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An Investigation on the Analysis Method for Assembled Tolerances
Details
The product is more complicated and the parts can fit to the adjacent parts with multiple constraints for improving the stiffness and accuracy of the assembly. The average dimension of the parts may shifts or drifts from the nominal value during the manufacturing process. And, the dimension distribution of the parts can be in different non- normal distribution since they are manufactured by different manufacture process. This method predicts more accurate resultants by an interpolation method. With this method, the assembled state of an assembly with multiple constraints can be evaluated. The assembly behaves a higher probability of stiffness, as if the minimum gap index is smaller. For the mean shift studied for the cases represented in this paper, the results show the difference between this model and the Monte Carlo method with 1,000,000 simulation samples is less than 0.5%. The two stack-up examples described in this paper show the predicted errors only 0.799% and -1.76% respectively. The proposed model is fast and accurate for non-normal distribution and process with mean shift or drift.
Autorentext
Education: Mechanical Engineering, NCU, Taiwan, B.S., 1985. Engineering Science, National Cheng Kung University, Taiwan, M.S., 1987. Mechanical Engineering, National Chung Hsing University, Taiwan, Ph.D., 2010. Employment: Hiwin Tech. Corp., since 1989. Research Area: Design, manufacture and quality control of ball screw and bearing.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783843369862
- Sprache Englisch
- Genre Maschinenbau
- Anzahl Seiten 124
- Größe H220mm x B150mm x T8mm
- Jahr 2010
- EAN 9783843369862
- Format Kartonierter Einband
- ISBN 3843369860
- Veröffentlichung 16.11.2010
- Titel An Investigation on the Analysis Method for Assembled Tolerances
- Autor Chang-Hsin Kuo
- Untertitel Statistical tolerance analysis method for non-normal distribution parts with mean shifts and drifts
- Gewicht 203g
- Herausgeber LAP LAMBERT Academic Publishing