Model-based Production Control

Business environment demands an instant replay to different influences that appear in the production process and in the global market. The synthesis of plant-wide control structures is recognized as one of the most important production-management design problems in the process industries. To develop a production control system, in appropriate model of the production process is needed to evaluate the various control strategies. Within the model different production Key Performance Indicators (KPIs) can be identified which are used to extract the relevant information about the state of the production process. The control systems ill production plants tire structured hierarchically into several levels, Closed-loop control at the production-management level using production KPIs as controlled variables was implemented. In this article, the simulation model of a polymerization production plant is presented. The plant call lie controlled by its input variables, which are Production speed, Raw materials' quality and Batch schedule and the efficiency of the production is determined based oil three characteristic KPIs: Productivity, Mean product quality and Mean production costs. These KPIs arc used to control the process of the procedural model. To help the manager with the decisions a model predictive controller (MPC) was used. With the controller it is assured to keep Productivity and Mean product quality indicators at the defined set-points. Preliminary results show the usefulness of the proposed methodology.