Industrial machine allocation using rulebased knowledge representation technique
| dc.contributor.author | Wan Remeli, Wan Nur Akmal | |
| dc.date.accessioned | 2015-05-21T08:10:39Z | |
| dc.date.available | 2015-05-21T08:10:39Z | |
| dc.date.issued | 2010 | |
| dc.description.abstract | Machine allocation is a complex problem in manufacturing industry. There is a need for some tools to aid the production line managers in deciding which machine will be used in the different processes in manufacturing. The objective of this research is to provide a Decision Support System (DSS) to help those managers in canying out that specific task. Currently it is done manually which time is consuming and dependent on the line manager's expertise and experience. This research describes the development of a rule based DSS which will make their task easier by providing the options of possible machines to be selected. One of the most important steps in DSS is to 'acquire knowledge from "experts on what are the criteria that they consider in allocating machines. Interview sessions with the expert are conducted as the knowledge acquisition method. It is found that machine availability, machine productivity and processing times are the factors that affect the machine allocation problem. The rules are implemented in the proposed DSS in the attempt to provide alternatives solution in deciding machine allocation. It is beneficial for the management in the manufacturing industry to have this decision support system as it can make the machine allocation decision more efficiently and within a shorter time period. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/667 | |
| dc.language.iso | en | en_US |
| dc.title | Industrial machine allocation using rulebased knowledge representation technique | en_US |
| dc.type | Thesis | en_US |
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