Stages of DOE

Designed experiments are usually carried out in five stages -- planning, screening, optimization, robustness testing, and verification.

Planning

It is important to carefully plan for the course of experimentation before embarking upon the process of testing and data collection. A thorough and precise objective identifying the need to conduct the investigation, assessment of time and resources available to achieve the objective and integration of prior knowledge to the experimentation procedure are a few of the considerations to keep in mind at this stage. A team composed of individuals from different disciplines related to the product or process should be used to identify possible factors to investigate and determine the most appropriate response(s) to measure. A team-approach promotes synergy that gives a richer set of factors to study and thus a more complete experiment. Carefully planned experiments always lead to increased understanding of the product or process.

Screening

Screening experiments are used to identify the important factors that affect the system under investigation out of the large pool of potential factors. These experiments are carried out in conjunction with prior knowledge of the system to eliminate unimportant factors and focus attention on the key factors that require further detailed analyses. Screening experiments are usually efficient designs requiring a few executions where the focus is not on interactions but on identifying the vital few factors.

Optimization

Once attention is narrowed down to the important factors affecting the process, the next step is to determine the best setting of these factors to achieve the desired objective. Depending on the product or process under investigation this objective may be to either maximize, minimize or achieve a target value of the response.

Robustness Testing

Once the optimal settings of the factors have been determined, it is important to make the product or process insensitive to variations that are likely to be experienced in the application environment. These variations result from changes in factors that affect the process but are beyond the control of the analyst. Such factors as humidity, ambient temperature, variation in material, etc. are referred to as noise factors. It is important to identify sources of such variation and take measures to ensure that the product or process is made insensitive (or robust) to these factors.

Verification

This final stage involves validation of the best settings of the factors by conducting a few follow-up experiment runs to confirm that the system functions as desired and all objectives are met.