Study Of Flow-oriented MES Model And Production Scheduling Optimization

With the continuous development of market economy, the traditional ERP/MRP II has been unable to meet the demands of enterprises whose strategic planning can not keep up with changes of market. To improve the competitiveness of enterprises, MES is one of the hottest study of modern flow process. MES can be used to supervise the production process, refine the production planning and collect production data real-time to pass it to the departments where it's needed. In this way, it can not only improve production efficiency, but also it can increase benefit and improve product quality. MES is an effective measure to integrate enterprise information.The overall scheme of MES model is designed in this paper. In addition, production scheduling, which plays a central role in the MES is discussed. The important contents included are as follows:Based on analyzing characteristics of flow process industry, MES model, combined with international ISA SP95 standards and function model of MESA is built with a standard set of terminology and unified concepts. This model completes distribution of the whole business information to enhance the continuity of each module. Management department can make full use of the production data of each module to analyze production process, as well as to strengthen the production management.By deep study of production scheduling model, complete production scheduling is decomposed into scheduling of mixed crude oil, production equipment scheduling and mediation oil according to characteristics of oil production. By analyzing relational parameters and constrains, three models are built, taking maximum benefit as the overall goal. The effective decomposition can reduce the scale of scheduling model. The three components are mutual interrelated and restraint to realize optimization of whole production process.Mutation operator is introduced to dynamic adjustment of the inertia weight PSO. The algorithm is used to crude oil mixing scheduling model, production equipment scheduling model and oil harmonic scheduling model. The inertia weight is dynamic adjusted with speed and position update of particle. Compared with the particle swarm algorithm, this algorithm improves the convergence rate, finds the optimal solution of the objective function and increases the profits of oil refining enterprises. Examples show the effectiveness of the algorithm.