Abstract
The electronics industry in Taiwan is flourishing in recent years, and it is increased demand for electronic chemicals which are high degree of purity, few-particle and required in the manufacturing process in the electronics industry. There are complex production constraints in electronic chemicals production, including production capacity, manpower, raw materials, packaging materials and other restrictions. Because of the electronics industry puts a high premium on product delivery, the electronic chemicals be delivered on time or not would be a important target of scheduling in the electronic chemical industry. The study aims to develop a multi-stage production planning and scheduling model for the electronic chemical industry. It concludes a mixed-integer linear programming based on time slot to clarify the production constraints in electronic chemical industry, and a genetic algorithm with local search to find the optimal solution which has the most jobs delivered on time of scheduling problem. The study cooperates with an electronic chemical industry in Taoyuan for an empirical research. We use model of this study to get the schedulings in the different 12 scenarios, and evaluate schedulings by the targets which electronic chemical industry attaches importance to the scheduling. And we can also find the model of this study is useful in all of the scenarios and ensure the validity of the study. Even in the hard production situation, the model can produce 99.8 percents of jobs and at least 87.7% of jobs would be delivered on time in the planning horizon.