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Quality-Based Supplier Selection Model for Products with Multiple Quality Characteristics

Author

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  • Kuen-Suan Chen

    (Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 411030, Taiwan
    Department of Business Administration, Asia University, Taichung 413305, Taiwan
    Department of Business Administration, Chaoyang University of Technology, Taichung 413310, Taiwan)

  • Ming-Chieh Huang

    (Department of Industrial Education and Technology, National Changhua University of Education, Changhua 50074, Taiwan)

  • Chun-Min Yu

    (Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 411030, Taiwan)

  • Hsuan-Yu Chen

    (Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan)

Abstract

The concept of Industry 4.0 was first proposed by the German government in 2011. As the Internet of Things (IoT) becomes more prevalent and big data analysis technology becomes more mature, it is beneficial for the manufacturing industry to integrate and apply the related technologies to pursue the goal of smart manufacturing. Taiwan’s machine tool industry and downstream machine-tool purchasers, who are scattered around the world, have formed a machine-tool industry chain. To help the machine-tool industry and the suppliers of important components boost their process capabilities, ensure the final product quality of machine tools and improve the process capabilities of the entire industry chain, this study used radar charts to present the statistical testing information of the process capabilities of all quality characteristics, so that managers could have more complete information when evaluating and selecting appropriate suppliers. As noted in many studies, improving product quality and availability can reduce not only the rate of reworking and scrappage during production but also the frequency of maintenance or replacement of components after purchase. As a result, the loss of costs caused by reworking, scrappage, and maintenance can be diminished, carbon emissions can be lowered, and environmental pollution can be reduced as well, which will help to achieve sustainable operation in the entire machine tool industry chain.

Suggested Citation

  • Kuen-Suan Chen & Ming-Chieh Huang & Chun-Min Yu & Hsuan-Yu Chen, 2022. "Quality-Based Supplier Selection Model for Products with Multiple Quality Characteristics," Sustainability, MDPI, vol. 14(14), pages 1-17, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8532-:d:861093
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    References listed on IDEAS

    as
    1. Weber, Charles A. & Current, John R. & Benton, W. C., 1991. "Vendor selection criteria and methods," European Journal of Operational Research, Elsevier, vol. 50(1), pages 2-18, January.
    2. Kuen-Suan Chen & Hsi-Tien Chen & Tsang-Chuan Chang, 2017. "The construction and application of Six Sigma quality indices," International Journal of Production Research, Taylor & Francis Journals, vol. 55(8), pages 2365-2384, April.
    3. Mei-Fang Wu & Hsuan-Yu Chen & Tsang-Chuan Chang & Chih-Feng Wu, 2019. "Quality evaluation of internal cylindrical grinding process with multiple quality characteristics for gear products," International Journal of Production Research, Taylor & Francis Journals, vol. 57(21), pages 6687-6701, November.
    4. Tsang-Chuan Chang & Kuen-Suan Chen, 2019. "Testing process quality of wire bonding with multiple gold wires from viewpoint of producers," International Journal of Production Research, Taylor & Francis Journals, vol. 57(17), pages 5400-5413, September.
    5. Federica Acerbi & Claudio Sassanelli & Sergio Terzi & Marco Taisch, 2021. "A Systematic Literature Review on Data and Information Required for Circular Manufacturing Strategies Adoption," Sustainability, MDPI, vol. 13(4), pages 1-26, February.
    6. Chen-Ju Lin & W. L. Pearn & J. Y. Huang & Y. H. Chen, 2018. "Group selection for processes with multiple quality characteristics," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(16), pages 3923-3934, August.
    7. Chun-Ming Yang & Kuen-Suan Chen, 2019. "Two-phase selection framework that considers production costs of suppliers and quality requirements of buyers," International Journal of Production Research, Taylor & Francis Journals, vol. 57(20), pages 6351-6368, October.
    8. Chunguang Bai & Simonov Kusi-Sarpong & Sharfuddin Ahmed Khan & Diego Vazquez-Brust, 2021. "Sustainable buyer–supplier relationship capability development: a relational framework and visualization methodology," Annals of Operations Research, Springer, vol. 304(1), pages 1-34, September.
    9. Kun-Tzu Yu & Kuen-Suan Chen, 2016. "Testing and analysing capability performance for products with multiple characteristics," International Journal of Production Research, Taylor & Francis Journals, vol. 54(21), pages 6633-6643, November.
    10. Chen, Kuen-Suan & Wang, Ching-Hsin & Tan, Kim Hua & Chiu, Shun-Fung, 2019. "Developing one-sided specification six-sigma fuzzy quality index and testing model to measure the process performance of fuzzy information," International Journal of Production Economics, Elsevier, vol. 208(C), pages 560-565.
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