An analytical interval fuzzy inference system for risk evaluation and prioritization in failure mode and effect analysis Kerk, Yi Wen, Tay, Kai Meng and Lim, Chee Peng 2017, An analytical interval fuzzy inference system for risk evaluation and prioritization in failure mode and effect analysis, IEEE systems journal, pp. 1-12, doi: 10.1109/JSYST.2015.2478150. Attached Files Name Description MIMEType Size Downloads Title An analytical interval fuzzy inference system for risk evaluation and prioritization in failure mode and effect analysis Author(s) Kerk, Yi Wen Tay, Kai Meng Lim, Chee Peng orcid.org/0000-0003-4191-9083 Journal name IEEE systems journal Start page 1 End page 12 Total pages 12 Publisher IEEE Place of publication Piscataway, N.J. Publication date 2017-05-23 ISSN 1932-8184 1937-9234 Keyword(s) Failure mode and effect analysis (FMEA) inference systems (FISs) interval approach monotonicity property risk analysis Summary 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. Notes In Press Language eng DOI 10.1109/JSYST.2015.2478150 Field of Research 099999 Engineering not elsewhere classified Socio Economic Objective 970110 Expanding Knowledge in Technology HERDC Research category C1 Refereed article in a scholarly journal Copyright notice ©2017, IEEE Persistent URL http://hdl.handle.net/10536/DRO/DU:30089716 Document type: Journal Article Collection: Centre for Intelligent Systems Research Related Links Link Description Connect to Elements publication management system Go to link with your DU access privileges   Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Wed, 30 Nov 2016, 14:17:51 EST Thu, 01 Dec 2016, 04:01:53 EST Thu, 01 Dec 2016, 07:37:49 EST Tue, 06 Jun 2017, 06:03:24 EST Wed, 07 Jun 2017, 10:50:47 EST Wed, 07 Jun 2017, 10:52:57 EST Wed, 07 Jun 2017, 11:41:26 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 2 times in Scopus Search Google Scholar Access Statistics: 11 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Wed, 30 Nov 2016, 14:17:51 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.