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Low resolution fractional factorial experimental designs, used in screening, are more popular than ever due to the ever increasing costs of materials and machine time. Experimenters have to be more precise in their analysis, making every degree of freedom count. Resolution III designs are becoming more commonplace for use in screening designs. When running unsaturated resolution III designs there are extra degrees of freedom stemming from unassigned interactions. It is common practice to utilize these extra degrees of freedom to approximate error. In many cases, this common practice can over state the error and lead to erroneous results regarding factor statistical significance. Utilizing saturated resolution III designs and statistically analyzing unassigned interactions while estimating the error with replication is a method for strengthening the DOE strategy and improving the results from screening designs.

There is still much controversy and confusion in industry today regarding the use of process capability indices and analysis. A lack of knowledge regarding the underlying variation assumptions and rationale sampling strategies in indices such as Cp, Cpk, Pp and Ppk have added to the confusion and in many cases has led to misapplication of these widely used metrics. This issue has also promoted inconsistency in the assessment of long-term versus short-term capability and has hampered the true characterization of processes which is a critical step in any continuous improvement effort. Capability indices and analysis, when properly applied can impart a wealth of knowledge regarding process performance as well as provide focus for improvement activity through the proper characterization and enumeration of variation. Being able to properly characterize variation if the first step in reducing it.

Evolutionary Operation (EVOP) experimental design using Sequential Simplex method is an effective and robust means for determining the ideal process parameter (factor) settings to achieve optimum output (response) results. EVOP is the methodology of using on-line experimental design. Small perturbations to the process are made within allowable control plan limits, to minimize any product quality issues while obtaining information for improvement on the process. It is often the case in high volume production where issues exist, however off-line experimentation is not an option due to production time, the threat of quality issues and costs. EVOP leverages production time to arrive at the optimum solution while continuing to process saleable product, thus substantially reducing the cost of the analysis.