Maintenance modeling tools with special reference to incomplete data
The problem of incomplete maintenance data, the knowledge on how to analyse the data and represent the result in a proper and understandable way are the major difficulty faces by many maintenance engineers during identification and definition of the real maintenance problem. The situation is more di...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English English |
| Published: |
2009
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/15718/1/Maintenance%20Modelling%20Tools%20With%20Special%20Reference%20To%20Incomplete%20Data.pdf http://eprints.utem.edu.my/id/eprint/15718/2/Maintenance%20modeling%20tools%20with%20special%20reference%20to%20incomplete%20data.pdf |
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| Summary: | The problem of incomplete maintenance data, the knowledge on how to analyse the data and represent the result in a proper and understandable way are the major difficulty faces by many maintenance engineers during identification and definition of the real maintenance problem. The situation is more difficult and time consuming without the assistance of operation research (OR) experts. Other related problem that has also been addressed is how well experts estimate the delay time for maintenance modelling, which as consequences either overestimate or underestimate. If these problems could not be solved, the condition causes a wrong maintenance decision and may lead to unforeseen consequences. This research proposes a tool that enhances snapshot model for maintenance problem recognition in order to easily assist maintenance engineers during identification and definition of the real maintenance problem. The proposed tool is a hybrid of failure mode, effect and criticality analysis (FMECA) with decision analysis method embedded into the current snapshot model and implemented in computers environment. This tool aims is ensure and enable maintenance engineers to conduct snapshot modelling with little or without the help of OR experts to facilitate the maintenance problem recognition process. An information technology (IT) tool that improves the accuracy of the delay time data estimates has been also proposed as an enhancement of the subjective survey method. These tools have been tested into Palm Oil Mill (POM) plant machines from three different companies. The result of this particular part of this research shows that the users need more features and less time to facilitate them during identification and definition of the real maintenance problem. The developed tool also satisfies the users in term of ease of use and user friendliness but need a further investigation due to some limitation. The limitation includes the need to enhance the processing speed when building the snapshot model, the accuracy of the result and the decision support technique. For the case of delay time estimates, even though the result of enhancement of the subjective survey method is still varying but the applicability of the method is proven more acceptable when it is compared to the current method. This method also improves the elicitation and calibration process but need a further enhancement. The enhancement includes the need to reduce the involvement of experts during elicitation and calibration process, increase the performance when retrieving the information and improve its consistency. |
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