K. Becker, S. Voges, P. Fruehauf, M. Heimann, S. Nerreter, R. Blank, M. Erdmann, S. Gottwald, A. Hofmeister, M. Hesse, M. Thies, S. Mehrafsun, R. Fust, E. Beck, J. Pawlikowski, B. Schröder, C. Voight, T. Braun, M. Schneider-Ramelow
{"title":"Implementation of Trusted Manufacturing & AI-based process optimization into microelectronic manufacturing research environments","authors":"K. Becker, S. Voges, P. Fruehauf, M. Heimann, S. Nerreter, R. Blank, M. Erdmann, S. Gottwald, A. Hofmeister, M. Hesse, M. Thies, S. Mehrafsun, R. Fust, E. Beck, J. Pawlikowski, B. Schröder, C. Voight, T. Braun, M. Schneider-Ramelow","doi":"10.4071/1085-8024-2021.1","DOIUrl":null,"url":null,"abstract":"\n Digitization is one of the hot topics in all Industry 4.0 efforts that are currently discussed. Often the focus is on digitization of business processes with a financial/organizational perspective on manufacturing, so the tools are adapting to enterprise resource planning [ERP] and manufacturing execution system [MES] rather than on actual manufacturing issues on the shop floor. Within the SiEvEI 4.0 project, a research consortium from the area of electronics manufacturing is working on digitization for a manufacturing scenario where high value electronic goods are built in a distributed manufacturing environment. The key research topics addressed are the implementation of a Chain of Trust [CoT] for such a distributed manufacturing, i.e. and the application of artificial intelligence/machine learning to analyze and eventually optimize manufacturing processes.\n The paper will introduce the concept of both COT and AI-based process analysis that will later on transferred into a microelectronics production environment. Two reference processes are targeted, SMD assembly using fully automated manufacturing equipment and Solder Ball Application using a high-mix/low volume concept.\n As a result, the paper presents a concept of how to digitize manufacturing processes and use this digital description of a process combination to make a distributed manufacturing flow safe and increase product/process quality.","PeriodicalId":14363,"journal":{"name":"International Symposium on Microelectronics","volume":"92 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Microelectronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4071/1085-8024-2021.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Digitization is one of the hot topics in all Industry 4.0 efforts that are currently discussed. Often the focus is on digitization of business processes with a financial/organizational perspective on manufacturing, so the tools are adapting to enterprise resource planning [ERP] and manufacturing execution system [MES] rather than on actual manufacturing issues on the shop floor. Within the SiEvEI 4.0 project, a research consortium from the area of electronics manufacturing is working on digitization for a manufacturing scenario where high value electronic goods are built in a distributed manufacturing environment. The key research topics addressed are the implementation of a Chain of Trust [CoT] for such a distributed manufacturing, i.e. and the application of artificial intelligence/machine learning to analyze and eventually optimize manufacturing processes.
The paper will introduce the concept of both COT and AI-based process analysis that will later on transferred into a microelectronics production environment. Two reference processes are targeted, SMD assembly using fully automated manufacturing equipment and Solder Ball Application using a high-mix/low volume concept.
As a result, the paper presents a concept of how to digitize manufacturing processes and use this digital description of a process combination to make a distributed manufacturing flow safe and increase product/process quality.