An Analytical Interval Fuzzy Inference System for Risk Evaluation and Prioritization in Failure Mode and Effect Analysis
The fuzzy inference system (FIS) is useful for developing an improved Risk Priority Number (RPN) model for risk evaluation in failure mode and effect analysis (FMEA). A general FIS_RPN model considers three risk factors, i.e., severity, occurrence, and detection, as the inputs and produces an FIS_RP...
| Main Author: | |
|---|---|
| Format: | Article |
| Published: |
IEEE
2015
|
| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/10455/ |
| _version_ | 1848836782956740608 |
|---|---|
| author | Tay, Kai Meng |
| author_facet | Tay, Kai Meng |
| author_sort | Tay, Kai Meng |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | The fuzzy inference system (FIS) is useful for developing an improved Risk Priority Number (RPN) model for risk evaluation in failure mode and effect analysis (FMEA). A general FIS_RPN model considers three risk factors, i.e., severity, occurrence, and detection, as the inputs and produces an FIS_RPN score as the output. At present, there are two issues pertaining to practical implementation of classical FIS_RPN models as follows: 1) the fulfillment of the monotonicity property between the FIS_RPN score (output) and the risk factors (inputs); and 2) difficulty in obtaining a complete and monotone fuzzy rule base. The aim of this paper is to propose a new analytical interval FIS_RPN model to solve the aforementioned issues. Specifically, the incomplete and potentially nonmonotone fuzzy rules provided by FMEA users are transformed into a set of interval-valued fuzzy rules in order to produce an interval FIS_RPN model. The interval FIS_RPN model aggregates a set of risk ratings and produces a risk interval, which is useful for risk evaluation and prioritization. Properties of the proposed interval FIS_RPN model are analyzed mathematically. An FMEA procedure that incorporates the proposed interval FIS_RPN model is devised. A case study with real information from a semiconductor company is conducted to evaluate the usefulness of the proposed model. The experimental results indicate that the interval FIS_RPN model is able to appropriately rank the failure modes, even when the fuzzy rules provided by FMEA users are incomplete and nonmonotone. |
| first_indexed | 2025-11-15T06:29:15Z |
| format | Article |
| id | unimas-10455 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| last_indexed | 2025-11-15T06:29:15Z |
| publishDate | 2015 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-104552017-04-12T02:37:49Z http://ir.unimas.my/id/eprint/10455/ An Analytical Interval Fuzzy Inference System for Risk Evaluation and Prioritization in Failure Mode and Effect Analysis Tay, Kai Meng Q Science (General) TA Engineering (General). Civil engineering (General) The fuzzy inference system (FIS) is useful for developing an improved Risk Priority Number (RPN) model for risk evaluation in failure mode and effect analysis (FMEA). A general FIS_RPN model considers three risk factors, i.e., severity, occurrence, and detection, as the inputs and produces an FIS_RPN score as the output. At present, there are two issues pertaining to practical implementation of classical FIS_RPN models as follows: 1) the fulfillment of the monotonicity property between the FIS_RPN score (output) and the risk factors (inputs); and 2) difficulty in obtaining a complete and monotone fuzzy rule base. The aim of this paper is to propose a new analytical interval FIS_RPN model to solve the aforementioned issues. Specifically, the incomplete and potentially nonmonotone fuzzy rules provided by FMEA users are transformed into a set of interval-valued fuzzy rules in order to produce an interval FIS_RPN model. The interval FIS_RPN model aggregates a set of risk ratings and produces a risk interval, which is useful for risk evaluation and prioritization. Properties of the proposed interval FIS_RPN model are analyzed mathematically. An FMEA procedure that incorporates the proposed interval FIS_RPN model is devised. A case study with real information from a semiconductor company is conducted to evaluate the usefulness of the proposed model. The experimental results indicate that the interval FIS_RPN model is able to appropriately rank the failure modes, even when the fuzzy rules provided by FMEA users are incomplete and nonmonotone. IEEE 2015 Article PeerReviewed Tay, Kai Meng (2015) An Analytical Interval Fuzzy Inference System for Risk Evaluation and Prioritization in Failure Mode and Effect Analysis. IEEE Systems journal (99). pp. 1-12. ISSN 1932-8184 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&tp=&arnumber=7287737 DOI: 10.1109/JSYST.2015.2478150 |
| spellingShingle | Q Science (General) TA Engineering (General). Civil engineering (General) Tay, Kai Meng An Analytical Interval Fuzzy Inference System for Risk Evaluation and Prioritization in Failure Mode and Effect Analysis |
| title | An Analytical Interval Fuzzy Inference System for Risk Evaluation and Prioritization in Failure Mode and Effect Analysis |
| title_full | An Analytical Interval Fuzzy Inference System for Risk Evaluation and Prioritization in Failure Mode and Effect Analysis |
| title_fullStr | An Analytical Interval Fuzzy Inference System for Risk Evaluation and Prioritization in Failure Mode and Effect Analysis |
| title_full_unstemmed | An Analytical Interval Fuzzy Inference System for Risk Evaluation and Prioritization in Failure Mode and Effect Analysis |
| title_short | An Analytical Interval Fuzzy Inference System for Risk Evaluation and Prioritization in Failure Mode and Effect Analysis |
| title_sort | analytical interval fuzzy inference system for risk evaluation and prioritization in failure mode and effect analysis |
| topic | Q Science (General) TA Engineering (General). Civil engineering (General) |
| url | http://ir.unimas.my/id/eprint/10455/ http://ir.unimas.my/id/eprint/10455/ http://ir.unimas.my/id/eprint/10455/ |