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Testing and analysing capability performance for products with multiple characteristics

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  • Kun-Tzu Yu
  • Kuen-Suan Chen

Abstract

Process capability analysis is a vital part of an overall quality improvement programme. Numerous techniques and tools have been proposed for process capability analysis. Among these, indices and charts of process capability are simple and effective tools and widely used in the manufacturing industry. Many scholars have revealed numerous valuable aspects of previously developed tools and methods. Due to the rising demands of product quality, the current tools and methods are insufficient for enabling managers to make informed decisions. To address this gap, this study proposes a hypothesis testing procedure which determines whether the process capabilities satisfy the target level. Furthermore, this study proposes an integrated quality test chart (IQTC), which can display the process potential and performance for an entire product with smaller-the-better, larger-the-better and nominal-the-best specifications. The proposed procedure and IQTC incorporate the quality-level concept of the Six Sigma model and can be used to quantitate the relationships among the quality level, capability indices and process yield. They can be applied to assist managers in measuring, monitoring, analysing and improving process performance in a timely manner which will help ensure that the quality levels of their products meet customer demands. Finally, an example is provided to illustrate how to use the proposed procedure and IQTC.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:21:p:6633-6643
    DOI: 10.1080/00207543.2016.1203469
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    Cited by:

    1. Chun-Min Yu & Win-Jet Luo & Ting-Hsin Hsu & Kuei-Kuei Lai, 2020. "Two-Tailed Fuzzy Hypothesis Testing for Unilateral Specification Process Quality Index," Mathematics, MDPI, vol. 8(12), pages 1-18, November.
    2. Kuen-Suan Chen & Chun-Min Yu, 2024. "Confidence-interval-based fuzzy supplier selection model with lifetime performance index," Annals of Operations Research, Springer, vol. 340(1), pages 133-147, September.
    3. Kuen-Suan Chen & Kung-Jeng Wang & Tsang-Chuan Chang, 2017. "A novel approach to deriving the lower confidence limit of indices , , and in assessing process capability," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 4963-4981, September.
    4. Wang, Ching-Hsin & Chen, Kuen-Suan, 2020. "New process yield index of asymmetric tolerances for bootstrap method and six sigma approach," International Journal of Production Economics, Elsevier, vol. 219(C), pages 216-223.
    5. 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.
    6. Kuen-Suan Chen & Tsang-Chuan Chang & Chien-Che Huang, 2020. "Supplier Selection by Fuzzy Assessment and Testing for Process Quality under Consideration with Data Imprecision," Mathematics, MDPI, vol. 8(9), pages 1-14, August.

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