DESIGN & ANALYSIS OF EXPERIMENTS

Statistical experimental design (DOE) plays a critical role in process optimization and Six Sigma. DOE's identify the vital few process inputs that significantly affect the process output. Once the vital few process variables have been identified, empirical models may be developed and used to maximize the process output by optimizing the process inputs. To assure optimal operating conditions are sustained, tolerances may be established and applied to the process inputs. We can then monitor vital process inputs and know when they become unstable. When this is the case, we may immediately react to the process inputs before the quality in the process output suffers. The result is a process that yields a product or service that has enhanced reliability, lower defects, faster cycle times, and lower costs.

This seminar is about planning, conducting, and analyzing experiments to arrive at valid and objective conclusions. The emphasis will be upon the effective use of techniques for experimentation, with the primary objective always being to achieve process optimization.

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