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FMEA-based interpretive structural modelling approach to model automotive supply chain risk

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  • Ajay Kumar Pandey
  • Rajiv Kumar Sharma

Abstract

The purpose of this study is to analyse and model various risks which may disrupt the automotive supply chain. For illustration, an automotive supply chain of tractor manufacturing company has been undertaken, 17 potential modes of failures or risk sources are identified through close scrutiny of literature and weighted risk priority numbers (WRPN) have been calculated. Out of these 17 failure modes, 11 are selected as key learning's (by performing SAP-LAP analysis) based upon higher WRPN numbers. Further to model the structural relationship among these key risks interpretive structural modelling (ISM) approach is used. In order to find out the driving power and dependency of risks MICMAC analysis has been performed. The results of the study demonstrate that the variables, i.e., poor planning and scheduling and hazards are the key risk variables (highest driving power) and can be considered as the root cause of the problem. Quality risk, inventory risk and outsourcing risk have strong dependence power and hence can be considered as the most important risks and management shall focus on these for the managing the disruptions in an automotive supply chain.

Suggested Citation

  • Ajay Kumar Pandey & Rajiv Kumar Sharma, 2017. "FMEA-based interpretive structural modelling approach to model automotive supply chain risk," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 27(4), pages 395-419.
    • Handle: RePEc:ids:ijlsma:v:27:y:2017:i:4:p:395-419
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    Cited by:

    1. Huy Truong Quang & Yoshinori Hara, 2019. "Managing risks and system performance in supply network: a conceptual framework," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 32(2), pages 245-271.

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