Intelligent Optimization-Based Production Planning and Simulation Analysis for Steelmaking and Continuous Casting Process

Abstract

Aiming at the limitations of the traditional mathematical model for production planning, a novel optimization model is proposed to improve the efficiency and performance for production planning in steelmaking and continuous casting (SCC) process. The optimization model combined with parallel-backward inferring algorithm and genetic algorithm is described. To analyze and evaluate the production plans, a simulation model based on cellular automata is presented. And then, the integrated system including the production plan optimization model and the simulation model is introduced to evaluate and adjust the production plan on-line. The test with production data in a steel plant shows that the optimization model demonstrates ability to deal with time uncertainty in production planning and to set up a conflict-free production plan, and the integrated system provides a useful tool for dynamically drawing and adjusting a production plan on-line. The average staying time of the production plan is about 5% shorter than that in a practical process.