Industrial machine allocation using rulebased knowledge representation technique
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Date
2010
Authors
Wan Remeli, Wan Nur Akmal
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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.