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Direct tolerance analysis of mechanical assemblies with normal and non-normal tolerances for predicting product quality.
- Source :
- International Journal of Computer Integrated Manufacturing; Jul2022, Vol. 35 Issue 7, p743-760, 18p, 7 Diagrams, 12 Charts, 1 Graph
- Publication Year :
- 2022
-
Abstract
- Tolerance analysis, as an effective tool for predicting the effects of geometrical and dimensional deviations on the key characteristics, plays an essential role in increasing the functionality and quality of mechanical products. The conventional methods in the literature have been developed based on this main assumption that the assembly function is available in an explicit form. However, in most industrial applications, deriving an assembly function in an explicit form may be difficult if not impossible. On the other hand, one of the major weaknesses of the conventional tolerance analysis methods in the literature is that all effective dimensions should be varied under the normality assumption. To overcome these weaknesses, in this paper, a new tolerance analysis approach is developed based on the univariate DRM and Pearson system concepts. The proposed method can analyze directly without the need to define any assembly function and also the rejected product rate can be easily predicted using evaluations of the assembly dimension at the limited number of special points. Finally, for verification of the proposed method, some illustrative case studies are considered and results are compared to obtained results of the Monte-Carlo Simulations and the improved Hassofer-Lind and Rack-Fizzler reliability index methods. [ABSTRACT FROM AUTHOR]
- Subjects :
- PRODUCT quality
FORECASTING
INDUSTRIAL applications
Subjects
Details
- Language :
- English
- ISSN :
- 0951192X
- Volume :
- 35
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- International Journal of Computer Integrated Manufacturing
- Publication Type :
- Academic Journal
- Accession number :
- 158319855
- Full Text :
- https://doi.org/10.1080/0951192X.2021.2023221