Supply chain risk model for cement industry based on interpretive structural model driven by FMEA

Pallawi Baldeo Sangode


Purpose: This paper aims to identify, analyze, model the risk elements in the supply chain and further set future trends to evaluate risks in other domains of cement manufacturing industry. Cement is the second most consumed material in the world, has a fast supply chain in the global market. This has driven the authors to study the supply chain risks for this sector.

Design/methodology/approach: Through a detailed literature review and interaction with industry experts, 19 risk elements have been identified that may disrupt the supply chain activities. Failure Mode and Effect Analysis (FMEA) is used to prioritize these risk elements based on the risk priority number (RPN). RPN is derived from the severity, occurrence, and detectability of these risk elements in various process functions of the supply chain. 10 risk elements are selected from this analysis that have higher priority number. Further, these elements have been fed to the Interpretive Structural Model (ISM) that derived the contextual interrelationship among these elements. Further MICMAC analysis has been implemented on the risk elements based on their driving and dependency power.

Findings: Unpredicted heavy rainfall and energy shortages have been identified as the root causes of other risk elements.  Increasing turnaround time in logistics and fleet adjustment during heavy demand, having the highest dependence power, are considered as the most important risk elements in the cement industry supply chain.  

Originality/value: This is the first study in the domain of supply chain risks which has analyzed and modelled risks for cement industry. This work would provide the decision-makers of cement industry to focus on the specific risk elements for reducing disruptions in the supply chain.


Supply Chain Risks, Failure Mode and Effect Analysis, Interpretive Structural Modelling

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Licencia de Creative Commons 

This work is licensed under a Creative Commons Attribution 4.0 International License

Journal of Industrial Engineering and Management, 2008-2024

Online ISSN: 2013-0953; Print ISSN: 2013-8423; Online DL: B-28744-2008

Publisher: OmniaScience