Heuristics guided optimization of a batch autoclave curing process

Abstract

A method for optimization of the autoclave curing process has been developed, which exploits accumulated knowledge regarding the process. The selection of the control variables follows the minimization of local (in time) optimization criteria derived from known heuristics and are used to drastically reduce the parameters of the problem. A near-optimun global solution is obtained by optimizing the values of only a few physically meaningful parameters which enter into the definition of the local criteria, employing any one of the available traditional methods for discrete optimization. The local criteria employed in the autoclave curing process involve an approximate (heuristic) evaluation of the process characteristics for different control scenarios projected forward from that point in time. The proposed methodology is exemplified by applying it to the well-known brachistochrone problem, which serves as a test bed, since the solution is known. A reactor optimization problem for the literature is used to confirm the adaptability of this technique to chemical engineering problems. The method is then used to optimize an autoclave molding process for the manufacture of thick composite laminates.