FM – a pragmatic tool to model, analyse and predict complex behaviour of industrial systems

Abstract

Purpose

This paper aims to permit the system reliability analysts/managers/practitioners/engineers to analyze the system failure behavior using fuzzy methodology (FM)

Design/methodology/approach

In order to deal with both qualitative and quantitative information related to system performance the authors have adopted failure mode effect analysis (FMEA) and Petrinets (PNs), the well‐known tools for reliability analysis, to build an integrated framework aimed at helping the reliability and maintenance managers in decision‐making.

Findings

Using the proposed framework an industrial case from the paper mill is examined. From the results it is observed that the limitations associated with the traditional procedure of risk ranking in FMEA are efficiently modeled using fuzzy decision‐making system (FDMS) based on FM. Also, the fuzzy synthesis of system failure and repair data helps to quantify the system behavior in a more realistic manner.

Originality/value

The simultaneous adoption of the proposed techniques to model, analyze and predict the uncertain behavior of an industrial system will not only help the reliability engineers/managers/practitioners to understand the behavioral dynamics of system but also to plan/adapt suitable maintenance practices to improve system reliability, availability and maintainability (RAM) aspects.

Citation

Sharma, R.K., Kumar, D. and Kumar, P. (2007), "FM – a pragmatic tool to model, analyse and predict complex behaviour of industrial systems", Engineering Computations, Vol. 24 No. 4, pp. 319-346. https://doi.org/10.1108/02644400710748670