The Research On The Implementation Of Multi-Objective Input-Output Analysis In Process Manufacturing

With the economic globalization and arrival of the era of knowledge-driven economy, it develops gradually for the integrated and intelligent modern integrated manufacture system (CIMS) which pursues the enterprise's whole benefit. The concept of CIMS is expanded to the manufacturing company of the procedure to process production enterprise systematic CIPS. CIPS manages production, plans optimization, management and decision to lead into computer control system, which makes market awareness combine together to control to optimize. It is the inevitable tendency of process industrial automation development. In this paper, the optimization of production planning in large scale process manufacturing is discussed, the model for production planning and the algorithm of optimization is proposed. A cased is presented to demonstrate the effectiveness of the model. The paper is organized as follows: First, we introduce the background of the research, including the overview of current status and problems of current research on the production planning of process manufacturing, and the method that we used in this paper. Second, we apply input and output analysis to the process manufacturing, setup the input and output model of process manufacturing, present the making method of material of input and output analysis table. The application of material input and output analysis table in the analysis of product structure, the proportional analysis of primary production and secondary production, the making and adjustment of production planning are also proposed. Third, we combine the input and output analysis of the process manufacturing to object programming, present the deterministic model of production planning in process manufacturing, setup the fuzzy production planning model in process manufacturing by introduce fuzzy variables. We solve the model using a mixed intelligent algorithm which is a combination of fuzzy simulation, Artificial Neural Network and Genetic Algorithm (GA). Finally, the fuzzy optimization model is applied to a joint steel making enterprise, and an optimal production planning is achieved. The result are given to demonstrate the effectiveness of the approach.