Virtual-point-based geometric error compensation model for additive manufacturing machines

Abstract

Purpose

The lack of geometric and dimensional accuracy of parts produced by additive manufacturing (AM) is directly related to the machine, material and process used. This paper aims to propose a method for the analysis and compensation of machine-related geometric errors applicable to any AM machine, regardless of the manufacturing process and technology used.

Design/methodology/approach

For this purpose, an error calculation model inspired by those used in computerized numerical control machines and coordinate measuring machines was developed. The error functions of the model were determined from the position deviations of a set of virtual points that are not sensitive to material and process errors. These points were obtained from the measurement of an ad hoc designed and manufactured master artefact. To validate the model, off-line compensation was applied to both the original designed artefact and an example part.

Findings

The geometric deviations in both cases were significantly smaller than those found before applying the geometric compensation. Dimensional enhancements were also achieved on the example part by using a correction parameter available in the three-dimensional printing software, whose value was adjusted from the measurement of the geometrically compensated master artefact.

Research limitations/implications

The errors that persist in the part derive from both material and process. Compensation for these type of errors requires a detailed analysis of the influencing parameters, which will be the subject of future research.

Originality/value

The use of the virtual-point-based error model increases the quality of additively manufactured parts and can be used in any AM system.

Citation

Zapico, P., Peña, F., Valiño, G., Rico, J.C., Meana, V. and Mateos, S. (2023), "Virtual-point-based geometric error compensation model for additive manufacturing machines", Rapid Prototyping Journal, Vol. 29 No. 4, pp. 837-849. https://doi.org/10.1108/RPJ-02-2022-0052