六西格玛DMAIC在轴承部件制造行业的流程改进:一个案例研究

Q3 Engineering

International Journal of Industrial and Systems Engineering Pub Date : 2023-01-01 DOI:10.1504/ijise.2023.134717

Sandeep Kumar Bhaskar, Manoj Kumar Sain, Manu Augustine, Praveen Saraswat, Brij Mohan Sharma

{"title":"六西格玛DMAIC在轴承部件制造行业的流程改进:一个案例研究","authors":"Sandeep Kumar Bhaskar, Manoj Kumar Sain, Manu Augustine, Praveen Saraswat, Brij Mohan Sharma","doi":"10.1504/ijise.2023.134717","DOIUrl":null,"url":null,"abstract":"Bearing parts manufacturing process is highly crucial in maintaining the quality of final product. This paper elaborates the use of the Six Sigma DMAIC approach to minimise variation in dimensions of inner and outer races of ball bearings for enhancing process quality in a manufacturing firm. In various phases of DMAIC, Six Sigma quality improvement tools like voice of customers and employee, statistical process control, control charts, process capability charts, customer/employee survey, and fishbone diagram were used. MINITAB18.0 software was used for data analysis. The results revealed that the adoption of the Six Sigma DMAIC approach significantly improved the process quality. Sigma level was improved from 2.5 to 3.8; defects per million opportunities were reduced from 0.632% to 0.023% and process variation was reduced from ±5 to ±3 and was well within target limits.","PeriodicalId":35142,"journal":{"name":"International Journal of Industrial and Systems Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Process improvement using Six Sigma DMAIC in the bearing component manufacturing industry: a case study\",\"authors\":\"Sandeep Kumar Bhaskar, Manoj Kumar Sain, Manu Augustine, Praveen Saraswat, Brij Mohan Sharma\",\"doi\":\"10.1504/ijise.2023.134717\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bearing parts manufacturing process is highly crucial in maintaining the quality of final product. This paper elaborates the use of the Six Sigma DMAIC approach to minimise variation in dimensions of inner and outer races of ball bearings for enhancing process quality in a manufacturing firm. In various phases of DMAIC, Six Sigma quality improvement tools like voice of customers and employee, statistical process control, control charts, process capability charts, customer/employee survey, and fishbone diagram were used. MINITAB18.0 software was used for data analysis. The results revealed that the adoption of the Six Sigma DMAIC approach significantly improved the process quality. Sigma level was improved from 2.5 to 3.8; defects per million opportunities were reduced from 0.632% to 0.023% and process variation was reduced from ±5 to ±3 and was well within target limits.\",\"PeriodicalId\":35142,\"journal\":{\"name\":\"International Journal of Industrial and Systems Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Industrial and Systems Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijise.2023.134717\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Industrial and Systems Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijise.2023.134717","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}

引用次数: 0

摘要

轴承零件的制造过程对保持最终产品的质量至关重要。本文详细阐述了六西格玛DMAIC方法的使用，以尽量减少滚珠轴承内圈和外圈尺寸的变化，以提高制造公司的工艺质量。在DMAIC的各个阶段，使用了客户和员工的声音、统计过程控制、控制图、过程能力图、客户/员工调查和鱼骨图等六西格玛质量改进工具。采用MINITAB18.0软件进行数据分析。结果表明，采用六西格玛DMAIC方法显著提高了过程质量。Sigma水平由2.5提高到3.8;每百万机会的缺陷从0.632%减少到0.023%，过程变化从±5减少到±3，并且完全在目标范围内。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Process improvement using Six Sigma DMAIC in the bearing component manufacturing industry: a case study

Bearing parts manufacturing process is highly crucial in maintaining the quality of final product. This paper elaborates the use of the Six Sigma DMAIC approach to minimise variation in dimensions of inner and outer races of ball bearings for enhancing process quality in a manufacturing firm. In various phases of DMAIC, Six Sigma quality improvement tools like voice of customers and employee, statistical process control, control charts, process capability charts, customer/employee survey, and fishbone diagram were used. MINITAB18.0 software was used for data analysis. The results revealed that the adoption of the Six Sigma DMAIC approach significantly improved the process quality. Sigma level was improved from 2.5 to 3.8; defects per million opportunities were reduced from 0.632% to 0.023% and process variation was reduced from ±5 to ±3 and was well within target limits.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

International Journal of Industrial and Systems Engineering Engineering-Industrial and Manufacturing Engineering

CiteScore

1.70

自引率

0.00%

发文量

期刊介绍： In today"s global economy, the most successful engineering managers rely on a combination of technical skills and business principles. Industrial and systems engineering (ISE) aims at imparting fundamental knowledge to develop the ability to address complex industrial issues, emphasising on how to design, run, control and optimise production systems. The field of industrial engineering embraces a broad spectrum of technical activities including the classical techniques of work methods, production and facilities planning, quality control and safety. It also embraces the fields of human factors, operations research, manufacturing systems, and organisation and management systems.