Summary: | 碩士 === 國立交通大學 === 工業工程與管理學系 === 98 === When market demands changes periodically, the product mix in production system will be varied. This situation makes production planning more difficult since the stability of schedule is losing while the variance of performance is increasing. Therefore, this thesis constructs a production scheduling system for TFT-LCD array factory under demand change environment. To determine the daily release plan and to allocate the capacity of bottleneck workstation, the master production schedule module and production performance estimation module are included in the system.
The duty of MPS module is to determine daily release type, quantity and sequence of products, and to estimate layer flow time of each product type. The initial value of layer flow time is set as that of last planning period. Based on this value, each lot either being work-in-process or planning to release will be projected the time arriving at bottleneck workstation according to its layer numbering at the beginning of a day. With such information, for minimizing the variation among daily release quantities, daily loading of the bottleneck workstation, as well as minimizing the unmet demands, an IP/LP model is built to solve the release plan under of capacity constraints. Then, base on the daily release amount and the quantity of initial WIP, the capacity load of bottleneck workstation is allocated to each machine group and then to each machine unit with consideration of the constraints related to process capability, quantity of available masks and the reentry times needed for each product type. IP/LP models are developed to minimize the variability among utilization rates of bottleneck machines.
Given the utilization rate of bottleneck workstation, the utilization rate of each non-bottleneck workstation can be derives by solving Jackson network and the flow time of each workstation can be estimated by using Conway’s formula. Then, each layer flow time can be estimated so as to calculate the difference between it and its corresponding initial value. If the error is larger then 2%, we will execute the MPS module again. Once the recursive revision is done, we will execute production performance estimate module to calculate the flow time for each product type and the optimal quantity of WIP to ensure that the MPS is practicable in the shop floor.
The case study reveals that compared with the simulation results, the average estimation error of production flow time is about 4.5% when release rule being uniform loading (UL); moreover, the average error is about 2% when adopting CONWIP release rule. In addition, the system throughput rate is about 100% achieved. Hence, the production scheduling system proposed in this thesis can be applied to the environment with demands being periodically changed.
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