FMECA-based maintenance planning through COPRAS-G and PSI

Abstract

Purpose

The purpose of this paper is to investigate the extent at which the reliability of an aluminium wire rolling mill can be improved by ameliorating current control and maintenance practices.

Design/methodology/approach

The paper deals with the discrimination of the most critical components by substantial shop-floor failure data. The research work narrates a method for evaluating maintainability criticality index for each failure cause of identified critical components through two different MCDM approaches: one based on grey-complex proportional risk assessment (COPRAS-G) and the other based on preference section index (PSI).

Findings

The primary findings of this research work are to prioritize the maintenance activities by comparing results obtained through different failure analysis models. It is proposing improvements in the maintenance plan of critical components like bearings, gears and shafts of an aluminium wire rolling mill which are commonly representing the most critical components in a large range of industrial processes.

Research limitations/implications

The limitation of the proposed study is that the failure models may not represent failures due to the first instant every time as adequate of design as such components are not checked for a high failure rate.

Practical implications

The proposed study is an interdisciplinary work which will help to understand about the working lives of components and associated failures. It will lead to reengineer new tools efficiently and to gain the maintenance excellence.

Originality/value

Originality mainly consists in the contemporary application of two non-identical MCDM-based methods (COPRAS-G and PSI). It will help to elucidate maintenance issues of major process industries and recommended deliverable keys.

Citation

Pancholi, N. and Bhatt, M. (2018), "FMECA-based maintenance planning through COPRAS-G and PSI", Journal of Quality in Maintenance Engineering, Vol. 24 No. 2, pp. 224-243. https://doi.org/10.1108/JQME-03-2017-0015