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Applying Bayesian Network Techniques to Prioritize Lean Six Sigma Efforts

Author

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  • Yanzhen Li

    (Continuous Improvement Manager, H&V Collision Center, Colonie, NY, USA)

  • Rapinder S. Sawhne

    (Department of Industrial and Information Engineering, The University of Tennessee, Knoxville, TN, USA)

  • Joseph H. Wilck

    (Department of Engineering, East Carolina University, Greenville, NC, USA)

Abstract

In order to retain competitive advantages, many manufacturing organizations have applied Lean Six Sigma techniques to improve production processes. The general approach for implementing Lean Six Sigma is to perform various projects to tackle specific problems or areas. However, with the manufacturing system and its external environment becoming more and more complex, it is simply not possible to solve all the problems given the limited resources. The purpose of this study is to develop a model that provides a systematic evaluation for potential opportunities to enhance the effectiveness of Lean Six Sigma. Deriving from the Bayesian Network methodology, the proposed model combines a graphical approach to represent cause-and-effect relationships between events of interests and probabilistic inference to estimate their likelihoods in the area of process improvement. The developed model can be used for assessing the problems associated with Lean Six Sigma initiatives and prioritizing efforts to solve these problems.

Suggested Citation

  • Yanzhen Li & Rapinder S. Sawhne & Joseph H. Wilck, 2013. "Applying Bayesian Network Techniques to Prioritize Lean Six Sigma Efforts," International Journal of Strategic Decision Sciences (IJSDS), IGI Global, vol. 4(2), pages 1-15, April.
    • Handle: RePEc:igg:jsds00:v:4:y:2013:i:2:p:1-15
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    Cited by:

    1. Tamie Takeda Yokoyama & Satie Ledoux Takeda-Berger & Marco Aurélio Oliveira & Andre Hideto Futami & Luiz Veriano Oliveira Dalla Valentina & Enzo Morosini Frazzon, 2023. "Bayesian networks as a guide to value stream mapping for lean office implementation: a proposed framework," Operations Management Research, Springer, vol. 16(1), pages 49-79, March.
    2. Jun-Der Leu & Wen-Hsien Tsai & Mei-Niang Fan & Sophia Chuang, 2020. "Benchmarking Sustainable Manufacturing: A DEA-Based Method and Application," Energies, MDPI, vol. 13(22), pages 1-21, November.

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