Abstract

Accuracy is one of the most important key indices to evaluate multi-axis systems’ (MAS’s) characteristics and performances. The accuracy of MAS’s such as machine tools, measuring machines and robots is adversely affected by various error sources, including geometric imperfections, thermal deformations, load effects, and dynamic disturbances. The increasing demand for higher dimensional accuracy in various industrial applications has created the need to develop cost-effective methods for enhancing the overall performance of these mechanisms. Improving the accuracy of a MAS by upgrading the physical structure would lead to an exponential increase in manufacturing costs without totally eliminating geometrical deviations and thermal deformations of MAS components. Hence, the idea of reducing MAS’s error by a software-based alternative approach to provide real-time prediction and correction of geometric and thermally induced errors is considered a strategic step toward achieving the full potential of the MAS. This paper presents a structured approach designed to improve the accuracy of Cartesian MAS’s through software error compensation. Four steps are required to develop and implement this approach: (i) measurement of error components using a multidimensional laser interferometer system, (ii) tridimensional volumetric error mapping using rigid body kinematics, (iii) volumetric error prediction via an artificial neural network model, and finally (iv) implementation of the on-line error compensation. An illustrative example using a bridge type coordinate measuring machine is presented.

Highlights

  • Current trends in precision engineering demand continually higher accuracy for various industrial applications

  • In response to the increasing demand for higher quality, improving the accuracy of multi-axis systems through software error compensation is becoming increasingly important in modern manufacturing

  • 90 Journal of Analytical Sciences, Methods and Instrumentation pends on the degree of consistency in identifying error sources, the precision of the measurement techniques, the reliability of the modelling approach, and its robustness in evaluating the error components at any location within the multi-axis systems (MAS) workspace

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Summary

Introduction

Current trends in precision engineering demand continually higher accuracy for various industrial applications. Major contributors to inaccuracies in MAS’s are quasi-static error sources, which are responsible for a very large proportion of the observed total deviation They account for 70% of the volumetric error [1]. Whereas some error sources affect machine accuracy directly, others are interrelated with each other and their combined effects cause significant positioning errors. By considering all these diverse and variable error sources, one can understand the difficulties involved in improving MAS accuracy. The approach proposed in this paper is based on an accuracy-monitoring scheme designed to improve the accuracy of multi-axis machines by compensating for geometric, thermal, loadinduced and inertial errors. The paper presents a structured and comprehensive approach designed to improve the accuracy of Cartesian MAS’s through software error compensation. This paper presents the approach’s limitations and some other research ideas to overcome the difficulties that still obstruct this promising technology from being widely applied in various manufacturing systems

Overview of MAS Errors
Errors Description and Modelling
Geometric Errors Model of Linear Axis
Geometric Errors Model of Three-Axis MAS
Errors Measurements
Application in the Case of a Coordinate Measuring Machine
Errors Measurement Procedure
Artificial Neural Network Modeling
Error Compensation
Findings
Conclusions
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