Statistical clustering is applied for mathematical description of a surface mount assembly process. The clustering model, intended for process control applications, defines the correspondence between various outcomes of the process and particular regions in the space of process variables. An adaptive version of the clustering model is presented. Prediction, regime selection and control procedures, utilizing the clustering model, are formulated.

Issue Section:
Technical Papers
Topics:
Performance, Printing, Process control, Surface mount assemblies
1.
Skormin, V. A., and Siciliano, R., “A Novel Approach to Quality Analysis and Control of the Film Coating Process,” Journal of Coating Technology, Jan. 1991.
2.
Skormin, V. A. “Mathematical Modeling and Control of Continuous Manufacturing Processes with Discrete Event Output,” Presented at the 8th International Conference on Mathematical Modeling and Computer Simulation, College Park, MD, Apr. 3, 1991.
3.
Maiso, P. Steven, and Bauer, Brian, “Statistical Process Control in Solder Paste Manufacture and Use,” IPC Technical Review, Sept. 1990, pp. 20–26.
4.
Duran, B. S., and Odell, P. L., Cluster Analysis: A Survey, Springer-Verlag, New York, 1974.
5.
Sebestyen, G. S., “Pattern Recognition by an Adaptive Process of Sample Set Construction,” IRE Transactions on Information Theory, Vol. IT-8, Sept. 1962.
6.
Nelder, J. A., and Mead, R., “A Simplex Method for Function Minimization,” The Computer Journal, Vol. 7, 1965.
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