An expert-system-based tool was developed in order to operate the autoclave cure of a thick fiber reinforced thermosetting matrix composite laminate in an optimal manner. The best temperature profile is obtained using a novel model-based optimization technique. It incorporates known heuristics about the problem to prune the search space and reduce the dimensionality of the problem so as to converge to a near-optimum in a reasonable amount of time. The objective function used has components for minimizing the total cure time, reducing the temperature excursions during an exotherm and minimization of process-induced residual stresses in the laminate. The inevitable divergence between the process and the simulation precludes the direct application of such optimal profiles. We have devised a general methodology to address this issue of process-model mismatch, which allows for the implementation of model-based optimal profiles in real situations. This methodology is directed at ensuring that the actual cure follows the same trends as predicted by the optimal cure, rather than trying to achieve an exact match. Trend analysis is used to access the underlying process trends in the profiles of different variables of the optimal solutions. Data from the autoclave is also analyzed on-line to determine the trends in real-time. A correlation between the control decisions and the trend analysis of a number of profiles from the optimization module is used to determine rules to translate the `simulation' optimal profile to one that will be used on the process. The results from application of this overall strategy for the curing of glass-polyester composites are presented. The expert system achieved the desired objectives of minimizing the cure time, while still producing a high quality part.
The manufacture of composite parts using the autoclave curing process requires the specification of the autoclave temperature as a function of time. It is desired to obtain a part meeting given specifications in the minimum amount of time. A recently developed methodology was used to optimize the process using a mathematical simulation of the cure process. The optimal profile so obtained was implemented on a full-sized autoclave which is interfaced to a proprietary control system running on a Hewlett-Packard computer, using a knowledge-based system (KBS) as a supervisor. In order to account for discrepancies between the simulation and the actual process, we have followed a strategy that uses process trend analysis of the simulation output as the basis for control. The whole process is split up into episodes based on an analysis of the variable profiles. This information is used in conjunction with other knowledge about the system embedded in the KBS to adjust the set point of the autoclave temperature so that the process follows the same "trends" as dictated by the model-based optimization. Using this system, it was possible to guide the cure robustly along an "optimal" path, consistently yielding superior quality parts despite the variability of the raw materials. This procedure allows us to optimize a process independently using even an inexact simulation and apply the optimal profiles obtained therefrom.
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