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Six Sigma Training

Six Sigma Training. Dr. Robert O. Neidigh Dr. Robert Setaputra. Process Out of Control. Point above UCL or below LCL 9 consecutive points on one side of center line, indicates that process mean has shifted 6 consecutive points increasing or decreasing, signals a drift in the process mean

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Six Sigma Training

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  1. Six Sigma Training Dr. Robert O. Neidigh Dr. Robert Setaputra

  2. Process Out of Control Point above UCL or below LCL 9 consecutive points on one side of center line, indicates that process mean has shifted 6 consecutive points increasing or decreasing, signals a drift in the process mean 14 consecutive points alternating up and down, indicates that two systematically alternating causes are producing different results 2 out of 3 consecutive points in Zone A or beyond, early warning of a process shift, probability of a Type II Error is approximately 2%

  3. Process Out of Control cont. 4 out of 5 consecutive points in Zone B or beyond, early warning of a process shift, probability of a Type II Error is approximately 2% 15 points in a row in Zone C, indicates less variability than expected, would like to determine why 8 consecutive points in Zones B and A or beyond on either side of the center line, indicates that different samples are affected by different factors resulting in a bimodal distribution of means

  4. Causes of Variation Common causes – causes of variation that are inherent in the process, responsibility of management to change the policies and procedures that define the process, qualitative tools can be used to help make changes Assignable causes – causes of variation that are not inherent in the process, responsibility of the workers and engineers, control charts are used extensively

  5. Process Capability Compares the output of an in-control process to the specification limits by using capability indices. Capability indices are ratios between the spread of the specification limits and the spread of the process. Two capability indices: Cp Cpk

  6. Cp σ known: Cp = (USL – LSL)/6σ σ unknown: Cp = (USL – LSL)/6S The higher, the better!

  7. Cp USL – LSL 6σ 8σ 10σ 12σ Cp1.00 1.33 1.66 2.00 Rejects 0.27% 64 ppm .6 ppm 2 ppb % of spec 100 75 60 50 Assumes mean is centered in specification limits

  8. Cpk σ known: Cpk = min[(USL – μ)/3σ, (μ – LSL)/3σ] σ unknown: Cpk = min[(USL – x-bar)/3S, (x-bar – LSL)/3S] The higher, the better!

  9. Qualitative Tools Cause and Effect Diagram Root Cause Analysis – 5 Whys Failure Mode and Effects Analysis (FMEA)

  10. Cause and Effect Diagram Used to organize possible sources of variation in a CTQ Fishbone diagram Page 151

  11. Root Cause Analysis Ask what causes the problem Write down the answer If answer does not identify root cause of the problem, ask why again Continue until root cause is identified 5 Whys is rule of thumb

  12. FMEA Considers at causes of failures Redesign process to eliminate or minimize future failures Assigns risk priority number (RPN) based upon scales of severity, likelihood of occurrence, and detection The higher the RPN, the more important the failure After redesign, reassign RPN Pages 156 - 160

  13. What does Six Sigma Represent? Voice of the Process (VoP) should take up no more than half of the Voice of the Customer (VoC). Plus or minus 3σ should take up no more than half of the specification limits. Thus, the specification limits should be no less than plus or minus 6σ. If the mean is centered, than the defect rate is 2 ppb!!! It is common for process variation to increase periodically and then drop back to the normal level. Studies have shown that this increase is equivalent to a 1.5σ shift in the mean. When this occurs, the defect rate is still only 3.4 ppm. This is why quality in six sigma is defined as 3.4 ppm!

  14. Analyze Step and Six Sigma The tools provided in this section are used to decrease process variation, properly center the process mean, and to eliminate waste or unnecessary steps. Also, by listening to the VoC the process specifications can be properly determined. Control charts are not just tools to control a process, but more importantly are used to decrease variation through the detection and elimination of assignable causes of variation.

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