1. 1 Six Sigma Green Belt -6-4-2024 6 Process Capability Analysis Sigma Quality Management

2. 2 Six Sigma Green Belt Capability Defined: “How well does our process' output (product or service) meet the valid requirements of the customer?”

3. 3 Six Sigma Green Belt Frequency Charts Frequency Number of Shipping Errors (each Day) 1 2 3 4 5 6 7 8 9 25 20 15 10 5 Date: 1/2/96 Prep’d: NPO Average = 3.2 errors/day

4. 4 Six Sigma Green BeltHistogram 0.0 6.0 12.0 18.0 24.0 30.0 Fill Weights (lbs) 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 Histogram– Refrigerant Fill Weights (lb.)– Manual Process Frequency Average- 7.6 lbs Date: 6/95 Prep’d: M. Lippen

5. 5 Six Sigma Green BeltInterpretation

6. 6 Six Sigma Green Belt Interpretation (Continued)

7. 7 Six Sigma Green Belt Capability - Picture One-Sided Specification

8. 8 Six Sigma Green Belt Capability - Picture Two-Sided Specification

9. 9 Six Sigma Green Belt Inherent Process Capability Customer's Tolerance = Upper Specification Limit - Lower Specification Limit Reasonable Width of Process Variation – 6 Standard Deviations Quality Characteristic Mean Region A Region B Region C

10. 10 Six Sigma Green Belt Inherent Process Capability - Cp Inherent Process Capability = Upper Specification - Lower Specification 6 x Process Standard Deviation Inherent Process Capability = |Specification - Process Mean| (One Spec Only) 3 x Process Standard Deviation

11. 11 Six Sigma Green Belt Cp Values

12. 12 Six Sigma Green Belt Operational Process Capability - Cpk

13. 13 Six Sigma Green Belt Process Capability Studies  Raw material sources,  Operators,  Gauge users,  Production rates, and  Environmental conditions.

14. 14 Six Sigma Green Belt Assessing Process Capability - Steps 1.Accumulate data in subgroups of consecutive parts taken periodically from production runs. If the same process produces a variety of part numbers with different target dimensions, each different part should be treated as a separate process unless we have evidence that the variation about the targeted dimension is not affected by the normal value. 2.Data should be accumulated over a long enough period of time that all sources of variation have an opportunity to be exhibited (25 subgroups of 4 taken over a “long” period of time is a guide). Check for process stability. 3.Test the data for shape of distribution. 4.If the distribution is normal, compute the standard deviation based on individuals. If the data is not normal, either transform the data or perform a capability analysis using the Weibull distribution (see Minitab, Help topics, process capability: non-normal data for more information). 5.Calculate Pc based on six standard deviations divided into the available tolerance. 6.Calculate Pc using standard deviation based on the average range. Compare this with the value obtained in step 5 to see what the potential of the process is given better controls or improved stability of mean performance.

15. 15 Six Sigma Green Belt Capability and Six Sigma -6-5-4-3-20123456 Lower Specification Limit Upper Specification Limit Mean Standard Deviations

16. 16 Six Sigma Green Belt Calculating Sigma – Measurement Data Lower Specification Limit Upper Specification Limit Mean Measure Area 1 Area 2

17. 17 Six Sigma Green Belt Calculating Sigma – Discrete Data

18. 18 Six Sigma Green Belt First, Final, Normalized, Rolled-TP Yield

19. 19 Six Sigma Green Belt Sigma Assessment - Example Market Product Execute Transaction Complete Transaction

20. 20 Six Sigma Green Belt Sigma Scorecard Calculated Using Basic Sigma Method for Discrete Data Calculated Using Normalized Yield Formula and Short Term Sigma The Product of Sub- Process Yields (and Failed Trade Yield)