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Accuracy enhancement of multi-axis CNC machines through on-line neurocompensation

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Abstract

This research is devoted to one of the most fundamental problems in precision engineering: machine tool accuracy. The paper presents a new approach designed to improve the accuracy of multi-axis CNC machines through software compensation of geometric, thermal and dynamic errors. Based on a multi-sensor monitoring system, the proposed compensation scheme is built to ensure error prediction. Four steps are required to develop and implement this system: (i) measurement of individual error components along each axis using a laser interferometer system, (ii) sensor integration via an artificial neural network model for on-line error estimation, (iii) synthesis of the total error into a three-dimensional error form using a simplified kinematic model and finally (iv) error compensation. Implemented on a turning center, the neurocompensation approach has improved machine accuracy by reducing the maximum error without compensation from 70 μm without compensation to less than 4 μm.

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Authors and Affiliations

  1. Mathematics, Computer and Engineering Department, University of Quebec at Rimouski, Rimouski, Canada, G5L 3A1

    Abderrazak El Ouafi

  2. Mechanical Engineering Department, Laval University, Quebec, Canada, G1K 7P4

    Michel GUILLOT & Abdellah Bedrouni

Authors
  1. Abderrazak El Ouafi
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  2. Michel GUILLOT
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  3. Abdellah Bedrouni
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Ouafi, A.E., GUILLOT, M. & Bedrouni, A. Accuracy enhancement of multi-axis CNC machines through on-line neurocompensation. Journal of Intelligent Manufacturing 11, 535–545 (2000). https://doi.org/10.1023/A:1026500422130

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  • DOI: https://doi.org/10.1023/A:1026500422130

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