Enhancement of Axle Bearing Quality in Sewing Machines Using Six Sigma

Author:

Huang C-F1,Chen K-S2,Sheu S-H13,Hsu T-S1

Affiliation:

1. Department of Industrial Management, National Taiwan University of Science and Technology, Taipei, Taiwan, Republic of China

2. Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung, Taiwan, Republic of China

3. Department of Statistics and Information Science, Providence University, Taichung County, Taiwan, Republic of China

Abstract

In today's world there is increasing emphasis on personal style and individuality, and hence a preference for semi-finished, customizable products over finished products. Consequently, sales of do-it-yourself products are increasing, including the high-quality equipment necessary to complete semi-finished goods. A representative example is the sewing machine; sewing machines must have high process yield to keep after-sales service costs low. In the current paper, a key component of sewing machines, the upper axle bearing, is used to present an implementation of Six Sigma via the measure-analyse-improve-control (MAIC) approach. Four bearing characteristics are identified as being critical to quality and are used to develop process capability indices for evaluating bearing quality. Then, a multi-characteristic product capability analysis chart (MPCAC) is used to identify and analyse the factors affecting bearing quality. Finally, the results of experiments and statistical tests using control charts to identify the optimum process levels are presented. The results show that the MAIC approach will help manufacturers and suppliers of sewing machines achieve Six Sigma quality.

Publisher

SAGE Publications

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Cited by 34 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

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