A proposed satisfaction function model to optimize process performance with multiple quality responses in the Taguchi method

Author:

Al-Refaie Abbas1

Affiliation:

1. Department of Industrial Engineering, The University of Jordan, Amman, Jordan

Abstract

The Taguchi method has been found effective for optimizing a single quality response. In reality, customers are concerned about multiple quality responses of a product. Although several approaches have been proposed to deal with this issue, however they ignored engineers’ satisfaction regarding process factor settings. This research, therefore, proposes an approach for optimizing multiple responses in the application of the Taguchi method. The mathematical relationships between each response quality and process factors are first formulated. Then, a proper satisfaction function is selected to represent each response and process factor. A complete optimization model is developed. Three case studies are provided for illustration; in all of which the proposed approach provides the largest improvement percentages while considering process engineers’ satisfaction about process factors. Compared to previous approaches in literature, such as gray analysis and fuzzy-gray analysis, the proposed approach provides optimal solution within factor setting ranges, relies on mathematical relationships between response and process factors, and considers engineers’ preference regarding process factor settings. Definitely, the proposed approach shall provide practitioners a great assistance in optimizing performance with multiple responses while considering their preferences about responses as well as process factor settings.

Publisher

SAGE Publications

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Cited by 13 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. Experimental study and multi-objective optimization of process parameters during turning of 100Cr6 using C-type advanced coated tools;Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science;2021-08-30

2. Experimental investigation and optimization of RMDTM welding parameters for ASTM A387 grade 11 steel;Materials and Manufacturing Processes;2020-12-23

3. A unique mathematical programming algorithm for performance optimization of organizational indicators in manufacturing sector;Journal of Industrial and Production Engineering;2019-10-03

4. A fuzzy goal programming-regression approach to optimize process performance of multiple responses under uncertainty;International Journal of Management Science and Engineering Management;2018-07-16

5. Using mixed goal programming to optimize performance of extrusion process for multiple responses of irrigation pipes;Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering;2018-06-12

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