Efficient volumetric error compensation technique for additive manufacturing machines

Abstract

Purpose

This paper aims to present a methodology for volumetric error compensation. This technique is applied to an Objet Eden350V 3D printer and involves a custom measurement strategy.

Design/methodology/approach

The kinematic model of the printer is explained, and its error model is simplified to 18 independent error functions. Each error function is defined by a cubic Legendre polynomial. The coefficients of the polynomials are obtained through a Levenberg–Marquardt optimization process. This optimization process compares, in an iterative algorithm, nominal coordinates with actual values of the cloud of points. The points are built in the faces of a gauge artefact as conical sockets defining one unique point for each socket. These points are measured by a coordinate measuring machine self-centring measurement process.

Findings

Most of the errors of the 3D printer are systematic. It is possible to obtain an improvement of 70 per cent in terms of global mean error reduction in single points within a volume of 120 × 120 × 40 mm. The forecast of the final error compensation fully matches the actual final error.

Practical implications

This methodology can be used for accuracy improvement in additive manufacturing machines.

Originality/value

Unlike the calculation of geometric errors, the proposed parametric determination through optimization of the error model allows global error reduction, which decreases all sort of systematic errors concurrently. The proposed measurement strategy allows high reliability, high speed and operator independence in the measurement process, which increases efficiency and reduces the cost. The proposed methodology is easily translated to other rapid prototyping machines and allows scalability when replicating artefacts covering any working volume.

Citation

Cajal, C., Santolaria, J., Samper, D. and Velazquez, J. (2016), "Efficient volumetric error compensation technique for additive manufacturing machines", Rapid Prototyping Journal, Vol. 22 No. 1, pp. 2-19. https://doi.org/10.1108/RPJ-05-2014-0061