Failure Mode Effect Analysis (FMEA) is popular and versatile approach applicable to risk assessment and safety improvement of a repairable engineering system. This method encompasses various fields such as manufacturing, healthcare, paper mill, thermal power industry, software industry, services, security etc. in terms of its application. In general, FMEA is based on Risk Priority Number (RPN) score which is found by product of probability of Occurrence (O), Severity of failure (S) and Failure Detection (D). As human judgement is approximate in nature, the accuracy of data obtained from FMEA members depend on degree of subjectivity. The subjective knowledge of members not only contains uncertainty but hesitation too which in turn, affect the results. Fuzzy FMEA considers uncertainty and vagueness of the data/ information obtained from experts. In order to take into account, the hesitation of experts and vague concept, in the present work we propose integrated framework based on Intuitionistic Fuzzy- Failure Mode Effect Analysis (IF-FMEA) and IF-Technique for Order Preference by Similarity to Ideal Solution (IF-TOPSIS) techniques to rank the listed failure causes. Failure cause Fibrizer (FR) was found to be the most critical failure cause with RPN score 0.500. IF-TOPSIS has been implemented within IF-FMEA to compare and verify ranking results obtained by both the IF based approaches. The proposed method was presented with its application for examining the risk assessment of cutting system in sugar mill industry situated in western Uttar Pradesh province of India. The result would be useful for the plant maintenance manager to fix the best maintenance schedule for improving availability of cutting system.
Purpose
The purpose of this paper is to develop a fuzzy methodology approaches based framework for carrying the risk analysis of a real industrial system of a urea fertilizer industry located in northern part of India.
Design/methodology/approach
Petri Net approach was applied for representing the series-parallel arrangement of the considered system. Various failure causes related to different subsystems or equipment of the considered system were listed under FMEA approach and their Risk Priority Number was tabulated. Further, to overcome the drawbacks of traditional FMEA approach in risk ranking fuzzy FMEA and grey relation analysis (GRA) approaches were applied within traditional FMEA approach and the ranking results were compared for better and effective decision making of risky components.
Findings
The proposed framework has overcome the drawbacks of tradition FMEA approach in an effective and efficient manner. Causes AC7, CL3, ST2, DR3 and NR3 of centrifugal compressor, hot heat exchanger, ammonia convertor reactor, cold condenser and ammonia separator have been identified as the most critical failure causes of the considered system.
Originality/value
The proposed framework has been tested with its application on an ammonia synthesis system of the considered process industry. The risk ranking results would be highly useful in developing a planned maintenance policy for the considered system which further results in improving the system availability.
This paper aims at proposing a novel integrated framework for studying reliability and risk issues of the curd unit in a milk process industry under uncertain environment. The considered plant’s complex series-parallel configuration was presented using the Petri Net (PN) modeling. The Fuzzy Lambda-Tau (λ-τ) approach was applied to study and analyze the reliability aspects of the considered plant. Failure dynamics of the curd unit has been analyzed with respect to increasing/ decreasing trends of the tabulated reliability indices. Availability of the considered plant shows a decreasing trend with an increase in spread values. For improving the system’s availability, a risk analysis was done to identify the most critical failure causes. Using the traditional FMEA approach, the FMEA sheet was generated on the basis of expert’s knowledge/experience. The Fuzzy-Complex Proportional Assessment (FCOPRAS) approach was applied within FMEA approach for identification of critical failure causes associated with different subsystem/components of the considered plant. In order to check the consistency of the ranking results, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) was applied within the FCOPRAS approach. Ranking results are compared for checking consistency and robustness of critical failure causes related decision making which would be useful in designing the finest maintenance schedule for the considered curd unit. Overheating/moisture lead to winding failure (MSCP5), visible sediment of milk jam in filter (MBFP3), improper quality of oil (H4), blade breakage (CTK4), wearing in gears (PFM11), and cylinder leakage (CFM7) were recognized as the most critical failure causes contributing to system unavailability. The analysis results were supplied to the maintenance manager for framing a suitable time-based maintenance intervals policy for the considered unit.
This study proposes a novel structured framework for analyzing sustainable operational performance‐related issues of ash handling unit (AHU) under vague/uncertain information and its impact on ecofriendly production. The structured framework is developed using an integrated fuzzy lambda–tau and fuzzy multicriteria decision‐making methods. Reliability parameters are formulated for assessing the failure behavior of AHU using the fuzzy lambda–tau approach. Repair time parameter for the AHU system shows an increasing trend with a 0.6840% increase as the spread increases from ±15% to ±25% and 0.5981% when spread increases from ±25% to ±60%. Furthermore, the availability of the system decreases by 0.0335% with increase in spread from ±15% to ±25% and further decreases to 0.0315% with spread increases from ±25% to ±60%. Under risk analysis, possible failure causes with their fuzzy rating are listed under the failure mode and effect analysis (FMEA) approach. Evaluation based on distance from average solution (EDAS) and combinative distance‐based assessment (CODAS) methods are further applied within the FMEA approach for identifying the most critical failure causes. Improper design (BT2), excessive gas volume (FH3), chocking/blockage (WA1), and scanty lubrication/greasing (SP1) associated with bottom ash handling, the fly ash handling system, wetting unit and ash disposal pipeline, and slurry pump with EDAS outputs (0.1464, 0.1090, 0.0918, 0.000) and CODAS outputs (3.3962, 3.5208, 2.6562, 2.0877) are found responsible for sudden failure of the considered unit. Sensitivity analysis has been done for evaluating the robustness of the proposed framework.
The aim of this research work is to study the behaviour of the CHU (compressor house unit) of a medium size coal fired thermal power plant using fuzzy -approach (quantitative approach). The system has been modelled using PN and various reliability indices viz. failure rate, repair time, MTBF, ENOF, Availability and reliability are computed at different spread/uncertainty level. The results are helpful to the system analyst to analyse the behaviour of the system and to plan suitable maintenance policy for improving the system availability.
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