A new fuzzy methodology-based structured framework for RAM and risk analysis

Abstract The aim of this paper is to propose a new hybridized framework for analyzing the performance issues of a chemical process plant by utilizing uncertain, imprecise and vague information. In the proposed framework, Fuzzy Lambda–Tau (FLT) approach has been used for computing reliability, availability and maintainability (RAM) parameters of the considered system. Further, for enhancing the RAM characteristics of the system, improved Fuzzy Failure Mode Effect Analysis (FMEA) approach is adopted. Under improved Fuzzy FMEA approach, defined Fuzzy linguistic rating values in the form of triangular and trapezoidal Fuzzy numbers have been assigned by the experts to each risk factor of the listed failure causes. The proposed framework is demonstrated with an industrial application in a chlorine production plant of a chemical process industry. The results show decreasing trend for system availability and deposition of solid Nacl, mechanical failure, corrosion due to wet chlorine, scanty lubrication, improper adsorption and valve malfunctioning are identified as the most critical failure causes for the considered system. A comparative performance analysis between the proposed framework, Fuzzy technique for order of preference by similarity to ideal solution (Fuzzy TOPSIS), Fuzzy evaluation based on distance from average solution (Fuzzy EDAS) and Fuzzy Vlse Kriterijumska Optimizacija I Kompromisno Resenje (Fuzzy VIKOR) are then carried out to show the competence of the proposed framework. It is expected that the analytical results would be highly useful in formulating an optimal maintenance policy for such complex systems and may also be used for improving performance of similar plants.

[1]  Jian-Bo Yang,et al.  Engineering System Safety Analysis and Synthesis Using the Fuzzy Rule‐based Evidential Reasoning Approach , 2005 .

[2]  Zhang-peng Tian,et al.  Risk evaluation by FMEA of supercritical water gasification system using multi-granular linguistic distribution assessment , 2018, Knowl. Based Syst..

[3]  Buket Karatop,et al.  The risk analysis by failure mode and effect analysis (FMEA) and fuzzy-FMEA of supercritical water gasification system used in the sewage sludge treatment , 2017 .

[4]  Wei Wu,et al.  Development of a risk-based maintenance strategy using FMEA for a continuous catalytic reforming plant , 2012 .

[5]  Harish Garg,et al.  An approach for analyzing the reliability of industrial systems using soft-computing based technique , 2014, Expert Syst. Appl..

[6]  Gwo-Hshiung Tzeng,et al.  Extended VIKOR method in comparison with outranking methods , 2007, Eur. J. Oper. Res..

[7]  Harish Garg,et al.  Performance analysis of an industrial system using soft computing based hybridized technique , 2017 .

[8]  Morteza Yazdani,et al.  Intuitionistic fuzzy edas method: an application to solid waste disposal site selection , 2017 .

[9]  Zhang-peng Tian,et al.  An integrated approach for failure mode and effects analysis based on fuzzy best-worst, relative entropy, and VIKOR methods , 2018, Appl. Soft Comput..

[10]  Harish Garg,et al.  Modeling and Analyzing System Failure Behavior for Reliability Analysis Using Soft Computing-Based Techniques , 2016 .

[11]  H. Schneider Failure mode and effect analysis : FMEA from theory to execution , 1996 .

[12]  Dinesh Kumar,et al.  Stochastic behaviour analysis of power generating unit in thermal power plant using fuzzy methodology , 2016 .

[13]  Patrick T. Hester,et al.  An Analysis of Multi-Criteria Decision Making Methods , 2013 .

[14]  Dinesh Kumar,et al.  Stochastic behaviour analysis of real industrial system , 2017, Int. J. Syst. Assur. Eng. Manag..

[15]  Dinesh Kumar,et al.  Modeling system behavior for risk and reliability analysis using KBARM , 2007, Qual. Reliab. Eng. Int..

[16]  Kostas Kalaitzakis,et al.  A fuzzy knowledge based method for maintenance planning in a power system , 2002, Reliab. Eng. Syst. Saf..

[17]  Dinesh Kumar,et al.  Integrated framework for behaviour analysis in a process plant , 2016 .

[18]  Charles E Ebeling,et al.  An Introduction to Reliability and Maintainability Engineering , 1996 .

[19]  Valentinas Podvezko,et al.  MCDM Assessment of a Healthy and Safe Built Environment According to Sustainable Development Principles: A Practical Neighborhood Approach in Vilnius , 2017 .

[20]  Edmundas Kazimieras Zavadskas,et al.  Extended EDAS Method for Fuzzy Multi-criteria Decision-making: An Application to Supplier Selection , 2016, Int. J. Comput. Commun. Control.

[21]  V. D. Tsoukalas,et al.  An adaptive neuro-fuzzy inference system (anfis) model for assessing occupational risk in the shipbuilding industry , 2014 .

[22]  H. Zimmermann,et al.  Fuzzy Set Theory and Its Applications , 1993 .

[23]  Jin Wang,et al.  Modified failure mode and effects analysis using approximate reasoning , 2003, Reliab. Eng. Syst. Saf..

[24]  Ying-Shen Juang,et al.  A knowledge management system for series-parallel availability optimization and design , 2008, Expert Syst. Appl..

[25]  Qingji Zhou,et al.  Fuzzy and grey theories in failure mode and effect analysis for tanker equipment failure prediction , 2016 .

[26]  David He,et al.  System Failure Analysis Through Counters of Petri Net Models , 2004 .

[27]  Cerry M. Klein,et al.  A simple approach to ranking a group of aggregated fuzzy utilities , 1997, IEEE Trans. Syst. Man Cybern. Part B.

[28]  Loon Ching Tang,et al.  Fuzzy assessment of FMEA for engine systems , 2002, Reliab. Eng. Syst. Saf..

[29]  Navneet Arora,et al.  Stochastic analysis and maintenance planning of the ash handling system in the thermal power plant , 1997 .

[30]  Morteza Yazdani,et al.  A state-of the-art survey of TOPSIS applications , 2012, Expert Syst. Appl..

[31]  Jezdimir Knezevic,et al.  Reliability modelling of repairable systems using Petri nets and fuzzy Lambda-Tau methodology , 2001, Reliab. Eng. Syst. Saf..

[32]  Tzong-Shi Liu,et al.  The application of Petri nets to failure analysis , 1997 .

[33]  Edmundas Kazimieras Zavadskas,et al.  Multi-Criteria Inventory Classification Using a New Method of Evaluation Based on Distance from Average Solution (EDAS) , 2015, Informatica.

[34]  Zhen Chen,et al.  Risk assessment of an oxygen-enhanced combustor using a structural model based on the FMEA and fuzzy fault tree , 2014 .

[35]  Dinesh Kumar,et al.  Reliability analysis of complex multi-robotic system using GA and fuzzy methodology , 2012, Appl. Soft Comput..

[36]  G. Sakthivel,et al.  Application of failure mode and effect analysis in manufacturing industry - an integrated approach with FAHP-fuzzy TOPSIS and FAHP-fuzzy VIKOR , 2018 .

[37]  Francisco Chiclana,et al.  An integrated inverse adaptive neural fuzzy system with Monte-Carlo sampling method for operational risk management , 2018, Expert Syst. Appl..

[38]  Mangey Ram,et al.  Risk analysis for clean and sustainable production in a urea fertilizer industry , 2018, International Journal of Quality & Reliability Management.

[39]  Lin Li,et al.  Picture fuzzy normalized projection-based VIKOR method for the risk evaluation of construction project , 2018, Appl. Soft Comput..

[40]  Pooja Sharma,et al.  Integrated framework to optimize RAM and cost decisions in a process plant , 2012 .

[41]  Harish Garg,et al.  Performance and behavior analysis of repairable industrial systems using Vague Lambda-Tau methodology , 2014, Appl. Soft Comput..

[42]  Khalil Md Nor,et al.  Development of TOPSIS Method to Solve Complicated Decision-Making Problems - An Overview on Developments from 2000 to 2015 , 2016, Int. J. Inf. Technol. Decis. Mak..

[43]  Zhiyong Gao,et al.  Failure mode and effects analysis using Dempster-Shafer theory and TOPSIS method: Application to the gas insulated metal enclosed transmission line (GIL) , 2018, Appl. Soft Comput..

[44]  Chee Peng Lim,et al.  Fuzzy FMEA with a guided rules reduction system for prioritization of failures , 2006 .

[45]  Valentinas Podvezko,et al.  Evaluation of quality assurance in contractor contracts by multi-attribute decision-making methods , 2017 .

[46]  Harish Garg,et al.  Predicting uncertain behavior of press unit in a paper industry using artificial bee colony and fuzzy Lambda-Tau methodology , 2013, Appl. Soft Comput..

[47]  Jeffery K. Cochran,et al.  Generic Markov models for availability estimation and failure characterization in petroleum refineries , 2001, Comput. Oper. Res..

[48]  Edmundas Kazimieras Zavadskas,et al.  Evaluation of Combined Heat and Power (CHP) Systems Using Fuzzy Shannon Entropy and Fuzzy TOPSIS , 2016 .

[49]  Jurgita Antucheviciene,et al.  A new multi-criteria model based on interval type-2 fuzzy sets and EDAS method for supplier evaluation and order allocation with environmental considerations , 2017, Comput. Ind. Eng..