{"title":"A Scheduling Method for Reducing Energy Consumption of Machining Job Shops Considering the Flexible Process Plan","authors":"He Yan, Wang Lexiang, Li Yufeng, Wang Yulin","doi":"10.3901/JME.2016.19.168","DOIUrl":null,"url":null,"abstract":"Numerous studies indicated that amount of energy is consumed by machining job shops. Hence reducing the energy consumption of machining job shops is one of the strategies for sustainable manufacturing. The existing researches of scheduling method considering energy consumption for machining job shops focus on constant or partly flexible process plan, and the study considering multi flexibilities of process plan is scarce. A scheduling method for reducing energy consumption of machining job shops considering the flexible process plan is proposed which considers the influence that flexible process plan have on energy consumption. Based on the analysis of energy consumption characteristics of flexible process plan-oriented task scheduling, a mathematical model of task scheduling problem is formulated. The optimal objects of the model include total energy consumption of task, makespan and workload of machine. The Q-learning algorithm is improved to find the Pareto optimal solution of the multi-objective mathematical model. Finally, the experimental results indicate that the proposed model has energy saving potential and improved Q-learning algorithm is feasible.","PeriodicalId":16166,"journal":{"name":"Journal of Mechanical Engineering and Sciences","volume":"7 1","pages":"179"},"PeriodicalIF":1.2000,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mechanical Engineering and Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3901/JME.2016.19.168","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 6
Abstract
Numerous studies indicated that amount of energy is consumed by machining job shops. Hence reducing the energy consumption of machining job shops is one of the strategies for sustainable manufacturing. The existing researches of scheduling method considering energy consumption for machining job shops focus on constant or partly flexible process plan, and the study considering multi flexibilities of process plan is scarce. A scheduling method for reducing energy consumption of machining job shops considering the flexible process plan is proposed which considers the influence that flexible process plan have on energy consumption. Based on the analysis of energy consumption characteristics of flexible process plan-oriented task scheduling, a mathematical model of task scheduling problem is formulated. The optimal objects of the model include total energy consumption of task, makespan and workload of machine. The Q-learning algorithm is improved to find the Pareto optimal solution of the multi-objective mathematical model. Finally, the experimental results indicate that the proposed model has energy saving potential and improved Q-learning algorithm is feasible.
期刊介绍:
The Journal of Mechanical Engineering & Sciences "JMES" (ISSN (Print): 2289-4659; e-ISSN: 2231-8380) is an open access peer-review journal (Indexed by Emerging Source Citation Index (ESCI), WOS; SCOPUS Index (Elsevier); EBSCOhost; Index Copernicus; Ulrichsweb, DOAJ, Google Scholar) which publishes original and review articles that advance the understanding of both the fundamentals of engineering science and its application to the solution of challenges and problems in mechanical engineering systems, machines and components. It is particularly concerned with the demonstration of engineering science solutions to specific industrial problems. Original contributions providing insight into the use of analytical, computational modeling, structural mechanics, metal forming, behavior and application of advanced materials, impact mechanics, strain localization and other effects of nonlinearity, fluid mechanics, robotics, tribology, thermodynamics, and materials processing generally from the core of the journal contents are encouraged. Only original, innovative and novel papers will be considered for publication in the JMES. The authors are required to confirm that their paper has not been submitted to any other journal in English or any other language. The JMES welcome contributions from all who wishes to report on new developments and latest findings in mechanical engineering.