| Summary: | 碩士 === 國立雲林科技大學 === 工業工程與管理研究所 === 88 === During the normal production run, potentially, factories can experience unexpected conditions like quantity or delivery date changes by customers and mechanical malfunction. At the very moment, if there’s no existing back up production procedure and scheduling, then the production may well be stopped and the delivery schedule will also be delayed.
For solving these kinds of unexpected conditions, this research introduced the “ Dynamic Integrated Product Control System” for coping and integrating both the normal-production-influencing machinery condition and customer orders. And with minimal total production cost as the premise, we set up the production procedure and scheduling based on the Dynamic Integrated Process Planning and Scheduling Algorithm. (DIPS) The DIPS based on the Genetic Algorithm (GA) with dynamic machine and order condition as the control factors to solve for problems in determining production procedures and scheduling. While on the evaluation of performance, this research used the statistical optimization technique for auditing the solution quality of DIPS algorithm. As for the performance evaluation, we conducted a simulation experiment. The performance evaluation indicators were the total cost after production planning and production scheduling and the CPU time. The results had shown great effects in both the solution quality and performance evaluation
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