Statistical problem‐solving teams: A case study in a global manufacturing organization in the automotive industry

Author:

Barsalou Matthew1ORCID,Perkin Robert1

Affiliation:

1. QPLUS Bahrain

Abstract

AbstractOrganizations are confronted with quality failures that must be addressed. Often, statistical methods can be helpful, but the organization lacks an internal statistician. This paper explores the use of a statistical problem‐solving team using Six Sigma professionals as problem‐solving team leaders, trainers, and coaches. A case study methodology is used. The actions and events from the implementation of a statistical problem‐solving team in a global manufacturing organization in the automotive industry through the first decade after implementation are described. Statistical problem‐solving bridges the gap between engineer and statistician using engineers trained to awareness‐level knowledge of statistics and supported by Six Sigma Master Black Belts. The statistical problem‐solving team members need to be highly trained in the three pillars of statistical problem‐solving: Key statistical concepts, key statistical analysis, and the key test method as well as a solid foundation in quality tools. This paper provides a unique view of a global problem‐solving team using both Six Sigma tools and methods and the 8D process as a problem‐solving methodology.

Publisher

Wiley

Subject

Management Science and Operations Research,Safety, Risk, Reliability and Quality

Reference44 articles.

1. Systematic problem-solving and its antecedents: a synthesis of the literature

2. The value of quality improvements

3. Cornerstone root causes through the analysis of the Ishikawa diagram, is it possible to find them? A first research approach;Suárez‐Barraza MF;Int J Qual Serv Sci,2019

4. Application of root cause analysis in improvement of product quality and productivity;Mahto D;J Ind Eng Manag,2008

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The ENBIS‐22 quality and reliability engineering international special issue;Quality and Reliability Engineering International;2023-12-17

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3