Developing a 3D decision making grid based on failure modes and effects analysis with a case study in the steel industry
Research output: Contribution to journal › Article
Design/methodology/approach - In a comparison between DMG and Failure Modes and Effects analysis (FMEA), severity has been assumed as time to repair and occurrence as the frequency of failure. Detection rate has been added as the third dimension of DMG. Nine months data of 21 equipment of casting unit of Mobarakeh Steel Company (MSC) has been analyzed. Then, appropriate condition monitoring (CM) techniques and maintenance tactics have been suggested. While in 2D DMG, CM is used when downtime is high and frequency is low, its application has been developed for other maintenance tactics in a 3D DMG.
Findings - Findings indicate that the results obtained from the developed DMG are different from conventional grid results, and it is more capable in suggesting maintenance tactics according to the operating conditions of equipment.
Research limitations/implications – In failure detection, the influence of CM techniques is different. In this paper, CM techniques have been suggested based on their maximum influence on failure detection.
Originality/Value - In conventional decision making grid (DMG), failure detection rate is not included. The developed 3D-DMG provides this advantage by considering a new axis of detection rate in addition to MTTR and failure frequency and enhances maintenance decision making by simultaneous selection of suitable maintenance tactics and condition monitoring techniques.
|Journal||International Journal of Quality & Reliability Management|
|Early online date||26 Aug 2020|
|Publication status||Early online - 26 Aug 2020|
- LABIB_2020_cright_Developing a 3D Decision Making Grid Based on Failure Modes and Effects Analysis With a Case Study in the Steel Industry
Rights statement: Shahin, A., Labib, A., Haj Shirmohammadi, A. and Balouei Jamkhaneh, H. (2020), "Developing a 3D decision-making grid based on failure modes and effects analysis with a case study in the steel industry", International Journal of Quality & Reliability Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJQRM-03-2019-0096. Copyright © 2020, Emerald Publishing Limited. All rights reserved.
Accepted author manuscript (Post-print), 1.47 MB, PDF document