Approach to optimization of cutting conditions by using artificial neural networks
| Autor: | Franci Cus, U. Zuperl |
|---|---|
| Rok vydání: | 2006 |
| Předmět: |
Engineering
Mathematical optimization Artificial neural network Optimization algorithm business.industry Metals and Alloys Machine learning computer.software_genre Industrial and Manufacturing Engineering Computer Science Applications Reduction (complexity) Machining Modeling and Simulation Genetic algorithm Ceramics and Composites Artificial intelligence business computer Metal cutting Selection (genetic algorithm) |
| Zdroj: | Journal of Materials Processing Technology. 173:281-290 |
| ISSN: | 0924-0136 |
| DOI: | 10.1016/j.jmatprotec.2005.04.123 |
| Popis: | Optimum selection of cutting conditions importantly contribute to the increase of productivity and the reduction of costs, therefore utmost attention is paid to this problem in this contribution. In this paper, a neural network-based approach to complex optimization of cutting parameters is proposed. It describes the multi-objective technique of optimization of cutting conditions by means of the neural networks taking into consideration the technological, economic and organizational limitations. To reach higher precision of the predicted results, a neural optimization algorithm is developed and presented to ensure simple, fast and efficient optimization of all important turning parameters. The approach is suitable for fast determination of optimum cutting parameters during machining, where there is not enough time for deep analysis. To demonstrate the procedure and performance of the neural network approach, an illustrative example is discussed in detail. |
| Databáze: | OpenAIRE |
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