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FM - a pragmatic tool to model, analyse and predict complex behaviour of industrial systems. (English) Zbl 1198.74103

Summary:
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.

MSC:

74S05 Finite element methods applied to problems in solid mechanics
74R99 Fracture and damage

Software:

PetriNets; SHARPE
Full Text: DOI

References:

[1] DOI: 10.1016/S0951-8320(02)00013-3 · doi:10.1016/S0951-8320(02)00013-3
[2] DOI: 10.1002/qre.545 · doi:10.1002/qre.545
[3] DOI: 10.1002/qre.747 · doi:10.1002/qre.747
[4] DOI: 10.1016/j.jlp.2003.08.006 · doi:10.1016/j.jlp.2003.08.006
[5] DOI: 10.1016/S0951-8320(02)00161-8 · doi:10.1016/S0951-8320(02)00161-8
[6] DOI: 10.1016/j.epsr.2003.08.011 · doi:10.1016/j.epsr.2003.08.011
[7] Bowles, J.B. (2003), ”An assessment of RPN prioritization in a failure modes effects and criticality analysis”,Proceedings of the Annual Reliability and Maintainability Symposium, pp. 380-6. · doi:10.1109/RAMS.2003.1182019
[8] DOI: 10.1016/0951-8320(95)00068-D · doi:10.1016/0951-8320(95)00068-D
[9] DOI: 10.1016/0165-0114(95)00385-1 · doi:10.1016/0165-0114(95)00385-1
[10] DOI: 10.1109/32.297939 · doi:10.1109/32.297939
[11] DOI: 10.1016/S0951-8320(00)00073-9 · doi:10.1016/S0951-8320(00)00073-9
[12] Exton, T. and Labib, A.W. (2002), ”Spare parts decision analysis the missing link in CMMSs (Part II)”,Journal of Maintenance & Asset Management, Vol. 17 No. 1, pp. 14-21.
[13] DOI: 10.1016/S0165-0114(00)00051-8 · Zbl 0979.68615 · doi:10.1016/S0165-0114(00)00051-8
[14] DOI: 10.1016/j.asoc.2005.06.002 · doi:10.1016/j.asoc.2005.06.002
[15] DOI: 10.1016/j.jlp.2004.06.004 · doi:10.1016/j.jlp.2004.06.004
[16] DOI: 10.1016/j.ress.2005.06.002 · doi:10.1016/j.ress.2005.06.002
[17] DOI: 10.1016/0951-8320(93)90029-X · doi:10.1016/0951-8320(93)90029-X
[18] Labib, A.W. (2003), ”Computerized maintenance management systems (CMMSs): a black hole or a black box?”,Journal of Maintenance & Asset Management, Vol. 18 No. 3, pp. 16-21.
[19] DOI: 10.1016/j.eswa.2004.08.003 · doi:10.1016/j.eswa.2004.08.003
[20] DOI: 10.1016/S0951-8320(97)00030-6 · doi:10.1016/S0951-8320(97)00030-6
[21] DOI: 10.1002/qre.668 · doi:10.1002/qre.668
[22] DOI: 10.1108/02644400410511855 · Zbl 1089.68642 · doi:10.1108/02644400410511855
[23] DOI: 10.1016/S0166-5316(01)00034-7 · Zbl 1014.68018 · doi:10.1016/S0166-5316(01)00034-7
[24] DOI: 10.1016/S0045-7949(02)00068-8 · doi:10.1016/S0045-7949(02)00068-8
[25] DOI: 10.1016/j.ress.2005.03.007 · doi:10.1016/j.ress.2005.03.007
[26] DOI: 10.1016/S0951-8320(02)00010-8 · doi:10.1016/S0951-8320(02)00010-8
[27] DOI: 10.1108/02656710510625248 · doi:10.1108/02656710510625248
[28] Sharma, R.K., Kumar, D. and Kumar, P. (2005c), ”FP approach to model and analyze system failure behavior”,Proceedings of International Conference on Reliability and Safety Engineering, INCRESE, IIT Khargpur, India, pp. 57-63.
[29] DOI: 10.1108/09544780710720817 · doi:10.1108/09544780710720817
[30] DOI: 10.1016/S0951-8320(01)00023-0 · doi:10.1016/S0951-8320(01)00023-0
[31] DOI: 10.1016/j.epsr.2003.07.001 · doi:10.1016/j.epsr.2003.07.001
[32] DOI: 10.1016/S0951-8320(97)00159-2 · doi:10.1016/S0951-8320(97)00159-2
[33] Swanson, L. (1997), ”Computerized maintenance management systems: a study of system design and use”,Production & Inventory Management Journal, Vol. 34, pp. 11-14.
[34] DOI: 10.1108/02656710610688202 · doi:10.1108/02656710610688202
[35] DOI: 10.1016/j.ress.2004.10.014 · doi:10.1016/j.ress.2004.10.014
[36] DOI: 10.1016/j.jss.2005.09.004 · doi:10.1016/j.jss.2005.09.004
[37] DOI: 10.1016/S0951-8320(01)00101-6 · doi:10.1016/S0951-8320(01)00101-6
[38] DOI: 10.1016/S0951-8320(02)00268-5 · doi:10.1016/S0951-8320(02)00268-5
[39] DOI: 10.1016/S0926-5805(03)00002-5 · doi:10.1016/S0926-5805(03)00002-5
[40] DOI: 10.1016/0020-0255(75)90046-8 · Zbl 0404.68074 · doi:10.1016/0020-0255(75)90046-8
[41] DOI: 10.1016/S0951-8320(01)00017-5 · doi:10.1016/S0951-8320(01)00017-5
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