Y Tina Lee, Senthilkumaran Kumaraguru, Sanjay Jain, Stefanie Robinson, Moneer Helu, Qais Y Hatim, Sudarsan Rachuri, David Dornfeld, Christopher J Saldana, Soundar Kumara
{"title":"A Classification Scheme for Smart Manufacturing Systems' Performance Metrics.","authors":"Y Tina Lee, Senthilkumaran Kumaraguru, Sanjay Jain, Stefanie Robinson, Moneer Helu, Qais Y Hatim, Sudarsan Rachuri, David Dornfeld, Christopher J Saldana, Soundar Kumara","doi":"10.1520/SSMS20160012","DOIUrl":null,"url":null,"abstract":"<p><p>This paper proposes a classification scheme for performance metrics for smart manufacturing systems. The discussion focuses on three such metrics: agility, asset utilization, and sustainability. For each of these metrics, we discuss classification themes, which we then use to develop a generalized classification scheme. In addition to the themes, we discuss a conceptual model that may form the basis for the information necessary for performance evaluations. Finally, we present future challenges in developing robust, performance-measurement systems for real-time, data-intensive enterprises.</p>","PeriodicalId":51957,"journal":{"name":"Smart and Sustainable Manufacturing Systems","volume":"1 1","pages":"52-74"},"PeriodicalIF":0.8000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1520/SSMS20160012","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart and Sustainable Manufacturing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1520/SSMS20160012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2016/12/12 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 27
Abstract
This paper proposes a classification scheme for performance metrics for smart manufacturing systems. The discussion focuses on three such metrics: agility, asset utilization, and sustainability. For each of these metrics, we discuss classification themes, which we then use to develop a generalized classification scheme. In addition to the themes, we discuss a conceptual model that may form the basis for the information necessary for performance evaluations. Finally, we present future challenges in developing robust, performance-measurement systems for real-time, data-intensive enterprises.