Abstract
After the design and construction of manufacturing tools, adjustment is often necessary to reduce mean deviation from target of product dimensions. We formulate a stochastic dynamic program to find the optimal adjustment policy when the adjustment outcome is uncertain. The optimal policy minimizes the sum of adjustment cost during pre-production and quality cost during production. The formulation is developed for a single process and for two processes producing components for assembly. In the single process case, sufficient conditions are given for the optimal policy to have an upper and lower control limit form. In the two process case, we compare separate and combined policies and give an example where appreciable savings can be realized from a combined policy.
The authors wish to acknowledge the National Science Foundation (grant No. SBR-9712997) and the Tauber Manufacturing Institute of the University of Michigan for their support of their research.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Clark, K. B.; and Fujimoto, T. (1991). Product Development Performance. Harvard Business School Press, Boston, MA.
Fine, C. H.; and Porteus, E. L. (1989). “Dynamic Process Improvement”. Operations Research 37, pp. 580–91.
Glenn, D.W.; and Pollock, S.M. (1998). “Process Centering With Uncertain Tool Adjustment”. IOE Technical Report 98–11, University of Michigan Department of Industrial and Operations Engineering, Ann Arbor MI.
Hammett, P. C. (1995). Methods for Vadidating Stamping and Metal Assembly Processes During Automotive Body Development. Ph.D. Dissertation. The University of Michigan, Ann Arbor, MI.
Hu, S. J.; and Liu, S. C. (1994). “Joint Designs and Their Variation Characteristics”. Lecture notes. The University of Michigan Mechanical Engineering Deptartment, Ann Arbor, MI.
Hu, S. J.; and Liu, S. C. (1998). “Sheet Metal Joint Configurations and Their Variation Characteristics”. ASME Journal of Manufacturing Science and Engineering 120, pp. 461–467.
Kumar, P. R.; and Varaiya, P. (1986). Stochastic Systems: estimation, identification, and adaptive control. Prentice-Hall, Englewood Cliffs, NJ.
Takezawa, N. (1980). “An Improved Method for Establishing the Process-Wise Quality Standard”. Reports of Statistical Application Research, Union of Japanese Scientists and Engineers (JUSE), 27, pp. 63–76.
Trietsch, D. (1998). “The Harmonic Rule for Process Setup Adjustment with Quadratic Loss”. Journal of Quality Technology 30, pp. 75–84.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer Science+Business Media New York
About this chapter
Cite this chapter
Glenn, D.W., Pollock, S.M. (2003). Process Adjustment for Assemblies. In: Gershwin, S.B., Dallery, Y., Papadopoulos, C.T., Smith, J.M. (eds) Analysis and Modeling of Manufacturing Systems. International Series in Operations Research & Management Science, vol 60. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1019-2_3
Download citation
DOI: https://doi.org/10.1007/978-1-4615-1019-2_3
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5354-6
Online ISBN: 978-1-4615-1019-2
eBook Packages: Springer Book Archive