Power distribution operational risk model driven by FMEA and ISM approach

Abstract

Purpose

The purpose of this paper is to identify various risks in the power distribution supply chain and further to prioritize the risk variables and propose a model to the power distribution industry for managing the interruptions in its supply chain. To accomplish this objective, a case of a major power distribution company has been considered.

Design/methodology/approach

Failure mode and effects analysis (FMEA) analysis has been done to identify the potential failure modes, their severity, and occurrence and detection scores. Then an interpretive structural model (ISM) has been developed to identify and understand the interrelationships among these enablers followed by MICMAC analysis, to classify the risk variables in four quadrants based on their driving and dependency powers.

Findings

The results of this study exhibit that technical failure in the information and technology system, the use of improper equipment, poor maintenance and housekeeping in the internal operations are the major risk drivers. Exposure to live wires and commercial loss in power supply has strong dependence power.

Research limitations/implications

This study is limited to a single power distribution company and not the whole power distribution sector.

Practical implications

This study suggests the managers of the power distribution company develop an initial understanding of the drivers and the dependent powers on the supply chain risks.

Social implications

Through prioritization, identification of drivers and the dependent risks, the losses in the power distribution supply chain can be minimized.

Originality/value

Various failures in the power distribution have been studied in the past, but they have not investigated the supply chain risks in the power distribution of a power distribution company.

Citation

Sangode, P.B. and Metre, S.G. (2021), "Power distribution operational risk model driven by FMEA and ISM approach", International Journal of Quality & Reliability Management, Vol. 38 No. 7, pp. 1445-1465. https://doi.org/10.1108/IJQRM-06-2019-0206