Optimization of cutting process by GA approach

The paper proposes a new optimization technique based on genetic algorithms (GA) for the determination of the cutting parameters in machining operations. In metal cutting processes, cutting conditions have an influence on reducing the production cost and time and deciding the quality of a final prod...

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Bibliographic Details
Published inRobotics and computer-integrated manufacturing Vol. 19; no. 1; pp. 113 - 121
Main Authors Cus, Franci, Balic, Joze
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.02.2003
Subjects
Cutting parameters
Genetic algorithm
Manufacturing
Optimization
Simulation
Cutting parameters
Manufacturing
Simulation
Genetic algorithm
Optimization
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Summary:The paper proposes a new optimization technique based on genetic algorithms (GA) for the determination of the cutting parameters in machining operations. In metal cutting processes, cutting conditions have an influence on reducing the production cost and time and deciding the quality of a final product. This paper presents a new methodology for continual improvement of cutting conditions with GA. It performs the following: the modification of recommended cutting conditions obtained from a machining data, learning of obtained cutting conditions using neural networks and the substitution of better cutting conditions for those learned previously by a proposed GA. Experimental results show that the proposed genetic algorithm-based procedure for solving the optimization problem is both effective and efficient, and can be integrated into an intelligent manufacturing system for solving complex machining optimization problems.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0736-5845
1879-2537
DOI:10.1016/S0736-5845(02)00068-6