Chemical experiments were done to quantify cause-and-effect relationships between adjustable parameters (inputs, factors, x) and the results (outputs, responses, y). They help to answer questions like:

• How do the ingredients and proportions of a mixture (inputs) influence its properties (outputs)?
• How do process parameters like temperature and stir-rate (inputs) influence the yield of a reaction and the purity of the end product (outputs)?
• Which settings offer the best compromise between conflicting aims, such as yield and purity?
• What range of inputs is permissible without causing out-of-specification outputs?

Six Sigma models and projects plays an important role in chemical industries specifically in the area of Design of Experiment, and Statistics to get conclusions and critical investment decision.