One of the more confusing aspects of learning Six Sigma, is the relationship between process Standard Deviation, which is denoted by the Greek letter sigma and the process Sigma value, known as Z.
When output data of a process is collected and analyzed, two of the first statistics to be calculated are the Mean and the Standard Deviation. The Mean, or average value, is compared to the process target, to see how accurately the process is actually performing. The Standard Deviation determines the spread of the data around the Mean, and is the prime measure of process variation. Clearly, the larger the Standard Deviation is, the worse the process is performing. The Standard Deviation of the process, denoted by the Greek letter , is NOT the process Sigma Value.
The process Z, on the other hand, relates the variation of the process to the output’s Specification Limits, relative to the process Mean. The process Sigma value is defined conceptually as the number of Standard Deviations which can fit between the Mean and the Specification Limit. If the process is performing well, with small variation, then the Standard Deviation of the output will be small, and many such Standard Deviations can fit between the Mean and the Spec Limit. The Sigma value of this process will be relatively large. On the other hand, if the process is “sloppy” with a large Standard Deviation, which is not a good situation, then few such Sigmas can fit between the Mean and the Spec Limit, and the process Sigma value will be small.
Phase 1: Measurement
This phase is concerned with selecting one or more product characteristics; i.e., dependent variables (Ys), mapping the respective process, making the necessary measurements, recording the results on process “control cards”, and estimating the short- and long-term process capability.
Phase 2: Analysis
This phase entails benchmarking the key product performance metrics. Following this, a gap analysis is often undertaken to identify the common factors of successful performance; i.e., what factors explains best-in-class performance. In some cases, it is necessary to redesign the product and/or process.
Having completed its process-characterization, the press-break team asks the Six Sigma Black Belt about the next steps to improve the process. The Six Sigma Black Belt explains the Process-optimization phases of the Breakthrough Strategy.
Phase 3: Improvement
This phase is usually initiated by selecting those product performance characteristics which must be improved to achieve the goal. Once this is done, the characteristics are diagnosed to reveal the major sources of variation. Next, the key process variables (Xs) are identified by way of statistically designed experiments. For each process variable which proves to give leverage, performance specifications are established.
Phase 4: Control
This phase is related to ensuring that the new process conditions are documented and monitored via Statistical Process Control methods. After a settling in period, the process capability would be reassessed. Depending upon the outcomes of such a follow-on analysis, it may be necessary to revisit one or more of the preceding phases.