Duaa Alrufaihi, Audrey Fernandes, Bhavya Gangar Jaysukh, Pauline Goldery, R. Kaur, Samuler Tirado Alvarez, Daniel Vazquez Navarro, K. Salonitis
{"title":"Methodology to Identify and Quantify Sources of Process Scrap on Shop Floor","authors":"Duaa Alrufaihi, Audrey Fernandes, Bhavya Gangar Jaysukh, Pauline Goldery, R. Kaur, Samuler Tirado Alvarez, Daniel Vazquez Navarro, K. Salonitis","doi":"10.2139/ssrn.3718046","DOIUrl":null,"url":null,"abstract":"Poor quality costs are the total financial losses caused by the products or services not being perfect. Process scrap is a major contributing factor to these losses. Identification of different sources of scrap and the resulting costs is paramount for Continuous Improvement. Furthermore, quantification of this scrap and how the data can be visualised will facilitate decision making by upper management. For this, a methodology that acts as a guide will prove to be of great use in the analysis of scrap generation in any manufacturing plant. In the case study presented, a comprehensive list of the possible sources was made. However, only those which were responsible for a major part of the cost and of great concern were shortlisted. Once identified, several measurement systems were proposed to accurately quantify the resultant scrap. This was then followed by data visualisation using a dashboard that gave a weekly update on the levels of scrap generated.","PeriodicalId":10639,"journal":{"name":"Computational Materials Science eJournal","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Materials Science eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3718046","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
Poor quality costs are the total financial losses caused by the products or services not being perfect. Process scrap is a major contributing factor to these losses. Identification of different sources of scrap and the resulting costs is paramount for Continuous Improvement. Furthermore, quantification of this scrap and how the data can be visualised will facilitate decision making by upper management. For this, a methodology that acts as a guide will prove to be of great use in the analysis of scrap generation in any manufacturing plant. In the case study presented, a comprehensive list of the possible sources was made. However, only those which were responsible for a major part of the cost and of great concern were shortlisted. Once identified, several measurement systems were proposed to accurately quantify the resultant scrap. This was then followed by data visualisation using a dashboard that gave a weekly update on the levels of scrap generated.