2 Sigma Limits vs 3 Sigma Limits
Two sigma limits and 3 sigma limits are indicators of the accuracy of the measurement method used in control charts.
Sigma is the measure of standard deviation or, the extent to which data can vary in a given distribution. A smaller sigma level denotes less variability, or close data points.
Two sigma limits indicate data chosen randomly from a set of normally distributed data that has a 95% of probability of being within the acceptable standard deviation.
Three sigma limits indicate data chosen randomly from a set of normally distributed data and has a 99.73% of probability of being within the acceptable standard deviation, translating into a possibility of 1,350 defects per million opportunities.
A 2 sigma control limit, therefore, indicates the extent to which data deviates from the 95% probability, and a 3 sigma control limit indicates the extent to which the defects deviate from the acceptable 1,350 defects.
In statistical control, 1 sigma is the lowest sigma and 6 sigma the highest. A process attains stability when data in the control chart falls within 3-sigma limits from the standard deviation. For this exact reason, the traditional control chart formulated by Walter Shewhart in 1924 and most control charts since have used 3-sigma limits to test the deviance of data.