Next Article in Journal
Silicon Nitride Photonic Integration Platforms for Visible, Near-Infrared and Mid-Infrared Applications
Next Article in Special Issue
Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information
Previous Article in Journal
Millimeter Scale Track Irregularity Surveying Based on ZUPT-Aided INS with Sub-Decimeter Scale Landmarks
Previous Article in Special Issue
A Time-Space Domain Information Fusion Method for Specific Emitter Identification Based on Dempster–Shafer Evidence Theory
Article Menu
Issue 9 (September) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(9), 2086; https://doi.org/10.3390/s17092086

Fuzzy Risk Evaluation in Failure Mode and Effects Analysis Using a D Numbers Based Multi-Sensor Information Fusion Method

School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China
*
Authors to whom correspondence should be addressed.
Received: 30 August 2017 / Revised: 8 September 2017 / Accepted: 11 September 2017 / Published: 12 September 2017
View Full-Text   |   Download PDF [821 KB, uploaded 12 September 2017]   |  

Abstract

Failure mode and effect analysis (FMEA) is a useful tool to define, identify, and eliminate potential failures or errors so as to improve the reliability of systems, designs, and products. Risk evaluation is an important issue in FMEA to determine the risk priorities of failure modes. There are some shortcomings in the traditional risk priority number (RPN) approach for risk evaluation in FMEA, and fuzzy risk evaluation has become an important research direction that attracts increasing attention. In this paper, the fuzzy risk evaluation in FMEA is studied from a perspective of multi-sensor information fusion. By considering the non-exclusiveness between the evaluations of fuzzy linguistic variables to failure modes, a novel model called D numbers is used to model the non-exclusive fuzzy evaluations. A D numbers based multi-sensor information fusion method is proposed to establish a new model for fuzzy risk evaluation in FMEA. An illustrative example is provided and examined using the proposed model and other existing method to show the effectiveness of the proposed model. View Full-Text
Keywords: fuzzy risk evaluation; failure mode and effects analysis; multi-sensor information fusion; D numbers; dempster-shafer evidence theory; fuzzy uncertainty fuzzy risk evaluation; failure mode and effects analysis; multi-sensor information fusion; D numbers; dempster-shafer evidence theory; fuzzy uncertainty
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Deng, X.; Jiang, W. Fuzzy Risk Evaluation in Failure Mode and Effects Analysis Using a D Numbers Based Multi-Sensor Information Fusion Method. Sensors 2017, 17, 2086.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top