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Construction and operation of a knowledge base on intelligent machine tools

Published: 01 March 2008 Publication History

Abstract

Machine tools lie at the heart of almost all manufacturing systems, and their performance has a massive influence on both the performance and productivity of systems. In accordance with the development of computer systems, intelligent technologies have been applied to manufacturing systems, thereby raising the need for more intelligent machine tools. Intelligent machines respond to external environments on the basis of decisions that are made by sensing the changes in the environment and analyzing the obtained information. This study focuses on the construction of a knowledge base which enables decision making with that information. Approximately 70% of all errors that occur in machine tools are caused by thermal errors. In order to proactively deal with these errors, a system which measures the temperatures of each part and predicts and compensates the displacement of each axis has been developed. The system was built in an open- type controller to enable machine tools to measure temperature changes and compensate the displacement. The construction of a machining knowledge base is important for the implementation of intelligent machine tools, and is expected to be applicable to the network-based, intelligent machine tools which look set to appear sooner or later.

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  • (2018)DEA advanced models for geometric evaluation of used lathesWSEAS TRANSACTIONS on SYSTEMS10.5555/1456007.14560177:5(510-520)Online publication date: 17-Dec-2018

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Published In

cover image WSEAS TRANSACTIONS on SYSTEMS
WSEAS TRANSACTIONS on SYSTEMS  Volume 7, Issue 3
March 2008
152 pages

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Stevens Point, Wisconsin, United States

Publication History

Revised: 19 March 2008
Published: 01 March 2008
Received: 27 December 2007

Author Tags

  1. intelligent machine tools
  2. machining knowledge base
  3. multiple linear regression models
  4. neural network
  5. offset compensation
  6. open controller
  7. thermal errors

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  • (2018)DEA advanced models for geometric evaluation of used lathesWSEAS TRANSACTIONS on SYSTEMS10.5555/1456007.14560177:5(510-520)Online publication date: 17-Dec-2018

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