A fuzzy TOPSIS and Rough Set based approach for mechanism analysis of product infant failure

He, Yihai; Wang, Linbo; He, Zhenzhen; Xie, Min

doi:10.1016/j.engappai.2015.06.002

Cited by 84 publications

(30 citation statements)

References 41 publications

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“…According to Equations (1)- (5), all imprecise preference are converted into stochastic beta comparisons, as shown in Table 4. Then, these stochastic pairwise comparisons are converted into precise ones by using Equations (6)- (8). The comparison with precise matrix for elements in the criteria level is shown in Table 5.…”

Section: Determine the Evaluation Criteria Weights Based On The Stochmentioning

confidence: 99%

Performance Evaluation for Sustainability of Strong Smart Grid by Using Stochastic AHP and Fuzzy TOPSIS Methods

Zhao

2016

Sustainability

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Abstract:As an efficient way to deal with the global climate change and energy shortage problems, a strong, self-healing, compatible, economic and integrative smart gird is under construction in China, which is supported by large amounts of investments and advanced technologies. To promote the construction, operation and sustainable development of Strong Smart Grid (SSG), a novel hybrid framework for evaluating the performance of SSG is proposed from the perspective of sustainability. Based on a literature review, experts' opinions and the technical characteristics of SSG, the evaluation model involves four sustainability criteria defined as economy, society, environment and technology aspects associated with 12 sub-criteria. Considering the ambiguity and vagueness of the subjective judgments on sub-criteria, fuzzy TOPSIS method is employed to evaluate the performance of SSG. In addition, different from previous research, this paper adopts the stochastic Analytical Hierarchy Process (AHP) method to upgrade the traditional Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) by addressing the fuzzy and stochastic factors within weights calculation. Finally, four regional smart grids in China are ranked by employing the proposed framework. The results show that the sub-criteria affiliated with environment obtain much more attention than that of economy from experts group. Moreover, the sensitivity analysis indicates the ranking list remains stable no matter how sub-criteria weights are changed, which verifies the robustness and effectiveness of the proposed model and evaluation results. This study provides a comprehensive and effective method for performance evaluation of SSG and also innovates the weights calculation for traditional TOPSIS.

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Section: Determine the Evaluation Criteria Weights Based On The Stochmentioning

confidence: 99%

Performance Evaluation for Sustainability of Strong Smart Grid by Using Stochastic AHP and Fuzzy TOPSIS Methods

Zhao

2016

Sustainability

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show abstract

“…Sundarkumar and Ravi (2015) considered dataset balancing in customer credit card churn prediction. He et al (2016) used fuzzy TOPSIS and rough sets for new product failure analysis. Krishna and Ravi (2016) used evolutionary computer in support of customer relationship management.…”

Section: Journal Risk Management Applicationsmentioning

confidence: 99%

Artificial intelligence in engineering risk analytics

Olson

Dolgui

2017

Engineering Applications of Artificial Intelligence

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“…Compute the improved score function-based separation measures in intuitionistic fuzzy environment and for each alternative from the positive ideal and negative ideal solutions using the equation (13) and (14); (13) Similarly, (14) Step 7. Compute the relative closeness coefficient, (CC i ), which is defined to rank all possible alternatives with respect to the positive ideal solution A + .…”

Section: Tab I Intuitionistic Fuzzy Numbers For Approximating the Lmentioning

confidence: 99%

“…While He et al [14], using Fuzzy TOPSIS and Rough set based approach identifies product infant failures that are most critical to improving product quality. By breaking down the early fault symptoms identified into root causes of critical functional parameters in the function domain, design parameters in the physical domain and process parameters in the manufacturing domain.…”

Section: Introductionmentioning

confidence: 99%

Application of Intuitionistic Fuzzy Topsis Model for Troubleshooting an Offshore Patrol Boat Engine

Aikhuele

Sorooshian

Ansah

et al. 2017

Polish Maritime Research

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In this paper, an Intuitionistic Fuzzy TOPSIS model which is based on a score function is proposed for detecting the root cause of failure in an Offshore Boat engine, using groups of expert's opinions. The study which has provided an alternative approach for failure mode identification and analysis in machines, addresses the machine component interaction failures which is a limitation in existing methods. The results from the study show that although early detection of failures in engines is quite difficult to identify due to the dependency of their systems from each other. However, with the Intuitionistic Fuzzy TOPSIS model which is based on an improved score function such faults/failuresare easily detected using expert's based opinions.

show abstract

A fuzzy TOPSIS and Rough Set based approach for mechanism analysis of product infant failure

Cited by 84 publications

References 41 publications

Performance Evaluation for Sustainability of Strong Smart Grid by Using Stochastic AHP and Fuzzy TOPSIS Methods

Performance Evaluation for Sustainability of Strong Smart Grid by Using Stochastic AHP and Fuzzy TOPSIS Methods

Artificial intelligence in engineering risk analytics

Application of Intuitionistic Fuzzy Topsis Model for Troubleshooting an Offshore Patrol Boat Engine

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