For improving the method of finding maintenance windows under uncertain parameters, an algorithm of maintenance window under uncertainties is presented using interval analysis and sensitivity analysis. Age replacement...For improving the method of finding maintenance windows under uncertain parameters, an algorithm of maintenance window under uncertainties is presented using interval analysis and sensitivity analysis. Age replacement model is selected to demonstrate how to use this new algorithm. Considered the uncertainties, the optimal maintenance interval of preventive maintenance is not only a single value, but a possible range. The requirement from maintenance engineers is also considered, the maintenance window is made as a symmetrical interval format, like(100 ± 10) day. Comparing with the methods using in the literatures, the new algorithm is without requirement of distribution assumption of uncertain parameter values and computer simulation.展开更多
The maintenance window scheme(MWS) is one of the most important railway transportation organizational plans and plays an important role in ensuring railway operational safety. However, MWS setting is a very complicate...The maintenance window scheme(MWS) is one of the most important railway transportation organizational plans and plays an important role in ensuring railway operational safety. However, MWS setting is a very complicated process, and most countries currently do so with the help of a computer-aided decision system. In general, a decision system can generate multiple alternatives for MWS within an acceptable time. Therefore, how to choose the best option from the alternatives is a vital decision. This paper presents a novel framework for MWS evaluation based on the Chinese railway system. Specifically, the requirements of each department related to MWS setting are analysed, and we construct an evaluation indicator system for MWS based on the preferences of different departments. Then, we apply the fuzzy soft set theory to MWS evaluation, a method that not only effectively deals with evaluation of uncertain information, but also gives flexibility for experts to input their subjective judgment.Additionally, using the ‘‘AND’’ operation of soft set theory allows combing evaluation information from multiple evaluators to give comprehensive results. Finally, a case study illustrates the proposed framework, showing that the proposed evaluation indicator system and evaluation method are effective and practical.展开更多
Maintenance optimization of periodic replacement for mono-unit production system is a widely discussed topic.In practice,the replacement for a parallel production system with multi-unit served by one repairman is univ...Maintenance optimization of periodic replacement for mono-unit production system is a widely discussed topic.In practice,the replacement for a parallel production system with multi-unit served by one repairman is universal.The replacement action is often implemented in a maintenance window at random,although the replacement period appears as a quasi-periodic event.To optimize these maintenance policies,this study analyzes a bivariate quasi-periodic replacement policy (T,W) for a two-unit parallel production system with a maintenance window and one repairman.One unit of the system is replaced when either a failure occurs or a replacement plan comes in the maintenance window,whichever comes first.If one of the two units is in the replacement,the other may continue operating or waiting until the replacement is completed.An optimal replacement window [T*,T* + W*] can be obtained by jointly considering the system's long-running cost rate and the availability using the genetic algorithm.This study also introduces three examples of the production system with different types of units to illustrate the proposed policy.展开更多
文摘For improving the method of finding maintenance windows under uncertain parameters, an algorithm of maintenance window under uncertainties is presented using interval analysis and sensitivity analysis. Age replacement model is selected to demonstrate how to use this new algorithm. Considered the uncertainties, the optimal maintenance interval of preventive maintenance is not only a single value, but a possible range. The requirement from maintenance engineers is also considered, the maintenance window is made as a symmetrical interval format, like(100 ± 10) day. Comparing with the methods using in the literatures, the new algorithm is without requirement of distribution assumption of uncertain parameter values and computer simulation.
基金supported by the National Natural Science Foundation of China (Project Nos.61273242,61403317)Science and Technology Plan of Sichuan province (Project No.2017015)Service Science and Innovation Key Laboratory of Sichuan Province (KL1701)
文摘The maintenance window scheme(MWS) is one of the most important railway transportation organizational plans and plays an important role in ensuring railway operational safety. However, MWS setting is a very complicated process, and most countries currently do so with the help of a computer-aided decision system. In general, a decision system can generate multiple alternatives for MWS within an acceptable time. Therefore, how to choose the best option from the alternatives is a vital decision. This paper presents a novel framework for MWS evaluation based on the Chinese railway system. Specifically, the requirements of each department related to MWS setting are analysed, and we construct an evaluation indicator system for MWS based on the preferences of different departments. Then, we apply the fuzzy soft set theory to MWS evaluation, a method that not only effectively deals with evaluation of uncertain information, but also gives flexibility for experts to input their subjective judgment.Additionally, using the ‘‘AND’’ operation of soft set theory allows combing evaluation information from multiple evaluators to give comprehensive results. Finally, a case study illustrates the proposed framework, showing that the proposed evaluation indicator system and evaluation method are effective and practical.
基金the National Natural Science Foundation of China(No.71561016)the China Postdoctoral Science Foundation(Nos.2017M613297XB , 2019T120964)。
文摘Maintenance optimization of periodic replacement for mono-unit production system is a widely discussed topic.In practice,the replacement for a parallel production system with multi-unit served by one repairman is universal.The replacement action is often implemented in a maintenance window at random,although the replacement period appears as a quasi-periodic event.To optimize these maintenance policies,this study analyzes a bivariate quasi-periodic replacement policy (T,W) for a two-unit parallel production system with a maintenance window and one repairman.One unit of the system is replaced when either a failure occurs or a replacement plan comes in the maintenance window,whichever comes first.If one of the two units is in the replacement,the other may continue operating or waiting until the replacement is completed.An optimal replacement window [T*,T* + W*] can be obtained by jointly considering the system's long-running cost rate and the availability using the genetic algorithm.This study also introduces three examples of the production system with different types of units to illustrate the proposed policy.
