PurposeThe purpose of this research is to extend the previous approach to software error compensation to fused deposition modeling (FDM) machines and explores the approach to apply compensation by correcting slice files.Design/methodology/approachIn addition to applying the stereolithography (STL) file‐based compensation method from earlier research; a new approach using the slice file format to apply compensation is presented. Under this approach, the confounded effects of all errors in a FDM machine are mapped into a “virtual” parametric machine error model. A 3D artifact is built on the FDM machine and differences between its actual and nominal dimensions are used to estimate the coefficients of the error functions. A slice file compensation method is developed and tested on two types of parts as a means for further improving the error compensation for feature form error improvement. STL file compensation is also applied to a specific FDM 3000 machine and the results are compared with those of a specific SLA 250 machine.FindingsThe two compensation methods are compared. Although, the slice file compensation method theoretically allows higher compensation resolution, the actual machine control resolution of the FDM machine can be a limitation which makes the difference between STL compensation and slice file compensation indistinguishable. However, as the control resolution is increased, this method will make it possible to provide a higher degree of compensation.Originality/valueCompensation method applied to slice file format is developed for FDM machines and its limitations are explored. Based on the experimental study, dimensional accuracy of parts is considerably improved by the software error compensation approach.
This paper is motivated by the need for a generic approach to evaluate the volumetric accuracy of rapid prototyping (RP) machines. The approach presented in this paper is inspired in large part by the techniques developed over the years for the parametric evaluation of coordinate measuring machine (CMM) errors. In CMM metrology, the parametric error functions for the machine are determined by actual measurement of a master reference artifact with known characteristics. In our approach, the RP machine is used to produce a generic artifact, which is then measured by a master CMM, and measurement results are used to infer the RP machine's parametric error functions. The results presented demonstrate the feasibility of such an approach on a two-dimensional model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.