Fuel Costs Minimization on a Steel Billet Reheating Furnace Using Genetic Algorithms
| Autor: | Paulo Eduardo Maciel de Almeida, Rodrigo T. N. Cardoso, Harley S. O. Santos |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Engineering Engineering drawing Article Subject business.industry 020208 electrical & electronic engineering General Engineering 02 engineering and technology lcsh:QA75.5-76.95 Computer Science Applications Nonlinear optimization problem Computational simulation 020901 industrial engineering & automation Fuel cost Modeling and Simulation Thermal 0202 electrical engineering electronic engineering information engineering Fuel efficiency Production (economics) Minification lcsh:Electronic computers. Computer science Process engineering business Reduction (mathematics) |
| Zdroj: | Modelling and Simulation in Engineering, Vol 2017 (2017) |
| ISSN: | 1687-5591 |
| DOI: | 10.1155/2017/2731902 |
| Popis: | Metallurgy industries often use steel billets, at a proper temperature, to achieve the desired metallurgical, mechanical, and dimensional properties of manufactured products. Optimal operation of steel billet reheating furnaces requires the minimization of fuel consumption while maintaining a homogeneous material thermal soak. In this study, the operation of a reheating furnace is modeled as a nonlinear optimization problem with the goal of minimizing fuel cost while satisfying a desired discharge temperature. For this purpose, a genetic algorithms approach is developed. Computational simulation results show that it is possible to minimize costs for different charge temperatures and production rates using the implemented method. Additionally, practical results are validated with actual data, in a specific scenario, showing a reduction of 3.36% of fuel consumption. |
| Databáze: | OpenAIRE |
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