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

Ajay Kumar Pandey and Rajiv Kumar Sharma

International Journal of Logistics Systems and Management, 2017, vol. 27, issue 4, 395-419

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.

Keywords: failure modes and effect analysis; FMEA; automotive supply chain; interpretive structural modelling; ISM; case study. (search for similar items in EconPapers)
Date: 2017
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