Application of Fuzzy FMEA to Indian Railway Signalling Systems

Subhash Chandra Panja, Jadavpur University, Kolkata; Ramakrishna Prasad Chakraborty ,K. K. Das Colleges, Kolkata; Debashis Sarkar ,Asansol Engineering College, Asansol; Ratri Parida ,IIM Sambalpur, Odisha; Sankar Narayan Patra ,Jadavpur University, Kolkata

FMEA, Fuzzy Logic, Railway Signalling Systems, RPN

The paper deals with the failure analysis of railway signalling systems, in general, and Indian Railway signalling systems, in particular. It is worth mentioned that failure of railway signalling subsystems and systems hampers the safe running of rolling stock and thus, sometime reduces productivity. Both traditional and fuzzy logic-based failure mode and effect analysis (FMEA) are considered here to analyse the railway signalling failures. It is observed that on the basis of risk priority numbers (RPN) of railway signalling subsystem’s failure, fuzzy logic-based FMEA is better than the traditional FMEA. Also, one hundred and twenty five rules have been generated with the help of fuzzy logic-based FMEA by considering different levels of severity, occurrence, and detectability. Twenty rules out of one hundred and twenty five are taken into account as very significant as far as operation and failure analysis of signalling system is concerned.
    [1] Kumar, K.V. and Chandra, V.Transputer-based fault-tolerant and fail-safe node for dual ring distributed railway signalling systems. Microprocessors and Microsystems, 1994, 18 (3), 141-150 [2] Lee, J.-H., Hwang, J.-G., and Park G.-T. Performance evaluation and verification of communication protocol for railway signalling systems. Computer Standards and Interfaces, 2005, 27, 207-219 [3] Bowles, J.B. and Pelaez, C. E. Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis, Reliability Engineering and System Safety, 1995, 50, 203-213 [4] Pelaez, C. E. and Bowles, J.B. Using fuzzy cognitive maps as a system model for failure modes and effects analysis”, Information Sciences, 1996, 88 (1-4), 177-199 [5] Misra, K.B.Reliability analysis and prediction: a methodology oriented treatment. Elsevier Science Publishers B.V., Amsterdam, the Netherlands, 1992 [6] Garcia, P. A. A., Schirru, R. and Melo, P. F .F .E. A fuzzy data envelopment analysis approach for FMEA. Progress in Nuclear Energy, 2005, 46 (3-4), 359-373 [7] Guimaraes, A.C.F. and Lapa, C.M.F. Fuzzy FMEA applied to PWR chemical and volume control system. Progress in Nuclear Energy, 2004, 44 (3), 191-213 [8] Panja, S. C. and Ray, P.K. Failure mode and effect analysis of indian railway signalling system. International Journal of Performability Engineering, 2008, 4 (3), 3-14 [9] Saxena, S.C. and Arora, S.P. A text book of railway engineering, Sixth Revised and Enlarged Edition, DhanpatRai Publications (P) LTD., New Delhi, India, 2003 [10] Liu, H.C., Liu, L. and Liu N. Risk evaluation approaches in failure mode and effects analysis: A literature review. Expert Systems with Applications, 2013, 40 (2), 828-838 [11] Lin, Q.L., Wang, D.J., Lin W.G., and Liu H.C. Human reliability assessment for medical devices based on failure mode and effects analysis and fuzzy linguistic theory. Safety Sciences, 2014, 62, 248-256 [12] Chen P.S. and Wu M.T. A modified failure mode and effects analysis method for supplier selection problems in the supply chain risk environment: A case study. Computer and Industrial Engineering, 2013, 66 (4), 634 – 642
Paper ID: GRDCF010008
Published in: Conference : Reaching the Unreached: A Challenge to Technological Development (RUCTD2018)
Page(s): 58 - 63