Similarly, for a 6σ process the Defects is as low as 3.4 in one million opportunities. For example, for a 2σ process the Defects are as high as 308,537 in one million opportunities. In the above table, you will observe that as the Sigma level increase the Defects decrease. Sigma Level vs DPMO Defects per Million Opportunities This is why it is good and it causes less defects beyond the lower and upper specification limits. Here with blue curve the majority of process outputs are around the desired average. As the process performance increases from 3σ to 6σ (blue curve), the process becomes centered between the upper and lower specification limits and does not have much variation. If the process improves from 2σ to 3σ (green curve), you will observe that the process variation reduces and the process has a larger peak (more outputs are around the desired average, but a different average than red curve). In the above figure, the red curve indicates a 2σ level of performance where we observe that its peak is very low (fewer outputs are around the desired average) and the variation is from extreme left to extreme right of the figure. Higher the capability, lower the defects. Sigma is also the capability of the process to produce defect free work. To reach a 6σ quality level in such a process, the standard deviation of car door length must be at most 0.00001 meter around the mean length. In order to smoothly assemble the door into the car, LSL can be 1.37179 meter, and USL can be 1.37191 meter. Specification Limits are derived from the customer requirements, and they specify the minimum and maximum acceptable limits of a process.įor instance in a car manufacturing system the desired average length (Mean length) of car door can be 1.37185 meter. LSL and USL stand for “Lower Specification Limit” and “Upper Specification Limit” respectively. Six Sigma stands for 6 standard deviations (6σ) between avarage and acceptable limits Obviously 7 or more σ processes are even better than a 6σ (Six Sigma) process, and yet throughout the evaluation and history of Six Sigma process, the practitioners gained the belief that a 6σ process is good enough to be reliable in almost all major situations except some systems whose defects can cause unrepairable consequences. This is the reason why a 6σ (Six Sigma) process performs better than 1σ, 2σ, 3σ, 4σ, 5σ processes. The more number of standard deviations between process average and acceptable process limits fits, the less likely that the process performs beyond the acceptable process limits, and it causes a defect. Standard Deviation (also known as Sigma or σ) determines the spread around this mean/central tendency. What is Sigma and Why is it Six Sigma? Mean is the arithmetic average of a process data set.Ĭentral tendency is the tendency of data to be around this mean.
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