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.
Keywords
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
Publisher
:Emerald Group Publishing Limited
Copyright © 2007, Emerald Group Publishing Limited