Optimal fixture locator adjustment strategies for multi-station assembly processes

Abstract

Fixture locating errors directly impact the dimensional quality of products in assembly processes. During a production run, fixture locators may deviate from their designed positions and this can possibly lead to defects and quality loss in the final assembled products. Mass production in multi-station assembly processes involves multiple fixtures/stations, which leads to extreme complexity in dimensional control through locator position adjustment. This research aims to develop a systematic methodology for fixture locator adjustment to minimize total production costs in multi-station assembly processes. In this paper, a linear model is derived to describe the complex propagation effect of fixture adjustments throughout all stations in an assembly process. Bayesian estimation with iterative algorithms is used to adaptively estimate the unknown parameters of locator deviation errors during production. An optimal fixture locator adjustment strategy is obtained through dynamic programming based on the given process and product design scheme. A case study is provided to illustrate the implementation procedures and the significance of the proposed methodology.

Keywords:

• Bayesian estimation
• dynamic programming
• fixture locator adjustment
• multi-station assembly process
• state space model

Acknowledgements

The authors would like to gratefully acknowledge the financial support of the Engineering Research Center on Reconfigurable Manufacturing Systems (NSF Grant EEC95-92125) at the University of Michigan, and the NSF Grants: PECASE/CAREER AWARD DMI-0133942 and DMI-0217395.

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