SUPPORT OF THE OPERATIVE PLANNING WITH UTILIZATION OF THE GENETIC ALGORITHMS IN THE ENVIRONMENT OF MICROSOFT EXCEL

1 DAVID Jiří
Co-authors:
1 PLAČEK Tomáš
Institution:
1 VSB - Technical University of Ostrava, Ostrava, Czech Republic, EU, j.david@vsb.cz, tomas.placek@vsb.cz
Conference:
27th International Conference on Metallurgy and Materials, Hotel Voronez I, Brno, Czech Republic, EU, May 23rd - 25th 2018
Proceedings:
Proceedings 27th International Conference on Metallurgy and Materials
Pages:
1961-1967
ISBN:
978-80-87294-84-0
ISSN:
2694-9296
Published:
24th October 2018
Proceedings of the conference were published in Web of Science and Scopus.
Metrics:
18 views / 5 downloads
Abstract

The contribution deals with model of operative scheduling of production on the facility for continuous casting of steels. Starting point for the increase of efficiency of complicated decision-making processes is the transfer to the decision-making based on the exact, scientific knowledge. Increase the exactivity means utilization of modeling and modern methods for problems solving. Modeling is basic methodological resource for solving of complicated problems, application of modern methods for realization of particular phases of model is then basic condition of the successful realization. Production scheduling at continuous casting of steel belongs to group of above mentioned problems. High emphasis is put on the efficiency of the processes with the compliance of the quality of products. It is necessary to search new innovative approaches with utilization of methods of artificial intelligence and knowledge management in this area, too. Model is compatible with INDUSTRY 4.0 concept when it utilizes genetic algorithm for establishing of the smelting plan. Proposed model is based on the model of crystallizer utilization and fatigue which use diagnostics. Utilization of the proposed model consists in the support of smelting planning in the sequences respectively campaigns. Proposed solution allows to find suitable combination of cumulative counts of smelts in the particular clusters after assignment of purposeful function, limiting conditions and residual life of crystallizer in the form of residual conicity change. Proposed model which is realized in MS Excel proposes to the user possible and effective variants of the scheduling of production in the next period according to the specified limited conditions.

Keywords: Metallurgy, continuous casting, mold, control, operative planning, genetic algorithms
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