{"title":"AMHS Capability Assessment Based on Planned Product Mixes","authors":"Robert Schmaler, C. Hammel, C. Schubert","doi":"10.1109/ASMC49169.2020.9185350","DOIUrl":null,"url":null,"abstract":"Automated material handling systems (AMHS) in Semiconductor Fabrication Plants (Fabs) are crucial to achieve a high production throughput. When refurbishing an existing or planning a new Fab production plans are used to decide on the necessary tool park. But what about AMHS planning? To our knowledge no method exists, given an anticipated product mix, to reliably generate expected transport patterns including nonproductive transports. This paper summarizes a methodology based on a given product mix together with scheduling rules and AMHS characteristics to generate such transport patterns, including non-productive transports like test wafers and empty FOUPs, and subsequently a deep insight into actual AMHS capabilities and requirements in the planning phase. Results will be reviewed via static simulation to identify possible AMHS bottlenecks as early as possible.","PeriodicalId":6771,"journal":{"name":"2020 31st Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","volume":"66 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 31st Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASMC49169.2020.9185350","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Automated material handling systems (AMHS) in Semiconductor Fabrication Plants (Fabs) are crucial to achieve a high production throughput. When refurbishing an existing or planning a new Fab production plans are used to decide on the necessary tool park. But what about AMHS planning? To our knowledge no method exists, given an anticipated product mix, to reliably generate expected transport patterns including nonproductive transports. This paper summarizes a methodology based on a given product mix together with scheduling rules and AMHS characteristics to generate such transport patterns, including non-productive transports like test wafers and empty FOUPs, and subsequently a deep insight into actual AMHS capabilities and requirements in the planning phase. Results will be reviewed via static simulation to identify possible AMHS bottlenecks as early as possible.