{"title":"使用六西格玛的Dmaic方法最小化玻璃容器瓶生产的低质量成本:一个瓶子和玻璃股份公司的案例研究","authors":"Besufekad Legesse, Sisay Geremew","doi":"10.11648/j.ie.20210501.12","DOIUrl":null,"url":null,"abstract":"Even if many tools are available to reduce defect, six sigma’s DMAIC model is one of a tool which significantly reduce defect if it is applied with appropriate methodology. In this work defect reduction is achieved using DMAIC model as a means. At the define phase major product types and defects are crafted and identified by using brainstorming, supplier-input-process-output-customer diagram, Pareto Diagram and failure mode and effect analysis. So that poor bead diameter and uneven glass distribution have been selected from the glass making processes. At the measuring phase data has taken and observed to display how the process behaves. Control charts, capability analysis and six pack capability analysis are applied to understand the process condition. Based on the data obtained from the preceding phase analysis undertaken using Fishbone diagram. The graph illustrates the root causes that are in need to improve. After the analysis phase identified the root causes i.e. process parameters, the improvement phase has held by using Taguchi technique to optimize the process parameters. The Taguchi analysis identified the main factors which determine the processes output factors. After the optimum value is decided the result is collected to check its effectiveness. these improvements decreased defects per million opportunities (DPMO) from 149,997.8 to 50,000 and reduced poor quality cost from ETB 429,540.3 to ETB 143,178 per day and the result showed that defect has reduced by 30% compared with the previous output.","PeriodicalId":13667,"journal":{"name":"Industrial & Engineering Chemistry","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Minimizing Costs of Poor Quality for Glass Container Bottles Production Using Six Sigma’s Dmaic Methodology: A Case Study in a Bottle and Glass Share Company\",\"authors\":\"Besufekad Legesse, Sisay Geremew\",\"doi\":\"10.11648/j.ie.20210501.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Even if many tools are available to reduce defect, six sigma’s DMAIC model is one of a tool which significantly reduce defect if it is applied with appropriate methodology. In this work defect reduction is achieved using DMAIC model as a means. At the define phase major product types and defects are crafted and identified by using brainstorming, supplier-input-process-output-customer diagram, Pareto Diagram and failure mode and effect analysis. So that poor bead diameter and uneven glass distribution have been selected from the glass making processes. At the measuring phase data has taken and observed to display how the process behaves. Control charts, capability analysis and six pack capability analysis are applied to understand the process condition. Based on the data obtained from the preceding phase analysis undertaken using Fishbone diagram. The graph illustrates the root causes that are in need to improve. After the analysis phase identified the root causes i.e. process parameters, the improvement phase has held by using Taguchi technique to optimize the process parameters. The Taguchi analysis identified the main factors which determine the processes output factors. After the optimum value is decided the result is collected to check its effectiveness. these improvements decreased defects per million opportunities (DPMO) from 149,997.8 to 50,000 and reduced poor quality cost from ETB 429,540.3 to ETB 143,178 per day and the result showed that defect has reduced by 30% compared with the previous output.\",\"PeriodicalId\":13667,\"journal\":{\"name\":\"Industrial & Engineering Chemistry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Industrial & Engineering Chemistry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11648/j.ie.20210501.12\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Industrial & Engineering Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11648/j.ie.20210501.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Minimizing Costs of Poor Quality for Glass Container Bottles Production Using Six Sigma’s Dmaic Methodology: A Case Study in a Bottle and Glass Share Company
Even if many tools are available to reduce defect, six sigma’s DMAIC model is one of a tool which significantly reduce defect if it is applied with appropriate methodology. In this work defect reduction is achieved using DMAIC model as a means. At the define phase major product types and defects are crafted and identified by using brainstorming, supplier-input-process-output-customer diagram, Pareto Diagram and failure mode and effect analysis. So that poor bead diameter and uneven glass distribution have been selected from the glass making processes. At the measuring phase data has taken and observed to display how the process behaves. Control charts, capability analysis and six pack capability analysis are applied to understand the process condition. Based on the data obtained from the preceding phase analysis undertaken using Fishbone diagram. The graph illustrates the root causes that are in need to improve. After the analysis phase identified the root causes i.e. process parameters, the improvement phase has held by using Taguchi technique to optimize the process parameters. The Taguchi analysis identified the main factors which determine the processes output factors. After the optimum value is decided the result is collected to check its effectiveness. these improvements decreased defects per million opportunities (DPMO) from 149,997.8 to 50,000 and reduced poor quality cost from ETB 429,540.3 to ETB 143,178 per day and the result showed that defect has reduced by 30% compared with the previous output.