Abstract
In today’s competitive market, it is no longer practical to design by trial and error. Yet, this remains the normal practice, whether through the testing of numerous prototype designs or the simulations of these designs. Of course, the latter is preferred because it is cheaper, but there remains the issue of finding the best possible design. A trial-and-error approach simply does not address this task. In this paper, the authors describe their work combining computational process modeling and nonlinear programming to optimally design manufacturing processes.
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