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An experimental strategy is developped to collect data to answer questions as for example "which factors should I control to have a robust process ?" or "how can I improve the quality of this mixture ?".
The use of experimental designs and of statistics increases the effectiveness of the research experiments.
The methodology of experimental research provides a powerfull framework to draw objective conclusions from experiments and to solve empirical problems.
This approach provides common tools to researchers, engineers. Statistical experimental designs (DOE) have been successfully applied in a broad variety of problem. DOE has found applications in many various fields (pharmaceuticals, paint, physics, chemistry, biology, electronics, car and aircraft manufacturing, ...).
Typical applications of statistical experimental designs are :
- to identify importants factors out of many process variables (screening),
- to understand relationship between factors (main effects and interactions studies) ,
- to build a predictive model (response surface methodology) to find a region of optimum,
- to study the proportions of ingredients (mixture/formulation),
- to improve the quality of a product or to test the robustness of a process.