Optimization of a bonded leads process using statistically designed experiments

In manufacturing high-technology products using automated manufacturing equipment it is critical to obtain process-operating conditions that simultaneously optimize several output variables of interest. Often these output variables are non-traditional responses such as standard deviations, and there may even be discrete (count or binary) responses. Statistically designed experiments are very useful in optimizing these processes. We illustrate how factorial experiments, statistical models for the responses of interest, and simple optimization techniques can be successfully applied to a bonded leads process.