Fuzzy methodology application for risk analysis of mechanical system in process industry

Srivastava, Priyank; Khanduja, Dinesh; Ganesan, Subramaniam

doi:10.1007/s13198-019-00857-y

Cited by 14 publications

(7 citation statements)

References 33 publications

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“…The results under the implementation of this approach are based on membership values (in closed interval 0 to 1) only for considering uncertainty/vagueness in the quantitative raw data available from various sources. In the past, this approach has been applied by many researchers in order to carry the reliability analysis of different industrial system under uncertainty Panchal et al, 2019;Srivastava et al, 2020).Hesitation element in membership function values was not considered under traditional FLT approach, which was one of the major drawback responsible for low accuracy in results (Garg, 2014;Gopal & Panchal, 2022).To overcome this drawback, the introduction of IF concept in traditional FLT approach prove to be very useful for achieving highly accurate results (Garg, 2014). IFLT approach considers both membership and non-membership function-based values to consider the hesitation element, leads to high degree of accuracy in the reliability results.…”

Section: Iflt Approachmentioning

confidence: 99%

Reliability analysis of turbine unit using Intuitionistic Fuzzy Lambda-Tau approach

Panchal

2023

Rep. Mech. Eng.

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The current work presents a two phase Intuitionistic Fuzzy (IF) based framework, for investigating the reliability analysis of a Turbine Unit (TU) in a sugar mill process industry. Intuitionistic Fuzzy Lambda Tau (IFLT) approach-based series-parallel expressions have been applied for computing various reliability indices. For series arrangement OR gate transitions expression has been used, and for parallel arrangement AND gate expressions has been used for calculation of reliability parameters for membership and non- membership function. For membership function, system’s availability decreases by 0.000002% for spread value ±15% to±30%, further decreases by 0.000005% for spread value ± 30% to±45%. While, non- membership function-based system’s availability decreases by 0.000003% for spread value ± 15% to±30% and further decreases by 0.000007 % for spread value ± 30% to±45%. The reliability trends at various spreads lay the foundation of studying the failure behaviour of the TU and to plan a maintenance schedule.

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Section: Iflt Approachmentioning

confidence: 99%

Reliability analysis of turbine unit using Intuitionistic Fuzzy Lambda-Tau approach

Panchal

2023

Rep. Mech. Eng.

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“…Panchal and Kumar (2017a, b) presented the application of fuzzy rule base PFMEA approach for studying the risk issues of compressor house unit of a thermal power plant. Srivastava et al (2019a, b) expounded the application of IF-THEN rule based PFMEA model for analyzing the risk issues of milling unit in sugar mill industry. Srivastava et al (2019a, b) again applied fuzzy IF-THEN rule base PFMEA approach for studying and analyzing the risk issues of water treatment plant.…”

Section: Literature Surveymentioning

confidence: 99%

“…Srivastava et al (2019a, b) expounded the application of IF-THEN rule based PFMEA model for analyzing the risk issues of milling unit in sugar mill industry. Srivastava et al (2019a, b) again applied fuzzy IF-THEN rule base PFMEA approach for studying and analyzing the risk issues of water treatment plant. Balaraju et al (2019) presented the application of fuzzy IF-THEN rule base PFMEA approach for evaluating the failure risk associated with Load-Haul-Dumper (LHD) in mining industry.…”

Section: Literature Surveymentioning

confidence: 99%

A novel PFMEA-Doubly TOPSIS approach-based decision support system for risk analysis in milk process industry

Das

Panchal

Tyagi

2021

IJQRM

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PurposeThis paper aims to presents a novel integrated fuzzy decision support system for analyzing the issues related to failure of a milk process plant unit.Design/methodology/approachProcess failure mode effect analysis (PFMEA) approach was implemented to list failure causes under each subsystem/component and fuzzy ratings for three risk criteria, i.e. probability of failure occurrence (O_f), severity (S) and non-detection (O_d) are collected against the listed failure causes through experts feedback. A new doubly technique for order of preference by similarity to ideal solution (DTOPSIS) approach was implemented within fuzzy PFMEA tool for ranking of listed failure causes. The proposed decision support system overcomes the restrictions of classical PFMEA and IF-THEN rule base PFMEA approaches in an effective way.FindingsFailure causes such as electrical winding failure (RM4), high pressure in plate region (C1), communication problem in supervisory control and data acquisition control (MS3), insulation problem (ST2), lever breakage (B2), gasket problem (D3), formation of holes (PHE5), cavitations (FP7), deposition of milk particle inside the pipeline because of improper cleaning (MHP2) were acknowledged as the most critical one with the application of proposed decision support system.Research limitations/implicationsThe analysis results are based on subjective judgments of the experts and therefore correctness of risk ranking results are totally dependent upon the quality of input data/information available from these experts. However, the analyst has taken proper care for considering the vagueness of the raw data by incorporating fuzzy set theory within the proposed decision support system.Practical implicationsThe proposed fuzzy decision support system has been presented with its application on milk pasteurization plant of a milk process industry. The analysis based ranking results have been supplied to maintenance manager of the plant and a consent was shown by him with these results. Once the top management of the plant took decision for the implementation of these results, the detailed robustness of the proposed decision support system could be evaluated further.Social implicationsThe analysis result would be highly useful for minimizing sudden breakdowns and operational cost of the plant which directly contributes to plant's profitability. With the decrease in the chances of sudden breakdowns there would be high safety for the people working on/off the plant's site. Further, with increase in availability of the considered plant the societal daily demand related to dairy products could be easily fulfilled at reasonable prices.Originality/valueThe performance and proficiency of the proposed decision support system has been evaluated by comparing the ranking results with classical TOPSIS and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) approaches based results.

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“…[30] Integrating cloud model theory with extended GRA for resolving disadvantages of traditional RPN method. Screening unit in a paper mill Srivastava et al [31] Combined fuzzy decision support system and fuzzy GRA for estimating RPN scores, then compared with classical RPN scores for realistic prioritization and decision making.…”

Section: A Brief Literature Review Of Mcdm Combined With Fmeamentioning

confidence: 99%

A Failure Mode Assessment Model Based on Neutrosophic Logic for Switched-Mode Power Supply Risk Analysis

Liou

Liu

2020

Mathematics

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Reducing the potential risks in the manufacturing process to improve the reliability of the switched-mode power supply (SMPS) is a critical issue for the users’ safety. This paper proposes a novel failure mode and effects analysis (FMEA) model based on hybrid multiple criteria decision-making (MCDM), which adopts neutrosophic set theory into the proposed model. A developed neutrosophic Best Worst method (NBWM) is used to evaluate the weights of risk factors and determine their importance. Secondly, the neutrosophic Weight Aggregated Sum Product Assessments (NWASPAS) method is utilized to calculate the Risk Priority Number (RPN) of the failure modes. The proposed model improves the shortcomings of traditional FMEA and improves the practical applicability and effectiveness of the Best Worst method (BWM) and Weight Aggregated Sum Product Assessments (WASPAS) methods. In addition, this study uses neutrosophic logic to reflect the true judgments of experts in the assessment, which considers authenticity, deviation, and uncertainty to obtain more reliable information. Finally, an empirical case study from an SMPS company headquartered in Taiwan demonstrates the effectiveness and robustness of the proposed model. In addition, by comparing with two other FMEA models, the results show that the proposed model can more clearly reflect the true and effective risks in the assessment. The results can effectively help power supply manufacturers to assess risk factors and determine key failure modes.

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Fuzzy methodology application for risk analysis of mechanical system in process industry

Cited by 14 publications

References 33 publications

Reliability analysis of turbine unit using Intuitionistic Fuzzy Lambda-Tau approach

Reliability analysis of turbine unit using Intuitionistic Fuzzy Lambda-Tau approach

A novel PFMEA-Doubly TOPSIS approach-based decision support system for risk analysis in milk process industry

A Failure Mode Assessment Model Based on Neutrosophic Logic for Switched-Mode Power Supply Risk Analysis

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