The Research And Application Of Production Planning System Based On MES For Special-Steel Enterprise

With the application of the information technology in the manufacturing industries, the informational system is becoming a trend for the enterprise's development. The production of special-steel enterprise itself has both discrete and continuous characteristics whose process is complex, while numerous species of the products and few amounts make the production planning management harder. Making production plan is totally depend on orders because there is no linkage between the ERP system and the plant automatically control system, so the manager can't decide in time. To improve the production planning management, a practical production planning system which integrates with other systems is required.The main contents of the paper are as follows:(1) Based on the research of production management problems of special-steel enterprise, combined advanced management theories such as MES, ERP, the paper brings forward a production planning strategy based on MES.(2) According to the theories described above, this paper builds integrated production planning management model which includes three levels: enterprise planning, monthly plant planning, daily plant planning.(3) Using the Unified Modeling Language (UML) this paper designs the system functions and the four main function structures of the production planning management system.(4) Appling the three-level production planning model and according to real conditions and characteristics of the enterprise, adopting the J2EE 4-tier architecture, the production planning management system for Northeast Special Steel Group is developed.The production planning management system provided in this paper is based on the advantaged management theories, which can meet the practical requirements of the enterprise and solve the problems in making the production planning. Through the implement, the production planning is made correctly. And this system integrates the enterprise and the plants, therefore, the cost of production is reduced and the decision of enterprise management is more effective.