Reliability Analysis of CHU System of Coal Fired Thermal Power Plant Using Fuzzy λ-τ Approach

Panchal, Dilbagh; Kumar, Dinesh

doi:10.1016/j.proeng.2014.12.330

Cited by 18 publications

(11 citation statements)

References 16 publications

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“…To reduce the accumulating phenomenon of fuzziness, accelerating the computation process and using different membership functions in such a way that computed reliability parameters have symmetric shapes, this study applies TBGFLT technique to analyze the fuzzy reliability of CHU system in a coal fired thermal power plant (Panchal and Kumar, 2014; Komal, 2018a). The procedural steps of the TBGFLT technique are as followings: Step 1.…”

Section: Procedural Steps Of the Presented Tbgflt Techniquementioning

confidence: 99%

“…A coal fired thermal power plant consist of various functionary sub-system such as coal handling plant, coal crushing unit, water treatment plant, steam generating unit, power generating unit, CHU, ash handling unit, etc. (Panchal and Kumar, 2014). The present analysis is based on the study of CHU.…”

Section: A Case Studymentioning

confidence: 99%

“…The system RBD and its fault tree are shown in Figure 4. The failure rate ( λ i ) and repair time ( τ i ) data for its main components are given in Table VII (Panchal and Kumar, 2014).…”

Section: A Case Studymentioning

confidence: 99%

“…Also, these approaches do not examine the systems for components with different membership functions. Thus, the present study is an effort in this direction and evaluates fuzzy reliability of the compressor house unit (CHU) system in a coal fired thermal power plant for components with different membership functions, which is the main contribution of the paper (Panchal and Kumar, 2014). To analyze the fuzzy reliability of the system in more promising way by adopting different fuzzy membership functions through reducing the accumulating phenomenon of fuzziness and accelerating the computation process, this paper applies T ω -based generalized fuzzy Lambda-Tau (TBGFLT) technique Komal (2018b).…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy reliability analysis of the compressor house unit (CHU) system in a coal fired thermal power plant using TBGFLT technique

Komal

2019

IJQRM

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Purpose The purpose of this paper is to analyze the fuzzy reliability of the compressor house unit (CHU) system in a coal fired thermal power plant under vague environment by reducing the accumulating phenomenon of fuzziness and accelerating the computation process. This paper uses different fuzzy membership functions to quantify uncertainty and access the system reliability in terms of different fuzzy reliability indices having symmetric shapes. Design/methodology/approach This study analyses the fuzzy reliability of the CHU system in a coal fired thermal power plant using Tω-based generalized fuzzy Lambda-Tau (TBGFLT) technique. This approach applies fault tree, Lambda-Tau method, different fuzzy membership functions and α-cut coupled Tω-based approximate arithmetic operations to compute various reliability parameters (such as failure rate, repair time, mean time between failures, expected number of failures, availability and reliability) of the system. The effectiveness of TBGFLT technique has been demonstrated by comparing the results with results obtained from four different existing techniques. Moreover, this paper applies the extended Tanaka et al. (1983) approach to rank the critical components of the system when different membership functions are used. Findings The adopted TBGFLT technique in the present study improves the shortcomings of the existing approaches by reducing the accumulating phenomenon of fuzziness, accelerating the computation process and getting symmetric shapes for computed reliability parameters when different membership functions are used to quantify data uncertainty. Originality/value In existing fuzzy reliability techniques which are developed for repairable systems either triangular fuzzy numbers, triangle vague sets or triangle intuitionistic fuzzy sets have been used for quantifying uncertainty. These approaches do not examine the systems for components with different membership functions. The present study is an effort in this direction and evaluates the fuzzy reliability of the CHU system in a coal fired thermal power plant for components with different membership functions. This is the main contribution of the paper.

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Section: Procedural Steps Of the Presented Tbgflt Techniquementioning

confidence: 99%

Section: A Case Studymentioning

confidence: 99%

“…The system RBD and its fault tree are shown in Figure 4. The failure rate ( λ i ) and repair time ( τ i ) data for its main components are given in Table VII (Panchal and Kumar, 2014).…”

Section: A Case Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fuzzy reliability analysis of the compressor house unit (CHU) system in a coal fired thermal power plant using TBGFLT technique

Komal

2019

IJQRM

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“…Garg and Sharma (2012) purposed a new fuzzy lambda tau approach for analyzing the behaviour of Synthesis unit of a urea plant. Panchal and Kumar (2014) expounded the application of FM based lambda tau methodology for the reliability analysis of Compressor house unit of a coal fired thermal power plant located in northern India. Guimara˜es and Lapa (2007) developed a fuzzy decision support system for criticality rating of risky components of a nuclear power plant.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated framework for behaviour analysis in a process plant

Panchal

Kumar

2016

Journal of Loss Prevention in the Process Industries

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A novel fuzzy‐based structured framework for sustainable operation and environmental friendly production in coal‐fired power industry

Panchal

Chatterjee

Pamučar

et al. 2021

Int J of Intelligent Sys

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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.

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Reliability Analysis of CHU System of Coal Fired Thermal Power Plant Using Fuzzy λ-τ Approach

Cited by 18 publications

References 16 publications

Fuzzy reliability analysis of the compressor house unit (CHU) system in a coal fired thermal power plant using TBGFLT technique

Fuzzy reliability analysis of the compressor house unit (CHU) system in a coal fired thermal power plant using TBGFLT technique

Integrated framework for behaviour analysis in a process plant

A novel fuzzy‐based structured framework for sustainable operation and environmental friendly production in coal‐fired power industry

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