A New Two-Stage Fuzzy Inference System-Based Approach to Prioritize Failures in Failure Mode and Effect Analysis

QR Code

A New Two-Stage Fuzzy Inference System-Based Approach to Prioritize Failures in Failure Mode and Effect Analysis

This paper presents a new Fuzzy Inference System (FIS)-based Risk Priority Number (RPN) model for the prioritization of failures in Failure Mode and Effect Analysis (FMEA). In FMEA, the monotonicity property of the RPN scores is important. To maintain the monotonicity property of an FIS-based RPN mo...

Full description

Bibliographic Details
Main Authors:	Tze, Ling Jee, Kai, Meng Tay, Chee, Peng Lim
Format:	Article
Language:	English
Published:	Institute of Electrical and Electronics Engineers Inc. 2015
Subjects:	T Technology (General)
Online Access:	http://ir.unimas.my/id/eprint/14847/ http://ir.unimas.my/id/eprint/14847/1/NO%208%20A%20New%20Two-Stage%20Fuzzy%20Inference%20System%20-%20abstrak.pdf

Similar Items

A New Two-Stage Fuzzy Inference System-Based Approach to Prioritize Failures in Failure Mode and Effect Analysis
by: Tay, Kai Meng, et al.
Published: (2015)

An Analytical Interval Fuzzy Inference System for Risk Evaluation and Prioritization in Failure Mode and Effect Analysis
by: Tay, Kai Meng
Published: (2015)

On fuzzy inference system based failure mode and effect analysis (FMEA) methodology
by: Tay, Kai Meng
Published: (2009)

Enhancing a Fuzzy Failure Mode and Effect Analysis methodology with an Analogical Reasoning Technique
by: Tze, Ling Jee, et al.
Published: (2011)

A perceptual computing-based method to prioritize failure modes in failure mode and effect analysis and its application to edible bird nest farming
by: Kok, Chin Chai, et al.
Published: (2016)

A new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems
by: Kai, Meng Tay, et al.
Published: (2013)

Clustering and visualization of failure modes using an evolving tree
by: Tay, Kai Meng, et al.
Published: (2015)

A New Framework With Similarity Reasoning and Monotone Fuzzy Rule Relabeling for Fuzzy Inference Systems
by: Tay, Kai Meng, et al.
Published: (2013)

A non-linear programming-based similarity reasoning scheme for modelling of monotonicity-preserving multi-input fuzzy inference systems
by: Kai, Meng Tay, et al.
Published: (2012)

Building Fuzzy Inference Systems with Similarity Reasoning: NSGA II-based Fuzzy Rule Selection and Evidential Functions
by: Tze, Ling Jee, et al.
Published: (2014)

Application of the fuzzy failure mode and effect analysis methodology to edible bird nest processing
by: Tay, K.M, et al.
Published: (2013)

Enhancing a Fuzzy Inference System-Based Criterion-referenced Assessment with an Analogical Reasoning Schema
by: Tze, Ling Jee, et al.
Published: (2012)

Clustering and visualization of failure modes using an evolving tree
by: Wui, Lee Chang, et al.
Published: (2015)

Optimization of Gaussian Fuzzy Membership Functions and Evaluation of the Monotonicity Property of Fuzzy Inference Systems
by: Kai, Meng Tay, et al.
Published: (2011)

A clustering-based failure mode and effect analysis model and its application to the edible bird nest industry
by: Tay, Kai Meng, et al.
Published: (2015)

A fuzzy inference system-based criterion-referenced assessment model
by: Kai, Meng Tay, et al.
Published: (2011)

A New Fuzzy Ratio and Its Application to the Single Input Rule Modules Connected Fuzzy Inference System
by: Chian, Haur Jong, et al.
Published: (2014)

Monotone Fuzzy Rule Relabeling for the Zero-Order TSK Fuzzy Inference System
by: Tay, Kai Meng, et al.
Published: (2016)

Application of self-organizing map to failure modes and effects analysis methodology
by: Chang, Wuilee, et al.
Published: (2017)

On the Use of Fuzzy Inference Techniques in Assessment Models: Part I: Theoretical Properties
by: Tay, Kai Meng, et al.
Published: (2008)

Single-Input-Rule-Modules connected fuzzy inference system and its applications to failure mode and effect analysis
by: Jong, Chian Haur
Published: (2015)

Interval-based and fuzzy set-based approaches to modeling of fuzzy inference systems with the local monotonicity property
by: Chin, Ying Teh, et al.
Published: (2013)

Clustering and visualization of failure modes using an evolving tree
by: Tay, km
Published: (2015)

The Monotonicity And Sub-Additivity Properties Of Fuzzy Inference Systems And Their Applications
by: Tay , Kai Meng
Published: (2011)

Multi-stage Prediction of Bearing Failure
by: Lim, Adrian Jern Ee
Published: (2019)

An integrated approach for fuzzy failure modes and effects analysis using fuzzy AHP and fuzzy MAIRCA
by: Boral, Soumava, et al.
Published: (2020)

Failure mode and effects analysis based on fuzzy utility cost estimation
by: Dong, Chensong
Published: (2007)

Monotonicity preserving SIRMs-connected fuzzy inference systems with a new monotonicity index: Learning and tuning
by: See, Hung Lau, et al.
Published: (2013)

On the Use of Fuzzy Inference Techniques in Assessment Models: Part II: Industrial Applications
by: Tay, Kai Meng, et al.
Published: (2008)

Potential Failure Mode In Pergau Spillway
by: Mohd Zaini, Mohamad Zulhisyam
Published: (2022)

Fuzzy inference and multi-criteria decision making applications in pavement rehabilitation prioritization
by: Moazami, Danial, et al.
Published: (2010)

A New Monotonicity Index for Fuzzy Rule-based Systems
by: Lie, Meng Pang, et al.
Published: (2014)

A new dempster-shafer theory-based method with fuzzy targets for fuzzy sets ranking
by: Kok, Chin Chai, et al.
Published: (2013)

Failure assessment : comparison of the failure mode between OPC mic and fiber mix concrete slab
by: Cheng, Kam Hao
Published: (2012)

A new fuzzy peer assessment methodology for cooperative learning of students
by: Tay, Kai Meng, et al.
Published: (2015)

Diabetic ketoacidosis in end stage renal failure patient on maintenance dialysis – key challenges in management
by: Lim, Xue Meng, et al.
Published: (2020)

Parametric and nonparametric inference for partly interval-censored failure time data
by: Mohammad Alharpy, Azzah
Published: (2013)

Integrating Statistical Techniques With The Reliability Engineering Methodology Of 'Failure Mode And Effects Analysis' For Continuous Improvement Of Manufacturing Processes.
by: Abdul Aziz, Zalina, et al.
Published: (2003)

Age-specific diastolic dysfunction improves prediction of symptomatic heart failure by Stage B heart failure
by: Coller, J.M., et al.
Published: (2019)

Determining the probability of failure modes by fault tree analysis
by: Bujna, Marián, et al.
Published: (2023)