On-Line Production Cost Optimization in High Performance Machining Operations through AI Techniques

Author

Silva, Jorge A. ; Siller, Héctor R. ; Kitazawa, G. ; Abellan-Nebot, J.V.

Author_Institution

Centre for Innovation in Design & Technol., Tec de Monterrey (ITESM), Monterrey, Mexico

fYear

2011

fDate

15-18 Nov. 2011

Firstpage

47

Lastpage

52

Abstract

This paper proposes an on-line adaptive control with optimization (ACO) system for optimizing the production cost subjected to quality constraints in high performance machining operations of hardened steel. Unlike traditional approaches for optimizing production cost, this paper deals with optimizing the cutting operation considering the real state of the cutting-tool. Artificial intelligence techniques for modeling (Artificial Neural Networks) and optimizing (Genetic Algorithms and Mesh Adaptive Direct Search algorithms) are applied for this purpose.

Keywords

artificial intelligence; costing; cutting; cutting tools; genetic algorithms; machining; neural nets; production engineering computing; steel; ACO system; AI technique; artificial intelligence; artificial neural network; cutting operation; cutting-tool; genetic algorithm; hardened steel; high performance machining operation; mesh adaptive direct search algorithm; online adaptive control; online production cost optimization; quality constraint; Cutting tools; Estimation; Machining; Optimization; Rough surfaces; Surface roughness;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics, Robotics and Automotive Mechanics Conference (CERMA), 2011 IEEE

Conference_Location

Cuernavaca, Morelos

Print_ISBN

978-1-4577-1879-3

Type

conf

DOI

10.1109/CERMA.2011.15

Filename

6125808