- Full factorial, partial factorial
- Surface Response modeling
- Optimization of settings
- Identifying key inputs variables
- Goal based design, experiment design
Design of experiment (DOE) is a systematic method to determine the reLationship between factors affecting a process and the output of that process. In other words, it is used to find cause-and-effect relationships. This information is needed to manage process inputs in order to optimize the output. An understanding of Design of experiments (DOE) first requires knowledge of some statistical tools and experimentation concepts. Although a Design of experiments (DOE) can be analyzed in many software programs, it is important for practitioners to understand basic DOE concepts for proper application. Well-performed Design of experiments (DOE) may provide answers of questions such as:
- What are the key factors in a process?
- At what settings would the process deliver acceptable performance ?
Design of experiment (DOE) is powerful technique for discovering set of process or design variables which are most important to process/product/system and then assisting experiments to determine at what levels these variables should be set/kept to optimize performance.