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An Integrated Key Performance Measurement for Manufacturing Operations Management

Author

Listed:
  • Gyusun Hwang

    (Memory Business Unit, Device Solution, Samsung Electronics Co., Ltd., Hwaseong-si 18448, Korea)

  • Jun-Hee Han

    (Department of Industrial and Management Engineering, Dong-A University, Busan 49315, Korea)

  • Tai-Woo Chang

    (Department of Industrial and Management Engineering/Intelligence and Manufacturing Research Center, Kyonggi University, Suwon-si 16227, Korea)

Abstract

This paper proposes a comprehensive production performance measurement framework and illustrates the method to evaluate the performance and guide practitioners to make further improvement. The development comprises four steps. (1) Performance indicators derived from business excellence models are enumerated to provide the performance model: 74 indicators, which can be classified in terms of their characteristics, are identified in six criteria. (2) A multiple criteria decision-making approach based on the analytic hierarchical and network processes, which determine the weights of the criteria and indicators, is applied. In addition, this study introduced additional formulas to derive the final performance values. (3) A performance measurement framework that integrates the measurement and result analysis processes is implemented. (4) The proposed framework is verified through a case study. The results of the case study show that the proposed framework identifies the gaps and discrepancies among the management levels, enabling the determination of means for continuous improvement.

Suggested Citation

  • Gyusun Hwang & Jun-Hee Han & Tai-Woo Chang, 2020. "An Integrated Key Performance Measurement for Manufacturing Operations Management," Sustainability, MDPI, vol. 12(13), pages 1-15, June.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:13:p:5260-:d:377785
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    References listed on IDEAS

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    4. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    5. Guangdong Wu , & Kaifeng Duan & Jian Zuo & Xianbo Zhao & Daizhong Tang, 2017. "Integrated Sustainability Assessment of Public Rental Housing Community Based on a Hybrid Method of AHP-Entropy Weight and Cloud Model," Sustainability, MDPI, vol. 9(4), pages 1-25, April.
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    Cited by:

    1. Prabath Chaminda Abeysiriwardana & Udith K. Jayasinghe-Mudalige, 2021. "Role of Peripheral Analysis Methods in Adoption of Successful KPIs for a Research Institute Working Towards Commercial Agriculture," International Journal of Global Business and Competitiveness, Springer, vol. 16(1), pages 61-71, June.

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