Design of experiments.

Design of Experiments

Design of Experiments (DOE) is an efficient structured and proven approach for investigating
a process in order to understand and enhance its performance. DOE is a highly educational
investigative approach in the variables which influence a process and the resulting quality of products and services in an experimental setting, putting you in a position to effectively analyze and interpret the data thus giving you the best information to enhance all aspects of the production environment.

Experiments are a vital tool in Six Sigma. They give us prototypes to evaluate and test our hypotheses in a controlled setting. This reduces risk, and builds confidence as well as act as a bridge between models and the working world. Unfortunately, time and resources for experiments are limited. People are impatient and many times the experiment is seen as a hurdle. Therefore, it is important to view the experiment as a useful tool, and mini-project. Then, consume resources, including as much personnel as permitted, equipment, and materials. Yes, experiments cost money and time, but they do so because they are the bases for the working process.

The four steps you should follow in your experiment are:

Define your problem. Know the nature of the problem you intend the experiment
to solve.

Define your objective. It is vital that your experiment is focused on producing
a specific and practical piece of information.

Define your experiment. Use as many DOE tools available to design a project,
which will satisfy your objective.

Develop your plan. You need to thoroughly analyze all conditions: the environment, background, conditions, which will guide or constrain your experiment. Then develop a plan, which will meet the objectives of the time and recourses you have been given.

Create a data collection plan and ensure you have the measurement system in place.

Lastly, you need a data analysis plan, which will account for the work required to correctly interpret your results.

The purpose of DOE is to concurrently understand the effects of changing the settings of multiple variables, without actually creating the changes in the process. This is where mistakes made are used as a tool to discover deficiencies, which will save the corporation in the end.

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