Complexity of manufacturing processes has hindered methodical specification of machine setpoints for improving productivity. Traditionally in injection molding, the machine setpoints are assigned either by trial and error, based on heuristic knowledge of an experienced operator, or according to an empirical model between the inputs and part quality attributes obtained from statistical design of experiments (DOE). In this paper, a Knowledge-Based Tuning (KBT) Method is presented which takes advantage of the a priori knowledge of the process, in the form of a qualitative model, to reduce the demand for experimentation. The KBT Method is designed to provide an estimate of the process feasible region (process window) as the basis of finding the optimal setpoints, and to update its knowledge-base according to new input-output data that becomes available during tuning. The KBT Method’s utility is demonstrated in production of digital video disks (DVDs).

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