Hao Liu, Qianchuan Zhao, Weihua Cao, N. Huang, Xiang Zhao
{"title":"基于仿真的典型焊接车间能耗评估与优化","authors":"Hao Liu, Qianchuan Zhao, Weihua Cao, N. Huang, Xiang Zhao","doi":"10.1109/CASE.2011.6042482","DOIUrl":null,"url":null,"abstract":"Manufacturing facility's energy consumption depends on series of factors such as machines and equipment used for production, manufacturing procedures, building design, outside weather conditions and indoor environmental requirements, where many of them are stochastic in nature, thus makes energy consumption optimization of manufacturing facility a very difficult and challenging problem. It is almost impossible to solve the problem via an analytical study, while experimental studies usually are very costly and time consuming. To overcome these difficulties, this paper proposes a simulation based approach to evaluate and optimize the energy consumption of a manufacturing facility, and we use a typical welding shop as an example. To achieve long term low energy consumption, we face a two-level optimization problem: the building design and daily production scheduling. In the proposed approach, we use EnergyPlus for integrated energy usage estimation and we apply Ordinal Optimization (OO) method and Genetic Algorithms (GA) for optimization of building design and production scheduling, respectively. Numerical examples and results are provided. The optimization concept and the modeling framework could be used for manufacturing facility design and production scheduling to minimize the total energy consumption while maintaining production throughput.","PeriodicalId":236208,"journal":{"name":"2011 IEEE International Conference on Automation Science and Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Simulation based evaluation and optimization for energy consumption of a typical welding shop\",\"authors\":\"Hao Liu, Qianchuan Zhao, Weihua Cao, N. Huang, Xiang Zhao\",\"doi\":\"10.1109/CASE.2011.6042482\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Manufacturing facility's energy consumption depends on series of factors such as machines and equipment used for production, manufacturing procedures, building design, outside weather conditions and indoor environmental requirements, where many of them are stochastic in nature, thus makes energy consumption optimization of manufacturing facility a very difficult and challenging problem. It is almost impossible to solve the problem via an analytical study, while experimental studies usually are very costly and time consuming. To overcome these difficulties, this paper proposes a simulation based approach to evaluate and optimize the energy consumption of a manufacturing facility, and we use a typical welding shop as an example. To achieve long term low energy consumption, we face a two-level optimization problem: the building design and daily production scheduling. In the proposed approach, we use EnergyPlus for integrated energy usage estimation and we apply Ordinal Optimization (OO) method and Genetic Algorithms (GA) for optimization of building design and production scheduling, respectively. Numerical examples and results are provided. The optimization concept and the modeling framework could be used for manufacturing facility design and production scheduling to minimize the total energy consumption while maintaining production throughput.\",\"PeriodicalId\":236208,\"journal\":{\"name\":\"2011 IEEE International Conference on Automation Science and Engineering\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Conference on Automation Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CASE.2011.6042482\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Automation Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CASE.2011.6042482","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simulation based evaluation and optimization for energy consumption of a typical welding shop
Manufacturing facility's energy consumption depends on series of factors such as machines and equipment used for production, manufacturing procedures, building design, outside weather conditions and indoor environmental requirements, where many of them are stochastic in nature, thus makes energy consumption optimization of manufacturing facility a very difficult and challenging problem. It is almost impossible to solve the problem via an analytical study, while experimental studies usually are very costly and time consuming. To overcome these difficulties, this paper proposes a simulation based approach to evaluate and optimize the energy consumption of a manufacturing facility, and we use a typical welding shop as an example. To achieve long term low energy consumption, we face a two-level optimization problem: the building design and daily production scheduling. In the proposed approach, we use EnergyPlus for integrated energy usage estimation and we apply Ordinal Optimization (OO) method and Genetic Algorithms (GA) for optimization of building design and production scheduling, respectively. Numerical examples and results are provided. The optimization concept and the modeling framework could be used for manufacturing facility design and production scheduling to minimize the total energy consumption while maintaining production throughput.