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Walter Schroeder Library, Milwaukee School of Engineering
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More by this author
Gervasi, Vito R.
Subjects
Rapid tooling
Mensuration
Tolerance (Engineering)
Prototypes, Engineering
Patternmaking
MSE Project.
Prototype Hard and Soft Tooling (PHAST)
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by author:
Gervasi, Vito R.
by title:
Metrology evaluation...
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Metrology evaluation and calibration tool kit for rapid tooling processes / by Vito R. Gervasi.
by
Gervasi, Vito R.
Subjects
Rapid tooling
Mensuration
Tolerance (Engineering)
Prototypes, Engineering
Patternmaking
MSE Project.
Prototype Hard and Soft Tooling (PHAST)
Description:
114 leaves : ill. ; 29 cm.
Contents:
Advisor: Dr. Gottfried Hoffmann.
Committee member: Matthew Panhans.
Committee member: Dr. William E. Howard
Introduction -- Benchmark geometry -- Mathematical approach -- Sample preparation and measurement -- Results and discussion -- Conclusions -- References -- Appendix A) Raw data, average feature size, and standard deviation B) Uniform probability plots of raw data C) Student's t table and F table D) Shrinkages E) Uniform probability plots of shrinkage F) Plots, relative shrinkage.
Many rapid tooling processes are currently under development and in use for applications such as injection molding and die-casting. To evaluate and improve rapid tooling processes, several benchmarking geometries and software programs have been developed but none of these lend themselves to the evaluation and improvement of the Prototype Hard and Soft Tooling (PHAST) process. This project provides a new benchmark geometry, designed especially for indirect rapid tooling processes such as PHAST. Also, a mathematical procedure to accompany the geometry has been developed.
The new benchmark geometry and mathematical procedure were applied to the PHAST indirect rapid tooling process. The goal was to prove that the mean and standard deviation of shrinkage could be estimated from the mean and standard deviation of shrinkage of individual process steps. By establishing a procedure where the mean and standard deviation of shrinkage for an entire process are calculated, based upon a number of independent steps, one can make process changes without reevaluating the entire process. Another use of data gathered from this procedure was to identify those steps in greatest need of improvement as well as prediction of shrinkage. Using the mathematical procedure and 2D calibration geometry developed in this project, the mean and standard deviation of shrinkage were successfully estimated. A plot was generated to identify which process steps are in greatest need of refinement. Another plot was generated to predict process shrinkage as a function of feature size.
web address:
https://msoe.tind.io/record/917
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Walter Schroeder Library
Master's Theses
AC805 .G47 2003
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