Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
System failure engineering and fuzzy methodology: an introductory overview
Fuzzy Sets and Systems - Special issue on fuzzy methodology in system failure engineering
Architecture-based approach to reliability assessment of software systems
Performance Evaluation
A fuzzy scheme for failure mode screening
Fuzzy Sets and Systems
Petri Net Theory and the Modeling of Systems
Petri Net Theory and the Modeling of Systems
Fuzzy inference to risk assessment on nuclear engineering systems
Applied Soft Computing
Robotics and Computer-Integrated Manufacturing
Supply chain integration in vendor-managed inventory
Decision Support Systems
Architecture-based software reliability modeling
Journal of Systems and Software
Risk prioritization in failure mode and effects analysis under uncertainty
Expert Systems with Applications: An International Journal
Review: Risk evaluation approaches in failure mode and effects analysis: A literature review
Expert Systems with Applications: An International Journal
A novel general approach to evaluating the reliability of gas turbine system
Engineering Applications of Artificial Intelligence
A non-linear fuzzy regression for estimating reliability in a degradation process
Applied Soft Computing
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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The main objective of the article is to permit the reliability analyst's/engineers/managers/practitioners to analyze the failure behavior of a system in a more consistent and logical manner. To this effect, the authors propose a methodological and structured framework, which makes use of both qualitative and quantitative techniques for risk and reliability analysis of the system. The framework has been applied to model and analyze a complex industrial system from a paper mill. In the quantitative framework, after developing the Petrinet model of the system, the fuzzy synthesis of failure and repair data (using fuzzy arithmetic operations) has been done. Various system parameters of managerial importance such as repair time, failure rate, mean time between failures, availability, and expected number of failures are computed to quantify the behavior in terms of fuzzy, crisp and defuzzified values. Further, to improve upon the reliability and maintainability characteristics of the system, in depth qualitative analysis of systems is carried out using failure mode and effect analysis (FMEA) by listing out all possible failure modes, their causes and effect on system performance. To address the limitations of traditional FMEA method based on risky priority number score, a risk ranking approach based on fuzzy and Grey relational analysis is proposed to prioritize failure causes.