abhishreshthaa
Abhijeet S
In Six-Sigma process, 99.9996599% data will be within +/- 6 sigma levels, which is a -total of 12 sigma under the curve. To have a six-sigma process, 12 standard deviations should be able to fit in the permissible spread (customer specification limits). Let’s look at few terms:
LSL = lower specification limit
USL = Upper specification limit
Permissible Spread under the curve = USL - LSL
In Six-Sigma, we can conclude:
12*standard deviation (sigma value) = Permissible spread under the curve
Here’s a practical example:
The customer wants cloth of thickness 1mm +/- 0.001 mm, so the customer wants between 0.999 mm to 1.001 mm thickness.
LSL = 0.999 mm, USL = 1.001 mm
Permissible spread = USL – LSL = 0.002
Since, 12*standard deviation (sigma value) = Permissible spread under the curve so standard deviation (sigma value) = (0.002)/12 = 0.000167 for a six sigma process.
It is a highly disciplined approach used to reduce the process variations to the extent that the level of defects are drastically reduced to less than 3.4 per million process, product or service opportunities (DPMO). The approach relies heavily on advanced statistical tools. While these tools have been known earlier, these were primarily limited to the statisticians and quality professionals. Sigma is Greek letter that is used to describe variability.
In statistical quality control, this means "standard deviation". Most of us may be familiar with the normal distribution and its properties. We are aware of the properties of normal distribution:
99.73% of the area lies within mean m ± 3 sigma
95.46% of the area lies within mean m ± 2 sigma
68.26% of the area lies within mean m ± 1 sigma
When we proudly mention that our process capability Cp is 1.33, our process spread is ± 4 sigma. This would mean and estimated defect rate of 0.0063% or 63 defective parts per million (PPM).
Moreover, when we deploy processes in production, the mean of the process can shift to the extent of approximately 1.5 sigma. In such case the defect rate will increase to a much higher value.
This would be about 6200 PPM! If the process capability is improved to a Cp of 2.0 the PPM level will come down to 0.002. With a shift of 1.5 sigma, the Cpk will drop down to 1.5 and the number of parts defective will be about 3.4 PPM. A Cp of 2.0 corresponds to the process spread of ± 6 sigma. This is shown in the figures below.
LSL = lower specification limit
USL = Upper specification limit
Permissible Spread under the curve = USL - LSL
In Six-Sigma, we can conclude:
12*standard deviation (sigma value) = Permissible spread under the curve
Here’s a practical example:
The customer wants cloth of thickness 1mm +/- 0.001 mm, so the customer wants between 0.999 mm to 1.001 mm thickness.
LSL = 0.999 mm, USL = 1.001 mm
Permissible spread = USL – LSL = 0.002
Since, 12*standard deviation (sigma value) = Permissible spread under the curve so standard deviation (sigma value) = (0.002)/12 = 0.000167 for a six sigma process.
It is a highly disciplined approach used to reduce the process variations to the extent that the level of defects are drastically reduced to less than 3.4 per million process, product or service opportunities (DPMO). The approach relies heavily on advanced statistical tools. While these tools have been known earlier, these were primarily limited to the statisticians and quality professionals. Sigma is Greek letter that is used to describe variability.
In statistical quality control, this means "standard deviation". Most of us may be familiar with the normal distribution and its properties. We are aware of the properties of normal distribution:
99.73% of the area lies within mean m ± 3 sigma
95.46% of the area lies within mean m ± 2 sigma
68.26% of the area lies within mean m ± 1 sigma
When we proudly mention that our process capability Cp is 1.33, our process spread is ± 4 sigma. This would mean and estimated defect rate of 0.0063% or 63 defective parts per million (PPM).
Moreover, when we deploy processes in production, the mean of the process can shift to the extent of approximately 1.5 sigma. In such case the defect rate will increase to a much higher value.
This would be about 6200 PPM! If the process capability is improved to a Cp of 2.0 the PPM level will come down to 0.002. With a shift of 1.5 sigma, the Cpk will drop down to 1.5 and the number of parts defective will be about 3.4 PPM. A Cp of 2.0 corresponds to the process spread of ± 6 sigma. This is shown in the figures below.