An Application of Decision Making Grid to Improve Maintenance Strategies in Small and Medium Industries

Burhanuddin, M. A.; Ahmad, Abd Rahman; Desa, Mohammad Ishak

doi:10.1109/iciea.2007.4318450

Cited by 13 publications

(8 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Here, the following strategies were adopted for the decision map; breakdown maintenance (BM), planned preventive maintenance (PPM), condition-based maintenance (CBM), skill level upgrade (SLU), and design out maintenance (DOM), as shown in Fig. 2 [18,44].…”

Section: Processing Procedures For the Proposed Hybrid Modelmentioning

confidence: 99%

Practical Demonstration of a Hybrid Model for Optimising the Reliability, Risk, and Maintenance of Rolling Stock Subsystem

et al. 2021

View full text Add to dashboard Cite

Railway transport system (RTS) failures exert enormous strain on end-users and operators owing to in-service reliability failure. Despite the extensive research on improving the reliability of RTS, such as signalling, tracks, and infrastructure, few attempts have been made to develop an effective optimisation model for improving the reliability, and maintenance of rolling stock subsystems. In this paper, a new hybrid model that integrates reliability, risk, and maintenance techniques is proposed to facilitate engineering failure and asset management decision analysis. The upstream segment of the model consists of risk and reliability techniques for bottom-up and top-down failure analysis using failure mode effects and criticality analysis and fault tree analysis, respectively. The downstream segment consists of a (1) decision-making grid (DMG) for the appropriate allocation of maintenance strategies using a decision map and (2) group decision-making analysis for selecting appropriate improvement options for subsystems allocated to the worst region of the DMG map using the multi-criteria pairwise comparison features of the analytical hierarchy process. The hybrid model was illustrated through a case study for replacing an unreliable pneumatic brake unit (PBU) using operational data from a UK-based train operator where the frequency of failures and delay minutes exceeded the operator’s original target by 300% and 900%, respectively. The results indicate that the novel hybrid model can effectively analyse and identify a new PBU subsystem that meets the operator’s reliability, risk, and maintenance requirements.

show abstract

Section: Processing Procedures For the Proposed Hybrid Modelmentioning

confidence: 99%

Practical Demonstration of a Hybrid Model for Optimising the Reliability, Risk, and Maintenance of Rolling Stock Subsystem

et al. 2021

View full text Add to dashboard Cite

show abstract

“…The DMG model has been used and reported by various researchers such as Fernandez et al [8], Burhanuddin [9], Aslam-Zainudeen, and Labib [10], Shain et al [11], and Tahir et al [12]. All literature have reported considerable saving in terms of minimising downtime and significant maximisation of productivity without having to acquire any additional capacity.…”

Section: The Decision Making Grid (Dmg) Modelmentioning

confidence: 99%

Learning from failures through feedback to design

Labib

2013

Safety and Security Engineering V

View full text Add to dashboard Cite

The paper attempts to define the concept of learning from failures through feedback to design. This is demonstrated through case studies where analytical tools have been incorporated to facilitate problem structuring and analysis. We provide a framework on how to analyze case studies of learning from major disasters. We then provide examples of tools and techniques that are capable of analyzing the rare event of high impact.

show abstract

“…1. Phase I describe the research that has been obtained previously ( [11], [12]). While phase II is the briefly research that described in this paper.…”

Section: Introductionmentioning

confidence: 99%

Using Genetic Algorithm to bridge Decision Making Grid data gaps in Small and Medium Industries

Tahir

Ahmad

Nur

et al. 2014

2014 Makassar International Conference on Electrical Engineering and Informatics (MICEEI)

View full text Add to dashboard Cite

Abstract-Maintenance management is certainly the important factor to support the successfulness of Small and Medium Industries (SMIs). The SMIs will gain larger profits with the correctness of maintenance system which can minimize the expenses incurred. The application with Decision Making Grid (DMG) for appropriate maintenance strategy has been achieved with favorable outcome. However, the problems, i.e. incompleteness, unavailability and inconsistency of data are the common practice gaps in SMIs. The presences of data gaps cause adverse effects on the DMG process which is certainly not able to provide satisfactory results of maintenance strategies. To overcome the problems, the current research applies the most optimal heuristic adaptive methods of Genetic Algorithm (GA) to generate optimal variable values of machine breakdowns from a DMG process on observed SMIs to be processed into other related problematic SMIs. The combination method has produced remarkable validation results against decision-making of maintenance strategies for all machines with the accuracy of 90,81%. The results deliver the trust toward related SMIs with the data problems or even new concerned SMIs with the absences of data to utilize this DMG-GA method for maintenance decision making which can help maintenance personnel by giving the correct selection of the maintenance strategy.Keyword-Small and Medium Industries; Decision Making Grid; Genetic Algorithm; Maintenance decision making. CONCLUSION AND FUTURE WORKSThe research describes the decision making for maintenance machine in Small and Medium Industries with DMG-GA method. The validation of DMG-GA method towards the data of frequency and downtime for all machines have obtained the accuracy of 90,81%. Based on this remarkable result, the system should be utilized to select the correct maintenance strategy for each machine in other related industries or new concerned industry which has the data gaps. Other learning methods such as Neural-Network as well as to increase the system functionality by using distributed computing technology are expected to be embedded on this research to provide more optimal results as well as better performances of the system.

show abstract

An Application of Decision Making Grid to Improve Maintenance Strategies in Small and Medium Industries

Cited by 13 publications

References 10 publications

Practical Demonstration of a Hybrid Model for Optimising the Reliability, Risk, and Maintenance of Rolling Stock Subsystem

Practical Demonstration of a Hybrid Model for Optimising the Reliability, Risk, and Maintenance of Rolling Stock Subsystem

Learning from failures through feedback to design

Using Genetic Algorithm to bridge Decision Making Grid data gaps in Small and Medium Industries

Contact Info

Product

Resources

About