This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Integrated Dimensional Variation Analysis Method for Robust Process Design
Technical Paper
2006-01-0161
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
Manufacturing variation effects on the fit and function of a finished product, e.g., a vehicle, can be analyzed into designs using 3D dimensional simulation method. In an effort to reduce the predicted process variation for improving the dimensional quality during design phase, an integrated analytical approach is presented using robust design and variation simulation method that leads to select the optimal product datum and locating schemes for the process design. The Taguchi’s robust design and ANOVA (analysis of variance) are used in the algorithm to generate meaningful information about the effects of several processes simultaneously on the variability of the measured products. The application of the proposed method in process control with the dynamic factor, such as powertrain roll, is also discussed.
Recommended Content
Authors
Citation
Zhang, B. and Plonka, F., "Integrated Dimensional Variation Analysis Method for Robust Process Design," SAE Technical Paper 2006-01-0161, 2006, https://doi.org/10.4271/2006-01-0161.Also In
References
- Ligget, J. V. Dimensional Variation Management Handbook Prentice Hall Englewood Cliffs 1993
- DCS-3D Software Dimensional Control System Troy, Michigan, USA 2003
- Phadke, M. S. Quality Engineering Using Robust Design Prentice Hall, NJ 1989
- ADAMS ADAMS Full Simulation Package Reference Mechanical Dynamics, Inc. Ann Arbor, Michigan, USA 2003
- Minitab Software and Manual Minitab Inc. State College PA, USA 2003
- Zhang, B. Munipalli, H. Vickers, P. “Functional Fit Analysis on a Designed Experiment” First GM CAE Conference, EMT11–12, Pontiac, MI 1998
- Introduction to Monte Carlo Methods Computational Science Education Project web page http://csep1.phy.ornl.gov/mc/mc.html 2003