New Approach for Quality Function Deployment Based on Linguistic Distribution Assessments and CRITIC Method
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| Udgivet i: | Mathematics vol. 13, no. 2 (2025), p. 240 |
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MDPI AG
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| Online adgang: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2227-7390 | ||
| 024 | 7 | |a 10.3390/math13020240 |2 doi | |
| 035 | |a 3159525253 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231533 |2 nlm | ||
| 100 | 1 | |a Ling-Xiang, Mao |u School of Economics and Management, Anhui Normal University, Wuhu 241002, China | |
| 245 | 1 | |a New Approach for Quality Function Deployment Based on Linguistic Distribution Assessments and CRITIC Method | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Quality function deployment (QFD) is a customer-oriented quality management tool used to maximize customer satisfaction by considering the correlations between customer requirements and engineering characteristics. However, the conventional QFD method exhibits some shortcomings when used in real situations, especially in terms of correlation evaluation and engineering characteristic ranking. Therefore, the objective of this study is to propose a new QFD approach based on linguistic distribution assessments and the CRiteria Importance Through Inter-Criteria Correlation (CRITIC) method to improve the effectiveness of the traditional QFD. Specifically, linguistic distribution assessments are utilized to describe the relationships between customer requirements and engineering characteristics. The CRITIC method is extended and used to determine the ranking orders of the engineering characteristics identified in QFD. To demonstrate the feasibility and practicality of the proposed QFD, a case example regarding the performance management system’s development is presented. It is shown that the QFD approach proposed in this paper can not only represent experts’ uncertain linguistic relationship evaluations flexibly but also determine more reliable importance rankings of engineering characteristics in production planning. | |
| 653 | |a Linguistics | ||
| 653 | |a Quality management | ||
| 653 | |a Assessments | ||
| 653 | |a Performance evaluation | ||
| 653 | |a Fuzzy sets | ||
| 653 | |a Correlation | ||
| 653 | |a Social network analysis | ||
| 653 | |a Decision making | ||
| 653 | |a Social networks | ||
| 653 | |a Criteria | ||
| 653 | |a Preferences | ||
| 653 | |a Methods | ||
| 653 | |a Manufacturing | ||
| 653 | |a Ranking | ||
| 653 | |a Quality function deployment | ||
| 653 | |a Performance management | ||
| 653 | |a Production planning | ||
| 653 | |a Product design | ||
| 653 | |a Product development | ||
| 653 | |a Case studies | ||
| 653 | |a Ratings & rankings | ||
| 653 | |a Quality | ||
| 653 | |a Engineering | ||
| 653 | |a Deployment | ||
| 653 | |a Client satisfaction | ||
| 653 | |a Customer satisfaction | ||
| 653 | |a Feasibility | ||
| 653 | |a Distribution | ||
| 653 | |a Satisfaction | ||
| 653 | |a Evaluation | ||
| 700 | 1 | |a Lan, Jing |u School of Economics and Management, Anhui Normal University, Wuhu 241002, China | |
| 700 | 1 | |a Chen, Anqi |u School of Performance and Cultural Industries, University of Leeds, Woodhouse LS2 9JT, UK | |
| 700 | 1 | |a Shi, Hua |u School of Materials, Shanghai Dianji University, Shanghai 201306, China | |
| 700 | 1 | |a Hu-Chen, Liu |u School of Economics and Management, Tongji University, Shanghai 200092, China | |
| 773 | 0 | |t Mathematics |g vol. 13, no. 2 (2025), p. 240 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3159525253/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3159525253/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3159525253/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |