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Quality evaluation of internal cylindrical grinding process with multiple quality characteristics for gear products

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  • Mei-Fang Wu
  • Hsuan-Yu Chen
  • Tsang-Chuan Chang
  • Chih-Feng Wu

Abstract

Gears are among the most crucial components in the transmission systems of machine tools. Gear manufacturing includes a number of processing procedures. The grinding process is an important procedure involving high precision and fairly small grinding surfaces. For this reason, this study aimed at developing a quality assessment model for the internal cylindrical grinding process of gears. The Six Sigma quality indices (SSQIs) were used to directly assess the quality of the internal cylindrical grinding process due to their ability to directly reflect quality level and process yield. Since the process may include nominal-the-best (NTB), larger-the-better (LTB) and smaller-the-better (STB) quality characteristics, so we used the variable transformation method to normalise the specifications of each quality characteristic for the convenient and effective management and analysis of process performance for multiple quality characteristics. We then constructed a multi-characteristic process quality analysis chart (MPQAC) to simultaneously assess the quality levels of various quality characteristics. Furthermore, the MPQAC can provide references for process improvement. This ensures the quality of internal cylindrical grinding and enhances the quality of gear and machine tool products. Finally, a real-world application and numerical experiments demonstrate the effectiveness and practical applicability of the proposed method.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:21:p:6687-6701
    DOI: 10.1080/00207543.2019.1567951
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    Citations

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    Cited by:

    1. Kuen-Suan Chen & Tsun-Hung Huang & Ruey-Chyn Tsaur & Wen-Yang Kao, 2022. "Fuzzy Evaluation Models for Accuracy and Precision Indices," Mathematics, MDPI, vol. 10(21), pages 1-12, October.
    2. Kuen-Suan Chen & Tsang-Chuan Chang, 2022. "Fuzzy testing model for the lifetime performance of products under consideration with exponential distribution," Annals of Operations Research, Springer, vol. 312(1), pages 87-98, May.
    3. Kuen-Suan Chen & Tsun-Hung Huang, 2021. "A Fuzzy Evaluation Model Aimed at Smaller-the-Better-Type Quality Characteristics," Mathematics, MDPI, vol. 9(19), pages 1-13, October.
    4. 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.
    5. 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.
    6. Wei Lo & Chun-Ming Yang & Kuei-Kuei Lai & Shao-Yu Li & Chi-Han Chen, 2021. "Developing a Novel Fuzzy Evaluation Model by One-Sided Specification Capability Indices," Mathematics, MDPI, vol. 9(10), pages 1-11, May.
    7. Kuen-Suan Chen & Chin-Chia Liu & Chi-Han Chen, 2022. "Fuzzy Evaluation of Process Quality with Process Yield Index," Mathematics, MDPI, vol. 10(14), pages 1-11, July.
    8. Chun-Chieh Tseng & Kuo-Ching Chiou & Kuen-Suan Chen, 2022. "Estimation of the Six Sigma Quality Index," Mathematics, MDPI, vol. 10(19), pages 1-13, September.
    9. Kuo-Ching Chiou, 2023. "Building Up of Fuzzy Evaluation Model of Life Performance Based on Type-II Censored Data," Mathematics, MDPI, vol. 11(17), pages 1-12, August.
    10. 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.

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