Journal of Reliability and Statistical Studies最新文献

Analysis of EAC Using Multiple Regression and Conditional Process: A Statistical Approach 利用多元回归和条件过程分析 EAC：统计方法

IF 0.9

Journal of Reliability and Statistical Studies Pub Date : 2024-07-03 DOI: 10.13052/jrss0974-8024.1715

Muskan Singh, Sachin Ghai, Amar Kumar Mishra, Nupur Goyal

{"title":"Analysis of EAC Using Multiple Regression and Conditional Process: A Statistical Approach","authors":"Muskan Singh, Sachin Ghai, Amar Kumar Mishra, Nupur Goyal","doi":"10.13052/jrss0974-8024.1715","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1715","url":null,"abstract":"In the modern world of increased competition, evolving technologies and volatile environment every institution must poise themselves to innovate and change, not only to prosper but merely to survive. The situation is more acute in institutions of higher education in India where things are changing with unprecedented speed. The survival of the institutions will depend upon the adaptability of their employees to embrace the change. However, employees’ acceptance to change cannot be developed overnight and also in isolation. It requires intensity and persistency of efforts in the right direction from the management. In the present paper, the researchers have identified the role of emotional intelligence and locus of control in enhancing employees’ acceptance to change in HEIs, Uttarakhand using multiple regression and conditional process analysis. The data for the present study were collected using stratified sampling and structured questionnaires from 432 employees from various HEIs in Uttarakhand. The finding revealed that EI enhances the EAC in HEI. Further, it also revealed that Job Satisfaction acts as a partial mediator in the relation between EI and EAC.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141684144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Study on One-Parameter Entropy-Transformed Exponential Distribution and Its Application 单参数熵变指数分布及其应用研究

IF 0.8

Journal of Reliability and Statistical Studies Pub Date : 2024-06-05 DOI: 10.13052/jrss0974-8024.1712

Mathew Stephen, David Ikwuoche John, Yaska Mutah

引用次数: 0

Optimizing Resource Allocation in M/M/1/N Queues with Feedback, Discouraged Arrivals, and Reneging for Enhanced Service Delivery 优化 M/M/1/N 队列中的资源分配，同时考虑反馈、受挫到达和背弃，以提高服务交付能力

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Journal of Reliability and Statistical Studies Pub Date : 2024-06-05 DOI: 10.13052/jrss0974-8024.1711

Savita, Amit Kumar, Chandra Shekhar

引用次数: 0

A Review Based on Various Applications to Find a Consistent Pairwise Comparison Matrix 基于各种应用寻找一致的配对比较矩阵的综述

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Journal of Reliability and Statistical Studies Pub Date : 2024-06-05 DOI: 10.13052/jrss0974-8024.1713

Shalu Kaushik, Sangeeta Pant, L. K. Joshi, Anuj Kumar, Mangey Ram

引用次数: 0

Modeling Software Release Time and Software Patch Release Time Based on Testing Effort and Warranty 基于测试工作和保修的软件发布时间和软件补丁发布时间建模

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Journal of Reliability and Statistical Studies Pub Date : 2024-06-05 DOI: 10.13052/jrss0974-8024.1714

Palak Saxena, Vijay Kumar, Stuti Tandon, Kuldeep Chaudhary, Mangey Ram

{"title":"Modeling Software Release Time and Software Patch Release Time Based on Testing Effort and Warranty","authors":"Palak Saxena, Vijay Kumar, Stuti Tandon, Kuldeep Chaudhary, Mangey Ram","doi":"10.13052/jrss0974-8024.1714","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1714","url":null,"abstract":"In this world of software technology, our dependency on software’s is increasing continuously. As a result, software industries are working hard to develop highly reliable software and to meet the expectation of customers. Generally, software companies release software early in market to take gain market share, but rigorous software testing is required for early release software to ensure reliability of software and meet the customer’s expectations. This requires a huge amount of resources, and it increases financial burden on the company, consequently, decreases the overall profit of company. Further, late release due to prolong testing of a software may improves reliability but results into a loss of market opportunity cost or may not be fulfil the customer’s aspirations. As a result, to stay competitive, companies release software early and release patches later to fix the bugs, improve the functionality of software, and to update the software. Software industries are improving the performance or usability of software by releasing patches which may increase the consumption of testing effort and consequently increase in cost. On the other hand, software firms also provide warranty on their products. To address the above said issues, we have developed a testing effort-based software reliability growth model, which incorporates warranty policy and estimates the optimal software release and patch time with the objective to minimise the total testing cost. Further, we have used Genetic Algorithm (GA) to estimate optimum software release and patch time. A numerical illustration has been presented on a real time data set to validate the proposed model.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141385435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bayesian Network Approach for Studying the Operational Reliability and Remaining Useful Life 研究运行可靠性和剩余使用寿命的贝叶斯网络方法

IF 0.8

Journal of Reliability and Statistical Studies Pub Date : 2024-05-14 DOI: 10.13052/jrss0974-8024.16210

Debasis Jana, Deepak Kumar, Suprakash Gupta, Sukomal Pal, Sandip Ghosh

{"title":"Bayesian Network Approach for Studying the Operational Reliability and Remaining Useful Life","authors":"Debasis Jana, Deepak Kumar, Suprakash Gupta, Sukomal Pal, Sandip Ghosh","doi":"10.13052/jrss0974-8024.16210","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.16210","url":null,"abstract":"Reliability study plays a significant role in supporting the operation of any machinery working in a dynamic and harsh environment such as mining, and construction industries. This quality is inherently uncertain and a stochastic variable of any system. This study focused on the effects of operating conditions (OCs) on the operational reliability and remaining useful life (RUL) of machinery. A probabilistic graphical method called Bayesian Network (BN) was used to study the effect of OCs on the system performance. The developed methodology has been demonstrated by analyzing the operational reliability and predicting the RUL of electrical motors operated in heavy mining machinery. The failure probabilities estimated from the historical data of the motor system are failure likelihood, and OCs are the evidence in the developed BN model. It has been observed that the performance and RUL of the motor are significantly influenced by OCs and maintenance. A threshold value of reliability at which the motor system requires maintenance or replacement has been proposed to guide management in decision-making. This study will be beneficial for designing an appropriate maintenance schedule, reducing unplanned production downtime, and reducing the maintenance cost of electrical motors operated particularly in dynamic and harsh environmental industries.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140979178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluation of the Reliability of a Standby Redundancy System Under Real Conditions 评估真实条件下备用冗余系统的可靠性

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Journal of Reliability and Statistical Studies Pub Date : 2024-05-07 DOI: 10.13052/jrss0974-8024.1629

H. A. Guesmi, S. O. Madbouly

引用次数: 0

Effect of Load on Sequential Imperfect Preventive Maintenance and Replacement Schedules of Mechanically Repairable Machines 负载对机械可修理机器的顺序不完善预防性维护和更换计划的影响

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Journal of Reliability and Statistical Studies Pub Date : 2024-03-27 DOI: 10.13052/jrss0974-8024.1628

Nse-Obong Udoh, Iniobong I. Uko, Kufre Bassey

{"title":"Effect of Load on Sequential Imperfect Preventive Maintenance and Replacement Schedules of Mechanically Repairable Machines","authors":"Nse-Obong Udoh, Iniobong I. Uko, Kufre Bassey","doi":"10.13052/jrss0974-8024.1628","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1628","url":null,"abstract":"This paper examines the impact of load on the operational time and maintenance cost of mechanically repairable machines. Three different levels of load with multiplicative impact on the hazard rate of the failure distribution were applied to the working of a cassava grinding machine using a two-parameter Weibull distribution with respective hazard and cumulative hazard functions. Their effect on the preventive maintenance (PM) and replacement schedules revealed that at above maximum load level, the length of the machine’s operational time decreased drastically compared to the decrease at maximum load level and relative decrease at the below maximum load level when compared to the machine’s operational time at the minimum load level. The application of load also results in frequent preventive maintenance actions and an increase in machine downtime for a given cost ratio. This implies that the influence of load on the PM and replacement maintenance schedule of mechanically repairable machines is essential to the design and operation of such machines. The results also provide maintenance engineers with an operational guide for PM and replacement maintenance actions in order to prevent failure maintenance and increase the machine’s availability for enhanced productivity.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140373475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reliability Analysis and Life Cycle Cost Optimization of Hydraulic Excavator 液压挖掘机的可靠性分析和生命周期成本优化

IF 0.8

Journal of Reliability and Statistical Studies Pub Date : 2024-03-17 DOI: 10.13052/jrss0974-8024.1626

Sandeep Kumar Mishra, N. Goyal, Arup Mukherjee

{"title":"Reliability Analysis and Life Cycle Cost Optimization of Hydraulic Excavator","authors":"Sandeep Kumar Mishra, N. Goyal, Arup Mukherjee","doi":"10.13052/jrss0974-8024.1626","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1626","url":null,"abstract":"This study focuses on conducting a reliability analysis of an excavator from its field failure data and improve its reliability cost effectively. The aim of the research is to perform reliability estimation of systems and identify the critical subsystem with significant contributions to system unreliability. The reliability analysis was performed using repairable system data analysis approaches. Life cycle cost (LCC) was estimated for critical subsystems, and it was optimized to select cost effective reliability improvement strategy. The results of the study provide valuable insights into the performance and cost-effectiveness of the excavator and its subsystems, which can assist manufacturers and operators in optimizing their equipment’s reliability, availability while considering the cost implications over the life cycle of the equipment. The results show that the undercarriage has critical contributions to system unreliability. This study attempts deep down reliability analysis of critical undercarriage components for optimal selection of improvement method among feasible alternatives. LCC analysis and its optimization performed on the critical sub-system is expected to help OEM save approx. 15% of LCC. The empirical data used in the paper is based on field data gathered during the operational life of the hydraulic excavator over approx. six years in its Indian operations.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140235276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generalized Estimator of Population Mean Using Auxiliary Information in Presence of Measurement Errors 存在测量误差时使用辅助信息的人口平均值广义估计器

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Journal of Reliability and Statistical Studies Pub Date : 2024-01-23 DOI: 10.13052/jrss0974-8024.1624

Peeyush Misra

引用次数: 0