Linear programming for production planning of flat panel display
Production planning of flat panel displays is having a great importance to Malaysia from two perspectives: academic and industrial. From the academic perspective, work that fulfills local industry requirements has not been found. From the perspective of local flat panel display manufacturing industr...
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| Format: | Thesis |
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| Language: | English |
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| Online Access: | http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72600/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72600/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72600/4/Khaled%20Mohammed%20Husin.pdf |
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| Summary: | Production planning of flat panel displays is having a great importance to Malaysia from two perspectives: academic and industrial. From the academic perspective, work that fulfills local industry requirements has not been found. From the perspective of local flat panel display manufacturing industry, the industry is facing greater difficulties in the world market due to the lack of techniques in production planning, causing it to lag behind the competition. This dissertation looks into developing appropriate models to be used in production planning of local flat panel display manufacturers. Three models have been suggested to be used by local companies, whereby the models take into account requirements based on linear programming techniques. The models developed cover aggregate production planning, piecewise cost functions directed towards forecasting under fuzzy environment conditions, and a material requirement plan. Results from the implementation of the models on three industries (A, B, C) are compared with existing methods used in the industries. The results indicated that in stable (deterministic) conditions, an aggregate production plan can be obtained by a linear programming model (model 1), while in a fuzzy environment, a better aggregate production plan can be obtained by piecewise linear production cost functions model (model 2) which is more flexible than the linear programming model (model 1). The cost of production, when model 1 was used, dropped by 34%, while the cost, when using model 2, dropped between 28% - 40% compared to actual factory costs. |
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