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A comprehensive model to prioritise lean tools for manufacturing industries: a fuzzy FMEA, AHP and QFD-based approach

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  • M. Bhuvanesh Kumar
  • R. Parameshwaran

Abstract

This paper describes a start-to-end lean tools (LTs) selection model for manufacturing industries. The integrated model utilises value stream mapping (VSM) and plant layout for identifying wastes from current state of the organisation. For prioritising the wastes along with associated risks, failure mode and effects analysis (FMEA) is adopted. Selection of LTs is done using analytic hierarchy process (AHP) and house of quality (HoQ). This model utilises fuzzy logic (FL) to convert the linguistic judgements into numerical values for computation. Future state map deployed with the shortlisted LTs is developed to compare current and future states. The model is applied in PVC pipe manufacturing industry and the results show notable improvements. The raw material saving of 2.5 kg, 3% reduction of value added time, 7% reduction of non-value added time and 5% reduction of lead time in the production of PVC pipes per batch are obtained in future state.

Suggested Citation

  • M. Bhuvanesh Kumar & R. Parameshwaran, 2020. "A comprehensive model to prioritise lean tools for manufacturing industries: a fuzzy FMEA, AHP and QFD-based approach," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 37(2), pages 170-196.
    • Handle: RePEc:ids:ijsoma:v:37:y:2020:i:2:p:170-196
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    Citations

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    Cited by:

    1. Mohammad Javad Rahimdel & Behzad Ghodrati, 2021. "Risk Prioritization for Failure Modes in Mining Railcars," Sustainability, MDPI, vol. 13(11), pages 1-14, May.
    2. Bhattacharjee, Pushparenu & Dey, Vidyut & Mandal, U.K. & Paul, Susmita, 2022. "Quantitative risk assessment of submersible pump components using Interval number-based Multinomial Logistic Regression(MLR) model," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    3. Chih-Hung Hsu & Xu He & Ting-Yi Zhang & An-Yuan Chang & Wan-Ling Liu & Zhi-Qiang Lin, 2022. "Enhancing Supply Chain Agility with Industry 4.0 Enablers to Mitigate Ripple Effects Based on Integrated QFD-MCDM: An Empirical Study of New Energy Materials Manufacturers," Mathematics, MDPI, vol. 10(10), pages 1-35, May.

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