Abstract
In this paper, a two-layer model is used to strengthen the quality assurance function in the process planning and operation monitoring stages of engineering design for small-volume production. The lower layer of the model, formulated by a dynamic time series, and the upper layer of the model, denoted by a static multivariable regression equation, are combined together. As for the dynamic counterpart of the model, the adaptive Kalman smooth algorithm (AKSA) mixed with a simplex algorithm is executed to predict the expectation and the range on the size of the part to be operated next. Regarding the static counterpart of the model, the nonlinear step-wise regression algorithm is applied to build up the relationship between the operation parameters and the parameters in the dynamic model. In view of the applicability of the two-layer model, an experiment is implemented and an integrated prototype system is designed and developed. From application in an enterprise, this system shows quite satisfactory behaviour.
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