Advance Innovation Group Explain about Measure Phase of Six Sigma

The measure phase of Six Sigma is one of the most important phases of the project, it revolves around data which is imperative for any Six Sigma project and the entire Six Sigma project revolves around data.

There is a great saying "Anything you cannot measure, you cannot Improve or Control" as for justification of improvements you will need to quantify the improvement and Quantification will only come from numbers and numbers from data.

So for data, the very first thing we do in a Six Sigma project is we design a Data Collection Plan wherein we define all the parameters of the data (Project Y) – the Operational definition, the defect definition, Performance Standard, Specification Limits, Formula Used, Unit of measurement, Decimal Places Used, Database, sampling plan etc. The purpose of this plan is to define the parameter of the data to ensure all the project team members and the management have the same understanding of the Project Y.

Data Collection Plan is followed by the process of Data Collection and when we collect data, there are chances of data being incorrect, fudged or manipulated; to check the correctness of the data we conduct the Measurement System Analysis (MSA) which helps in validating the data for its correctness, we as Six Sigma professionals always say that "Nothing in this world can be measured 100% Accurately, in any measurement we take, there is some amount of measurement error always present". So, whether to accept a measurement or not would depend on the magnitude of the measurement error or the criticality of the measurement.

Further, this Measurement Error is contributed either by the equipment or the operator, to check the measurement error contributed by the equipment, we conduct "Repeatability" and to check the measurement error contributed by the Operator, we conduct "Reproducibility"

Repeatability and Reproducibility help us validate the correctness of data, after the data is successfully validated we move ahead to calculate the Process Capability.

To measure Process Capability, there are different Indices such as Cp, Cpk, Z-value, and DPMO.

Cp and Cpk are Process Potential and Process Performance Indexes and are used for Continuous Data when the data is Normally Distributed and it has both sided specifications. In Cp we check whether 6 Standard Deviations fit between the Upper and Lower specifications of not and in Cpk, we check if 3 Standard Deviations fit between the Upper Specification and Mean or between Lower Specification and Mean. The target is to keep Cp and Cpk equal, as this is when the process is performing at its potential/as per the design.

Z Value represents the Sigma Level of the process and it is the number of standard deviations that Fit between the Mean and one of the specifications, it is used for continuous data whereas DPMO (Defects per Million Opportunities) is used for Discrete Data.