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Qing-Lian Lin
Researcher at Technical University of Berlin
Publications - 11
Citations - 1090
Qing-Lian Lin is an academic researcher from Technical University of Berlin. The author has contributed to research in topics: Fuzzy logic & Failure mode and effects analysis. The author has an hindex of 11, co-authored 11 publications receiving 936 citations. Previous affiliations of Qing-Lian Lin include Xiamen University.
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Failure mode and effects analysis using D numbers and grey relational projection method
TL;DR: A new risk priority model is proposed for the risk evaluation in FMEA based on a more effective representation of uncertain information, called D numbers, and an improved grey relational analysis method, grey relational projection (GRP), which is used to determine the risk priority order of the failure modes.
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Fuzzy Failure Mode and Effects Analysis Using Fuzzy Evidential Reasoning and Belief Rule-Based Methodology
TL;DR: A new risk priority model for prioritizing failures in failure mode and effects analysis (FMEA) on the basis of fuzzy evidential reasoning (FER) and belief rule-based (BRB) methodology is proposed to resolve some of the shortcomings in fuzzy FMEA approaches.
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Knowledge Acquisition and Representation Using Fuzzy Evidential Reasoning and Dynamic Adaptive Fuzzy Petri Nets
TL;DR: A knowledge acquisition and representation approach using the fuzzy evidential reasoning approach and dynamic adaptive FPNs to solve the problems of domain experts' diversity experience and reason the rule-based knowledge more intelligently is presented.
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Risk assessment in system FMEA combining fuzzy weighted average with fuzzy decision-making trial and evaluation laboratory
TL;DR: A new risk assessment methodology combining fuzzy weighted average with fuzzy decision-making trial and evaluation laboratory (fuzzy DEMATEL) is proposed in this article to rank the risk of failures in system FMEA.
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Human reliability assessment for medical devices based on failure mode and effects analysis and fuzzy linguistic theory
TL;DR: F fuzzy linguistic theory is applied to convert the subjective cognition of experts into an information entity to obtain the numerical values of risk factors in failure modes and effects analysis.