Approach to optimization of cutting conditions by using artificial neural networks

Franc Čuš (Author), Uroš Župerl (Author)

Abstract

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.

Keywords

optimiranje;optimiranje rezalnih parametrov;genetski algoritmi;nevronske mreže;rezalni parametri;algoritem nevronskih mrež;obdelovanje;rezanje kovin;optimization;cutting parameter optimization;genetic algorithm;cutting parameters;neural network algorithm;machining;metal cutting;

Data

Language:	English
Year of publishing:	2006
Typology:	1.01 - Original Scientific Article
Organization:	UM FS - Faculty of Mechanical Engineering
UDC:	621.914:[004.89:007.52]
COBISS:	10137878
ISSN:	0924-0136
Views:	1954
Downloads:	106
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary keywords:	optimiranje;optimiranje rezalnih parametrov;genetski algoritmi;nevronske mreže;rezalni parametri;algoritem nevronskih mrež;obdelovanje;rezanje kovin;
URN:	URN:SI:UM:
Pages:	str. 281-290
Volume:	ǂVol. ǂ173
Issue:	ǂiss. ǂ3
Chronology:	2006
ID:	8717308