Predictive modeling of machining line variation
View Patent ↗A multistage machining process includes a plurality of stations. Workpiece feature quality is predicted based on decomposition of the machining process into sources of variation, reticulation of the machining process into machining stations and error models that account for significant contributions to feature quality including from categorical sources of variation.
1. Method for predicting feature quality in workpieces produced by a multi-station machining process, comprising:
decomposing the multi-station machining process into sources of variation including machine variations, fixture variations and workpiece variations;
reticulating the multi-station machining process into machining stations;
determining workpiece feature errors at each machining station based on the sources of variation;
summing workpiece feature errors into station level errors; and
using the station level errors to statistically predict feature quality.
2. The method for predicting feature quality in workpieces as claimed in claim 1 wherein determining workpiece feature errors further comprises decomposing each machining station into generic machining process steps and determining workpiece errors at each generic machining process step based on the sources of variation uniquely related to the respective generic machining process step.
3. The method for predicting feature quality in workpieces as claimed in claim 1 wherein machine variations comprise at least one of toolpath variations and machine distortions.
4. The method for predicting feature quality in workpieces as claimed in claim 1 wherein fixture variations comprise at least one of fixture pad variations, fixture distortions, fixture position and fixture orientation.
5. The method for predicting feature quality in workpieces as claimed in claim 1 wherein workpiece variations comprise at least one of workpiece casting variations, workpiece pad variations, workpiece clamping distortions, workpiece cutting distortions and workpiece pressing distortions.
6. Method for predicting feature quality in workpieces produced by a multi-station machining process including at least one machine and one fixture, comprising:
identifying a workpiece feature and a quality metric corresponding thereto;
reticulating the multi-station machining process into machining stations;
performing a plurality of station level error determinations for each of the machining stations, each determination including providing errors that significantly affect the quality metric of the feature and summing the errors to provide a station level error for each determination, wherein a respective plurality of station level errors is provided for each of the machining stations; and
using the station level errors to statistically predict the feature quality with respect to the quality metric.
7. The method for predicting feature quality in workpieces as claimed in claim 6 wherein the feature quality is predicted with respect to the machining process in its entirety and using the station level errors to statistically predict the feature quality with respect to the quality metric comprises summing the station level errors from each of the machining stations.
8. The method for predicting feature quality in workpieces as claimed in claim 6 wherein the feature quality is predicted at a particular one of the machining stations and using the station level errors to statistically predict the feature quality with respect to the quality metric comprises summing the station level errors from each of the machining stations within a range beginning with an initial machining station and ending with the particular one of the machining stations.
9. The method for predicting feature quality in workpieces as claimed in claim 8 wherein the initial machining station is the first machining station of the machining process.
10. The method for predicting feature quality in workpieces as claimed in claim 8 wherein the initial machining station is a machining station subsequent to the first machining station of the machining process.
11. The method for predicting feature quality in workpieces as claimed in claim 6 wherein providing errors that significantly affect the quality metric of the feature comprises providing errors resulting from another error effected upon another workpiece feature at another machining station.
12. The method for predicting feature quality in workpieces as claimed in claim 6 wherein errors provided comprise errors resulting from machine variations.
13. The method for predicting feature quality in workpieces as claimed in claim 6 wherein errors provided comprise errors resulting from fixture variations.
14. The method for predicting feature quality in workpieces as claimed in claim 6 wherein errors provided comprise errors resulting from workpiece variations.
15. The method for predicting feature quality in workpieces as claimed in claim 12 wherein machine variations comprise toolpath variations, machine distortions and combinations thereof.
16. The method for predicting feature quality in workpieces as claimed in claim 13 wherein fixture variations comprise at least one of fixture pad variations, fixture distortions, fixture position and fixture orientation.
17. The method for predicting feature quality in workpieces as claimed in claim 14 wherein wherein workpiece variations comprise at least one of workpiece casting variations, workpiece pad variations, workpiece clamping distortions, workpiece cutting distortions and workpiece pressing distortions.
18. The method for predicting feature quality in workpieces as claimed in claim 6 wherein errors provided comprise at least one of geometric errors, static errors and dynamic errors.
19. The method for predicting feature quality in workpieces as claimed in claim 6 wherein errors provided comprise measured errors.
20. The method for predicting feature quality in workpieces as claimed in claim 6 wherein errors provided comprise modeled errors.