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Article
Publication date: 14 November 2019

Ikuobase Emovon and Rosemary Norman

One of the key elements of a maintenance system is risk analysis because the risk level of an engineering system will determine the maintenance policy required. Failure Mode and…

Abstract

Purpose

One of the key elements of a maintenance system is risk analysis because the risk level of an engineering system will determine the maintenance policy required. Failure Mode and Effect Analysis (FMEA) is widely applied in evaluating risk of failure of engineering systems. However, the conventional FMEA used in analyzing risk by most industries has shortcomings such as an inability to utilize imprecise and interval data in prioritizing risk. To overcome these limitations, different variants of FMEA have been reported in the literature. However, these modified approaches are computationally intensive; hence, the purpose of this paper is to develop an efficient FMEA-based methodology that is easy to analyze and implement.

Design/methodology/approach

The proposed technique combines the Taguchi method with FMEA in order to analyze risk of engineering systems easily and effectively. The effectiveness of the approach is demonstrated with a case study of the fuel oil system of a marine diesel engine.

Findings

The results of the integrated Taguchi method and FMEA, when compared with well-known techniques, namely, VIKOR and compromise programming, from the literature are very similar. From the comparative analysis, it was evident that the proposed method is a viable option to the more computationally intensive approaches used in the literature.

Originality/value

The approach proposed is novel and simple and can be implemented more easily than approaches from the literature in analyzing risk.

Details

Journal of Quality in Maintenance Engineering, vol. 26 no. 4
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 16 October 2020

Ikuobase Emovon, Oghenenyerovwho Stephen Okpako and Edith Edjokpa

In most developing countries riveting, upset forging and punching operations among others are performed using manual hammering technique. The use of the manual method increases…

Abstract

Purpose

In most developing countries riveting, upset forging and punching operations among others are performed using manual hammering technique. The use of the manual method increases production time and reduces efficiency. The use of the manual approach is predominantly due to the high cost of imported automated hammering machines (AHM) which the majority of the end-users are incapable of acquiring. The purpose of this paper, therefore, is to produce an AHM that is affordable using an effective material selection methodology in the design and fabrication process.

Design/methodology/approach

The material selection methodology proposed is the fuzzy multi-objective optimisation on the basis of the ratio analysis (MOORA) method. The tool was used to evaluate and determine the optimum material for the major of the components of the AHM from amongst alternative materials while considering several decision criteria. A case study of the shaft was applied to demonstrate the suitability of the proposed technique. The AHM components design is then carried out and machine fabricated and tested to ascertain performance effectiveness.

Findings

The result of the fuzzy MOORA evaluation showed that alloy steel is the optimal material for the shaft. The fuzzy MOORA approach was compared with the fuzzy Vlsekriterijumska Optimizacija Ikompromisno Resenje (VIKOR) and fuzzy grey relational analysis (GRA) methods to validate the proposed method. The fuzzy MOORA method produces completely the same result with the fuzzy VIKOR and fuzzy GRA methods. The machine was then designed, constructed and tested and found to be effective for the purpose of the design.

Originality/value

This is significant as no such study has been published by any other researcher to the best of our knowledge in this area.

Details

World Journal of Engineering, vol. 18 no. 1
Type: Research Article
ISSN: 1708-5284

Keywords

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