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


Article Information:

Title:

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

Author(s):

Rajiv Kumar Sharma, Dinesh Kumar, Pradeep Kumar

Journal:

Engineering Computations

Year:

2007 

Volume:

24 

Issue:

4 

Page:

319 - 346


DOI:

10.1108/02644400710748670

Publisher:

Emerald Group Publishing Limited

Document Access:

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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:

Failure (mechanical), Maintenance, Paper industry, Reliability management, System monitoring

Article Type:

Research paper

References:

57 references

Article URL:

www.emeraldinsight.com/10.1108/02644400710748670

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