Christoffer Fink, Wilma Krutrök, O. Schelén, Ulf Bodin
{"title":"装配线装配中的布局规划——一种约束规划方法","authors":"Christoffer Fink, Wilma Krutrök, O. Schelén, Ulf Bodin","doi":"10.1109/ETFA45728.2021.9613695","DOIUrl":null,"url":null,"abstract":"In truck manufacturing, an assembly line is typically used to produce many models and variations of trucks in any desired order. Thus, stations are fed with specific sets of parts, known as kits, depending on what truck is next in line. This paper focuses on how to automate the layout planning for placing parts on a kitting wagon. Layout planning resembles the pallet loading problem, but differences include that there is no layering, there may be constraints on how each part can be placed (orientation) and there may be predefined layout hints suggesting positions. A layout planner based on constraint programming is presented. The objective is to facilitate a decision support loop where an engineer may add placement hints as constraints (e.g., for enhancing the workflow at assembly stations) and reuse placements from similar kits to provide recognition. The layout planner automatically generates layout proposals. Finally, it is the engineer that approves the layout plan. There may be many acceptable solutions that have different scores (i.e., levels of quality). We show some approaches to reduce the search space to improve performance. The evaluations show the score and time needed for finding results on some problem instances that are optimally solvable. In the general case, however, finding an optimal solution may be unnecessary or even intractable.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Layout planning in assembly line kitting - a constraint programming approach\",\"authors\":\"Christoffer Fink, Wilma Krutrök, O. Schelén, Ulf Bodin\",\"doi\":\"10.1109/ETFA45728.2021.9613695\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In truck manufacturing, an assembly line is typically used to produce many models and variations of trucks in any desired order. Thus, stations are fed with specific sets of parts, known as kits, depending on what truck is next in line. This paper focuses on how to automate the layout planning for placing parts on a kitting wagon. Layout planning resembles the pallet loading problem, but differences include that there is no layering, there may be constraints on how each part can be placed (orientation) and there may be predefined layout hints suggesting positions. A layout planner based on constraint programming is presented. The objective is to facilitate a decision support loop where an engineer may add placement hints as constraints (e.g., for enhancing the workflow at assembly stations) and reuse placements from similar kits to provide recognition. The layout planner automatically generates layout proposals. Finally, it is the engineer that approves the layout plan. There may be many acceptable solutions that have different scores (i.e., levels of quality). We show some approaches to reduce the search space to improve performance. The evaluations show the score and time needed for finding results on some problem instances that are optimally solvable. In the general case, however, finding an optimal solution may be unnecessary or even intractable.\",\"PeriodicalId\":312498,\"journal\":{\"name\":\"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ETFA45728.2021.9613695\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETFA45728.2021.9613695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Layout planning in assembly line kitting - a constraint programming approach
In truck manufacturing, an assembly line is typically used to produce many models and variations of trucks in any desired order. Thus, stations are fed with specific sets of parts, known as kits, depending on what truck is next in line. This paper focuses on how to automate the layout planning for placing parts on a kitting wagon. Layout planning resembles the pallet loading problem, but differences include that there is no layering, there may be constraints on how each part can be placed (orientation) and there may be predefined layout hints suggesting positions. A layout planner based on constraint programming is presented. The objective is to facilitate a decision support loop where an engineer may add placement hints as constraints (e.g., for enhancing the workflow at assembly stations) and reuse placements from similar kits to provide recognition. The layout planner automatically generates layout proposals. Finally, it is the engineer that approves the layout plan. There may be many acceptable solutions that have different scores (i.e., levels of quality). We show some approaches to reduce the search space to improve performance. The evaluations show the score and time needed for finding results on some problem instances that are optimally solvable. In the general case, however, finding an optimal solution may be unnecessary or even intractable.