{"title":"基于遗传算法的多单元系统维修决策优化","authors":"Pravin P. Tambe","doi":"10.1109/ICIPTM57143.2023.10118331","DOIUrl":null,"url":null,"abstract":"Maintenance of equipment is one of the most important operational issues that can be focused on to improve productivity. Maintenance cost includes the cost of preventive and corrective maintenance, which may vary depending on how often maintenance is scheduled. This paper describes the maintenance modeling of a system with multiple parts. The objective is to get a minimum-cost decision that meets the machine availability criteria and to be finished within the time allowed for maintenance. A Genetic Algorithm (GA) is used for the decision parameters optimization. The algorithm procedure leads to a maintenance decision; repair, replacement, or no action for system parts. A case study shows how the model can be used in real life.","PeriodicalId":178817,"journal":{"name":"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization based on Genetic Algorithm for maintenance decision of multi-unit system\",\"authors\":\"Pravin P. Tambe\",\"doi\":\"10.1109/ICIPTM57143.2023.10118331\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Maintenance of equipment is one of the most important operational issues that can be focused on to improve productivity. Maintenance cost includes the cost of preventive and corrective maintenance, which may vary depending on how often maintenance is scheduled. This paper describes the maintenance modeling of a system with multiple parts. The objective is to get a minimum-cost decision that meets the machine availability criteria and to be finished within the time allowed for maintenance. A Genetic Algorithm (GA) is used for the decision parameters optimization. The algorithm procedure leads to a maintenance decision; repair, replacement, or no action for system parts. A case study shows how the model can be used in real life.\",\"PeriodicalId\":178817,\"journal\":{\"name\":\"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIPTM57143.2023.10118331\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIPTM57143.2023.10118331","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization based on Genetic Algorithm for maintenance decision of multi-unit system
Maintenance of equipment is one of the most important operational issues that can be focused on to improve productivity. Maintenance cost includes the cost of preventive and corrective maintenance, which may vary depending on how often maintenance is scheduled. This paper describes the maintenance modeling of a system with multiple parts. The objective is to get a minimum-cost decision that meets the machine availability criteria and to be finished within the time allowed for maintenance. A Genetic Algorithm (GA) is used for the decision parameters optimization. The algorithm procedure leads to a maintenance decision; repair, replacement, or no action for system parts. A case study shows how the model can be used in real life.