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Autonomous cutting parameter regulation using adaptive modeling and genetic algorithms

  • Published:1998-10 Issue:4 Volume:22 Page:243-251
  • ISSN:0141-6359
  • Container-title:Precision Engineering
  • language:en
  • Short-container-title:Precision Engineering

Author:

Ko Tae Jo,Kim Hee Sool

Publisher

Elsevier BV

Subject

General Engineering

Reference10 articles.

1. Learning and optimization of machining operations using computing abilities of neural networks;Rangwala;IEEE Trans SMC,1989

2. Machining parameter optimization for specified surface roughness;Jang;J Eng Ind,1992

3. Autonomous turning operation planning with predicting tool wear and surface roughness;Matsumura;Trans NAMRI/SME,1993

4. Maximum profit as the criterion in the determination of the optimum cutting conditions;Wu;J Eng Ind,1966

5. Computer Control of Manufacturing System;Koren,1983

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1. Energy Efficient Machining Through Evolutionary Real-Time Optimization of Cutting Conditions on CNC-Milling Controllers;Materials Forming, Machining and Tribology;2021

2. Designing and implementation of a novel online adaptive control with optimization technique in hard turning;Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering;2020-09-10

3. Intelligent model-based optimization of cutting parameters for high quality turning of hardened AISI D2;Artificial Intelligence for Engineering Design, Analysis and Manufacturing;2020-03-03

4. A review of empirical modeling techniques to optimize machining parameters for hard turning applications;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2014-12-05

5. A hybrid NN-FE approach to adjust blank holder gap over punch stroke in deep drawing process;The International Journal of Advanced Manufacturing Technology;2013-11-26
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