Producing Scheduling Management System For Electronic Manufacture Company

Through the implement of producing plan, producing scheduling is to arrange the whole processing orders to meet producing goals. The optimization of scheduling could reduce productions’ processing cycle, increase equipment’s utilization and enterprise’s management skills, which helps enterprises to save producing costs and create greater economic benefits. Because there are many restraints of this problem, the research of job shop scheduling (JSSP) optimization becomes a problem for solving complex non-deterministic polynomials.In order to solve the scheduling optimization problem for an electronic manufacturer, a producing scheduling management method and batch producing pattern are proposed for its intelligent manufacturing. After data preprocessing of the original producing speed data, the data of production time per unit is obtained. By studying traditional job shop problem, basic assumptions and restraints are proposed to simplify the problem, then the model of minimizing production cycle is established. Genetic algorithm (GA) is used to solve this problem, and coding method based on process is designed to satisfy constraint conditions and ensures feasible solutions. A combination selection mechanism of roulette wheel and elite competition effectively ensures convergence during optimization. Experiment result shows that comparing to FIFO and FILO scheduling method, which are now used by the company, genetic algorithm could be well used for solving scheduling problem and the best number of producing batch is given for company’s reference.Based on the ERP system structure, the producing scheduling management system is designed and developed. The descriptions of the system’s functions, relationships between database tables and E-R figure of database principals are explained in this paper. The scheduling management system is now used in an electronic manufacture, which effectively helps company to arrange producing time, and has significance for company’s making producing plans and scheduling decisions and realizing intelligent manufacturing.