W. Hoover, David A. Guerra-Zubiaga, Jeremy Banta, Kevin Wandene, Kaleb Key, Germanico Gonzalez-Badillo
{"title":"Industry 4.0 Trends in Intelligent Manufacturing Automation Exploring Machine Learning","authors":"W. Hoover, David A. Guerra-Zubiaga, Jeremy Banta, Kevin Wandene, Kaleb Key, Germanico Gonzalez-Badillo","doi":"10.1115/imece2022-96092","DOIUrl":null,"url":null,"abstract":"\n Current trends indicate that the manufacturing industry is moving toward implementing Industry 4.0 concepts in search of improved adaptability, efficiency, sustainability, and advanced technological implementation. Some of these new technologies include virtual process simulation, automation, machine learning technologies, and the use of IIoT to innovate solutions.\n Researchers are focusing on ways to improve the rate and economy of implementing Industry 4.0 concepts in current manufacturing processes. This paper focuses on the implementation of a combination of specific industry 4.0 concepts in a lab environment. There will also be a case study where this research will be applied, and the results discussed. Digital Twins is also a proposed component of the research case study that is implemented using Siemens PLM Tecnomatix tool. Future work is to improve the efficiency of the manufacturing, pick-and-place operation using Deep Reinforcement learning.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"102 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 2B: Advanced Manufacturing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/imece2022-96092","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
Current trends indicate that the manufacturing industry is moving toward implementing Industry 4.0 concepts in search of improved adaptability, efficiency, sustainability, and advanced technological implementation. Some of these new technologies include virtual process simulation, automation, machine learning technologies, and the use of IIoT to innovate solutions.
Researchers are focusing on ways to improve the rate and economy of implementing Industry 4.0 concepts in current manufacturing processes. This paper focuses on the implementation of a combination of specific industry 4.0 concepts in a lab environment. There will also be a case study where this research will be applied, and the results discussed. Digital Twins is also a proposed component of the research case study that is implemented using Siemens PLM Tecnomatix tool. Future work is to improve the efficiency of the manufacturing, pick-and-place operation using Deep Reinforcement learning.