Parametric Error Modeling and Software Error Compensation for Rapid Prototyping

Open Access
- Author:
- Tong, Kun
- Graduate Program:
- Industrial Engineering
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- January 12, 2005
- Committee Members:
- Sanjay B Joshi, Committee Chair/Co-Chair
El Amine Lehtihet, Committee Chair/Co-Chair
Tom Michael Cavalier, Committee Member
Enrique Del Castillo, Committee Member
Eric Russell Marsh, Committee Member - Keywords:
- Simulated Annealing
D-optimal Design
Parametric Errors
Error Compensation
Rapid Prototyping - Abstract:
- Rapid prototyping (RP) machines can build parts of complex geometry with very little process planning and human interaction, making them a very attractive manufacturing process. However, inferior dimensional accuracy of these processes is a major obstacle preventing this technology from greater penetration of manufacturing activities. This research presents a generic method for improving the accuracy of RP machines by error compensation using “virtual” parametric errors. It was inspired by techniques developed for parametric evaluation of Coordinate Measuring Machines (CMM) errors. Under this approach, the confounded effects of all errors in a RP machine were mapped into 18 “virtual” parametric errors which were used to build the machine error model. A specially designed 3D artifact was then built on the RP machine and measured by a master CMM. Measurement results were used to estimate the coefficients of the parametric error functions. Error compensation based on the derived error model was finally applied via software to the files which drive the RP machine. Two compensation methods were developed and tested. The first one applied compensation to StereoLithography (STL) files while the second applied compensation to slice files. Compensation applied to slice files theoretically allows higher compensation resolution, but machine control resolution must be sufficiently fine in order to take advantage of this strategy. The resolution of the RP machine used in this study to test slice file compensation was too coarse to distinguish significant differences between slide file compensation and STL file compensation. Experimental studies were conducted on a SLA 250 machine and a FDM 3000 system to validate and demonstrate the approach. Results showed that the volumetric error was reduced on average to around 33% of its original value for the SLA machine. In the study of a part with common features and dimensional constraints, it was found that (a) overall size of the part and feature positions on the part were considerably improved, (b) cylindrical feature sizes were improved by a small amount, and (c) dimensions along the z direction did not show obvious improvement due to “z quantization”. “z quantization” was addressed in particular to eliminate multiple layers phenomenon in compensated parts. Compensation results of the FDM 3000 machine were compared with those of the SLA machine. Differences in error reduction ratios between these two machines were analyzed. Finally, the design optimization problem of 3D artifact was studied. The coefficients of the “virtual” parametric error functions were estimated using the error data sampled from the 3D artifact. There are potentially different artifacts that can be used to sample these errors in the RP working volume. Each will result in a different accuracy of the estimated coefficients. How to choose these sampling points in the RP working volume is a Design of Experiments (DOE) problem. D-optimality criterion was employed to verify and improve the design of the 3D artifact. Mathematical programming and simulated annealing algorithm were used for optimization of the design. In conclusion, this research provides a low cost, generic software compensation method to improve the accuracy of a RP process with no hardware modification. “Virtual” parametric error functions not only enable a rational comparative evaluation of competing RP processes on the basis of a quantitative assessment of volumetric accuracy, but also serve as a diagnostic tool for the identification of direction dependent error sources due to other process characteristics.