkareem Lado Ismail
The dependability analysis of a hybrid series-parallel system with five subsystems A, B, C, D, and E is the subject of this research. Subsystem A has two active parallel units, whereas subsystem B has two out of four active units. Both units have a failure and repair time that is exponential. There are two states in the system under consideration: partial failure and complete failure. To assess the system's dependability, the system's first-order partial differential equations are constructed from the system transition diagram, resolved using the supplementary variables technique, and the reliability models are Laplace transformed. Failure times are assumed to follow an exponential distribution, whereas repair times are expected to follow a general distribution and a Gumbel-Hougaard family copula distribution. Reliability measurements of testing system effectiveness are derived and investigated, including reliability, availability, MTTF, sensitivity MTTF, and cost function. Tables and graphs show some of the most relevant findings.
DOI: https://doi.org/10.24412/1932-2321-2022-369-211-229
Nalini Kanta Barpanda, Ranjan Kumar Dash Optimization of Reliability under Different flow state of Multistate Flow Network
This paper focuses on maximizing the reliability of multistate flow network(MFN) by meeting the demand to flow from source to destination. The reliability maximization problem is formulated considering the different flow state of the edges and their corresponding existence probabilities. A method based on genetic algorithm is proposed to maximize the reliability of MFN searching through the state space. Each step of the proposed method is illustrated by taking a suitable example network. The values of computed reliability by the proposed method is exactly same as computed by the deterministic approach. The reliability of some benchmark networks are evaluated under different demand levels. The reliability of a practical example network is evaluated and compared against the reliability value computed by some deterministic approaches of similar interest. The computational time of the proposed method is also compared with these methods. The comparison findings reveal that the proposed method surpasses existing methods on the basis of computed reliability values and computational time.
DOI: https://doi.org/10.24412/1932-2321-2022-369-230-241
A. Bochkov, N. Zhigirev, A. Kuzminova Inversion Method of Consistency Measure Estimation Expert Opinions
The problem of collective choice is the problem of combining several individual experts' opinions about the order of preference of objects (alternatives) being compared into a single "group" preference. The complexity of collective choice consists in the necessity of processing the ratings of the compared alternatives set by different experts in their own private scales. This article presents the author's original algorithm for processing expert preferences in the problem of collective choice, based on the notion of the total "error" of the experts and measuring their contribution to the collective measure of their consistency. The presentation of the material includes the necessary theoretical part consisting of basic definitions and rules, the statement of the problem and the method itself based on the majority rule, but in the group order of objects.
DOI: https://doi.org/10.24412/1932-2321-2022-369-242-252
O. B. Zaitseva
The work analyzes the security model described by the controlled semi-Markov process with catastrophes. Management optimization is associated with determining the frequency of restoration work of the subsystem (security subsystem) which acts up attempts of malicious persons to disrupt the normal operation of the main system. The optimization criterion is the mathematical expectation of the time before the catastrophe (the moment of the first successful attempt to disrupt the normal operation of the main system). In the context of new linear limitations on management strategies, the structure of the optimal strategy was examined.
DOI: https://doi.org/10.24412/1932-2321-2022-369-253-260
Anwar hassan, Murtiza Ali Lone, Ishfaq Hassain Dar, Peer Bilal Ahmad A new continuous probability model based on a trigonometric function: Theory and applications
In this manuscript, we highlight a new probability distribution based on a trigonometric function, obtained by specializing the Sine-G family of distributions with exponentiated exponential distribution. The proposed distribution is quite flexible in terms of density and hazard rate functions. Several mathematical properties of the proposed distribution are also explored. For applicability of proposed distribution, two real data sets are scrutinized and it is sensed that proposed distribution leads to a better fit than all other models taken under consideration.
DOI: https://doi.org/10.24412/1932-2321-2022-369-261-272
A.Yu. Veretennikov, M.A. Veretennikova On Markov–up processes and their recurrence properties
A simple model of the new notion of “Markov up” processes is proposed; its positive recurrence and ergodic properties are shown under the appropriate conditions. A one-dimensional process in discrete time moves upwards as if it were Markov, and goes down in a more complicated way, remembering all its past from the moment of its “u-turn” down. Also, it is assumed that in some sense its move downwards becomes more and more probable after each step in this direction.
DOI: https://doi.org/10.24412/1932-2321-2022-369-273-291
K. Jyothsna, P. Vijaya Kumar, Ch. Gopala Rao DISCRETE-TIME WORKING VACATIONS QUEUE WITH IMPATIENT CLIENTS AND CONGESTION DEPENDENT SERVICE RATES
The current research article explores a finite capacity discrete-time multiple working vacations queue with impatient clients and congestion dependent service rates. An arriving client can choose either to enter the queue or balk with a certain probability. Due to impatience, he may renege after joining the queue as per geometric distribution. Rather than totally shutting down the service throughout the vacation period, the server functions with a different service rate. The times of services during regular service and during working vacation periods are considered to be geometrically distributed. The vacation periods are also presumed to be geometrically distributed. In addition, the service rates are considered to be dependent on the number of clients in the system during regular service period and during working vacation period. The model’s steady-state probabilities are calculated using matrix approach and a recursive solution is also provided. The recursive solution is used for obtaining the corresponding continuous-time results. Various system performance metrics are presented. Finally, the numerical representation of the consequences of the model parameters on the performance metrics is furnished.
DOI: https://doi.org/10.24412/1932-2321-2022-369-292-300
Gurami Tsitsiashvili, Tatiana Radchenkova QUEUING SYSTEM WITHOUT QUEUE AND DETERMINISTIC SERVICE TIME
There is a model of fault-counting data collected in the testing process of software development. In this model it is performed simulation based on the infinite server queueing model using the generated sample data of the fault detection time to visualize the efficiency of fault correction activities. In this model the thinning method using intensity functions of the delayed S-shaped and inflection S-shaped software reliability growth models to generate sample data of the fault detection time from the fault-counting data. But this model does not allow to analyse such systems without dependence of input and service intensities. In this paper, we consider a queuing system model with an infinite number of servers and a deterministic service time. The input flow to the system is non-stationary Poisson. It is investigated analytically how the parameter of the Poisson distribution characterizing the number of customers in the system depends on the service time in the presence of a peak load determined by the variable intensity of the input flow. In numerical simulations it is shown how graphs of the Poisson distribution parameter depends on deterministic service time.
DOI: https://doi.org/10.24412/1932-2321-2022-369-301-305
Aijaz Ahmad, Afaq Ahmad, I. H. Dar, Rajnee Tripathi
This work suggests a novel two-parameter distribution known as the log-Hamza distribution, in short (LHD). The significant property of the investigated distribution is that it belongs to the family of distributions that have support (0,1). Several statistical features of the investigated distribution were studied, including moments, moment generating functions, order statistics, and reliability measures. For different parameter values, a graphical representation of the probability density function (pdf) and the cumulative distribution function (CDF) is provided. The distribution’s parameters are determined using the well-known maximum likelihood estimation approach. Finally, an application is used to evaluate the effectiveness of the distribution.
DOI: https://doi.org/10.24412/1932-2321-2022-369-306-314
Kajal Sachdeva, Gulshan Taneja, Amit Manocha Sensitivity and Economic Analysis of an Insured System with Extended Conditional Warranty
Warranty and insurance are equally essential for a technological system to cover repair/replacement costs of all types of losses, i.e., natural wear/tear or unexpected external force/accidents. This paper examines the sensitivity and profitability of a stochastic model whose defects may cover under conditional warranty/insurance. The system user may extend the warranty period by paying an additional price. As a result, the system functions in normal warranty, extended warranty, and during non-warranty periods. If a system fault occurred is covered under warranty conditions, the manufacturer is responsible for all repair/replacement costs during normal/extended warranty which otherwise are paid by the insurance provider if covered under an insurance claim, or else, the user is responsible for the entire cost when coverage of fault neither falls in warranty conditions nor under the insurance policy. Using Markov and the regenerative process, various measures of system effectiveness associated with the profit of the user and the manufacturer are examined. Relative sensitivity analysis of the profit function and availability has been performed for all periods.
DOI: https://doi.org/10.24412/1932-2321-2022-369-315-327
Kuldeep Singh Chauhan
We recommended an inverse distributions family. The challenge of estimating R(t) and P in type-II censoring was measured to produce Uniformly Minimum Variance Unbiased Estimator (UMVUE) and Maximum Likelihood Estimator (MLE). The estimators have been created for R(t) and P.Testing approaches for R(t) and P under type-II censoring have been constructed for hypotheses associated with various parametric functions. The author provides an alternate method for generating these estimators. A comparative assessment of two estimating techniques has been conducted. The simulation technique has been used to assess the performance of estimators.
DOI: https://doi.org/10.24412/1932-2321-2022-369-328-339
Dhaval Bhoi, Amit Thakkar
Customers nowadays are more opinionated than they have ever been. They appreciate interacting with industries or businesses and providing feedback like positive, neutral and negative. Customers leave a plethora of information every time they connect with a company, whether it is through a mention or a review, letting businesses know what they are doing well and wrong. However, wading through all of this data by hand may be laborious task. Aspect-based sentiment analysis, on the other hand, can assist you in overcoming this issue. Because of their inherent competency in the semantic synchronization among aspects with associated contextual terms, attention mechanisms and Convolutional Neural Networks (CNNs) are often utilized for aspect-based sentiment categorization. However, because these models lack a mechanism for accounting for important syntactical restrictions and long-range word dependencies, they may incorrectly identify syntactically irrelevant contextual terms as hints for determining aspect emotion. To solve this problem, we suggest establishing a Graph Convolutional Network (GCN) over a sentence’s dependency tree, which is generated using bidirectional Long Short Term Memory (Bi-LSTM). A new aspect-specific sentiment categorization system is proposed as a result of it. Studies on several testing sets show how our suggested approach is on par with a number of state-of-the-art deep learning models in terms of reliable performance efficacy, and that the graph convolution structure appropriately captures both syntactic and semantic data and lengthy-term associations to perform reliable sentiment classification based on the aspects present in the review sentences.
DOI: https://doi.org/10.24412/1932-2321-2022-369-340-348
Ramanpreet Kaur, Upasana Sharma MEASURES TO ENSURE THE RELIABILITY OF WATER SUPPLY IN THE MLDB SYSTEM USING REFRIGERATION
Various components work together to form a system’s overall structure. Last but not least, how well each component functions affects how the system functions. Both a functioning and failing state are possible for a system built from components. Failure has a big effect on the way systems work in industry. So, in order to enhance system performance, it is essential to get rid of these errors. The aim of this research is to assess the scope of water supply concerns in the MLDB (Multi-Level Die Block) system at the Piston Foundry Plant.The MLDB system, which consists of a robotic key unit that works with the water supply, is the subject of this research. Robotic failure and a lack of water supply cause the system to fail. A reliability model is created in order to calculate MTSF (mean time to system failure), availability, busy times for repair, and profit evaluation. The abovementioned measurements were computed numerically and graphically using semi-Markov processes and the regenerating point technique. The results of this study are novel since no previous research has concentrated on the critical function of water delivery in the MLDB system in piston foundries. According to the discussion, the findings are both highly exciting and beneficial for piston manufacturing businesses who use the MLDB system. For companies that make pistons and use the MLDB system, the conclusions, according to the debate, are particularly beneficial.
DOI: https://doi.org/10.24412/1932-2321-2022-369-349-360
Nicy Sebastian, Jeena Joseph, Princy T Type 1 Topp-Leone q-Exponential Distribution and its Applications
The main purpose of this paper is to discuss a new lifetime distribution, called the type 1 Topp-Leone generated q-exponential distribution (Type 1 TLqE). Using the quantile approach various distributional properties, Lmoments, order statistics, and reliability properties were established. We suggested a new reliability test plan, which is more advantageous and helps in making optimal decisions when the lifetimes follow this distribution. The new test plan is applied to illustrate its use in industrial contexts. Finally, we proved empirically the importance and the flexibility of the new model in model building by using a real data set.
DOI: https://doi.org/10.24412/1932-2321-2022-369-361-375
Neelam Singla, Ankita Garg Single Server Retrial Queueing System with Catastrophe
The present paper analyses a retrial queueing system with Catastrophe. Primary and secondary customers follow Poisson processes. Inter arrival and service times are Exponentially distributed. Catastrophe occurs on a busy server and follows Poisson process. The server is sent for repair after its failure. The repair times are also Exponentially distributed. Steady state and time dependent solutions for number of customers in the system when the server is idle or busy are obtained. The probability of the server being under repair is obtained. Some performance measures are also evaluated. Numerical results are obtained and represented graphically.
DOI: https://doi.org/10.24412/1932-2321-2022-369-376-390
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Statistic, Probability and Uncertainty :
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