Applications to Autoclave Curing

Independent variable Measure of fit Quadratic regression ANN model 

In this effort, note that hold duration is a constraint, whereas thickness and void content are quality variables to be optimized. In much of the KBES-based work, curing duration is to be minimized, whereas nominal thickness (occasionally) and minimal void content (often) represent constraints. 

Results from these experimental runs were used as x, q data records to fit the parameters of six ANNs. In the experimental effort, a different feedforward ANN was used after each intermediate secondary measurement was obtained in the simulation-based effort, only one ANN accommodates all secondary measurements, and averaged dummy inputs are used for those secondary measurements not yet obtained. In addition in the experimental effort, a different ANN was used for final thickness and final void content predictions in the simulation-based effort, one ANN was used to predict both final thickness and final void content. The advantage of using one ANN to predict all values of q is that the parameters of only one ANN need be fitted. Fitting the parameters of an ANN for each variable in q is much more time-consuming. The disadvantage, however, is that the parameters A and abias are the same for each variable in q when just one ANN is used as an on-line model. When a different ANN is used for each variable in q, the parameters in A and abias are unique for each of those output variables, which results in increased on-line prediction accuracy. Similar speed-versus-accuracy arguments apply to the choice of one ANN for all secondary measurements versus an ANN for each secondary measurement. 

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