Abstract
The paper is concerned with the solution to the problem of planning technological processes for heating and rolling slabs at a mill, aimed at increasing the metallurgical production productivity. The main focus is on creating an optimization model for rolling batches and an intelligent algorithm for optimal planning based on the formation of rolling groups and arranging the heating furnace loading taking into account all technological requirements. Effective planning of loading sheet rolling mills is the key task determining the quality of the finished rolled product and its cost. The rolling plan is an ordered sequence of slabs formed on the basis of multiple orders. This task belongs to the class of complex ones, since when building a plan for consumer orders with different product mix and steel grades, it is necessary to take into account many technological limitations on heating and rolling processes. An additional complexity factor is the need to process large volumes of information. In such conditions, full compliance with all technological requirements for each slab becomes almost impossible. Therefore, when planning, it is necessary to minimize the costs arising from the violation of these requirements. In practice, to load hot rolling mills, specialists use heuristic rules based on the formalization of technological instructions and, as a rule, strive only to reduce the violations number and downtime between slab groups. The scientific novelty lies in the development of an integrated approach to automating planning processes characterized by original models for rolling groups forming, which, unlike existing ones, simultaneously take into account the slab technological parameters and the production schedule dynamics. The paper presents the practical testing results of the developed model for optimal planning of technological processes for heating and rolling slabs at the mill, confirming the reduction in the production cycle duration and equipment downtime. The model allows automating the process of forming rolling groups, increasing the efficiency of loading heating furnaces and reducing equipment downtime.
Keywords
intelligent planning, production process optimization, metal rolling, mathematical modeling, metallurgy
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