Six Sigma DMAIC

Six Sigma methodology aims to reduce variation in the output (Y) of a process using a Define, Measure, Analyse, Improve, Control (DMAIC) approach to identify and control the key process input variables (Xs) that contribute to the variation in the output.

The Lean Principles that help solve these situations and prevent them occurring in the first place

• Define. The define phase involves selecting the projects to improve that are most important to satisfying customers’ requirements and improving the performance of the business. Within this phase the measure of the process output (Y) that is critical to satisfaction (CTS) is identified and defined. A project charter is completed that contains the problem statement, measurable objective, business benefit, team selection and sponsorship.
• Measure. The current state of the process is mapped, key process output and input variables identified and the baseline performance determined. It is also important to ensure that the method of measuring the performance of the process gives accurate and consistent results. In determining the baseline performance of the process an efficient data sampling plan is conducted to identify key sources of variation in the process output.
• Analyse. The root causes of variation in the process output are determined with statistical confidence through data analysis and experimentation. Pareto Analysis is a key tool of the analysis phase along with other graphical analysis; multivari studies; hypothesis testing and design of experiments.
• Improve. The relationships between the key process inputs and the outputs are identified through regression analysis and design of experiments. The process specifications and tolerances are determined that provide an improved or optimised performance of the output of the process.
• Control. A control plan is identified and implemented that comprises monitoring the process and responding to changes in the process; training of process personnel in standard procedures; maintenance procedures for the process; audits of the process and appropriate corrective actions; control of measuring systems including calibration and repeatability and reproducibility (R&R) studies; mistake proofing techniques; statistical process control (SPC).