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Failure Mode and Effect Analysis Based on Probabilistic Linguistic Preference Relations and Gained and Lost Dominance
IEEE Transactions on Cybernetics
|September 6, 2021
Summary
This study introduces a novel Failure Mode and Effect Analysis (FMEA) method using probabilistic linguistic preference relations (PLPRs) and gained and lost dominance score (GLDS). It effectively addresses FMEA limitations by incorporating group and individual risk attitudes for improved risk evaluation.
Area of Science:
- Reliability Engineering
- Risk Management
- Decision Analysis
Background:
- Traditional Failure Mode and Effect Analysis (FMEA) using Risk Priority Number (RPN) faces practical limitations.
- Existing FMEA enhancements often neglect group and individual risk attitudes in evaluations.
Purpose of the Study:
- To develop an advanced FMEA approach that integrates expert risk attitudes.
- To enhance the accuracy and applicability of risk assessment in FMEA.
Main Methods:
- Utilized probabilistic linguistic preference relations (PLPRs) for expert risk evaluation via pairwise comparisons.
- Introduced an extended gained and lost dominance score (GLDS) method to rank failure modes considering diverse risk attitudes.
- Proposed a two-step optimization model for determining risk factor weights with unknown information.
Main Results:
- The new FMEA approach successfully incorporates group and individual risk attitudes.
- The extended GLDS method provides a robust ranking of failure modes.
- A case study on a load-haul-dumper machine validated the method's effectiveness.
Conclusions:
- The proposed FMEA method offers a practical and effective solution for risk evaluation.
- This approach improves upon traditional FMEA by accounting for nuanced expert risk perceptions.
- The integration of PLPRs and GLDS enhances reliability management in complex systems.
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