This research is devoted to one of the most fundamental problems in precision engineering: multi-axis machines accuracy. The paper presents a new approach designed to support the implementation of software error compensation of geometric, thermal and dynamic errors for enhancing the accuracy of multi-axis machines. The accuracy of multi-axis machines can be significantly improved using an intelligent integration of sensor information to perform the compensation function. The compensation process consists of the following major steps carried out on-line: continuous monitoring of the machine conditions using position, force, speed and temperature sensors mounted on the machine structure. Error forecasting through sensor fusion. Volumetric error synthesis and software compensation. To improve the effectiveness of error modeling, an artificial neural network is extensively applied.

Implemented on a turning center, the compensation approach has enabled improvement of the machine accuracy by reducing the maximum dimensional error from 70 μm initially to less than 4 μm.

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