1. Business Moment Whether you think you can or whether you think you can't, you're right! Henry Ford

2. Fundamentals of Statistical Process Control. SPC

3. Statistical Process Control SPC is a tool for obtaining cost effective quality, achieved by process monitoring and forecasting techniques which are used to predict problems before they occur. (defect prevention)

4. Reliability Rework Insp. Rework Corrective Action Prevention Inspect $ $ Quality +- Where should you spend your money? Increased Reliability

5. Detection vs. Prevention Manufacture SPC Ship Inspect & Sort Ship Scrap or Rework Prevent $ Manufacture Feedback Old method New Method

6. Elements of Quality - Zero Defects (Implied or specified) - Conformance to Specification - Reliability (life & uptime) - Functionality (does what’s intended) - Price (competitive for performance) - Delivery (received on promise date) - Service and Support (incl. Warranty)

7. Normal Variation Variable Data 68% 95% 99.7% Six Sigma.5.4.3.6.7.2.8 X -1  -2  -3  +3  +2  +1  Individual Measurements, the same values stack up. Variable Data is data that can be measured.

8. Sample Quantity -1 0 +2 3 -1 0 +2 3 -1 0 +2 5 3 -2 -1 0 +1 +2 +3 -1 0 +2 -1 0 +1 20 3 -2 -1 0 +1 +2 +3 0 -2 -1 0+1 +2 -1 0+1+2 –1 0+1+2 3 -2 -1 0 +1 +2 +3 -2 -1 0 +1 +2 3 -2 -1 0 +1 +2 +3 -2 -1 0 +1 +2 -1 0+1 –1 0+1+2 0 40 23 102 xxx xxxxx xxxxxxx xxxxxxxxx xxxxxxxxxxx xxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxx x It takes approximately 30 samples to assure the normal bell shape.

9. Any Measurement! Range height 76-60 = 16 in. Range of weight could be 300-60 = 240 lb Mean (Center) height = 68 in. Mean weight = 180 lbs

10. Increment of Measurement Fewer points make bell shape Takes more points to define bell shape..005 range per block.001.002.005.016.019.018.017.016.018.017.0#.00#

11. Histogram 4.5 to 5.55.5 to 6.56.5 to 7.5

12. Process Control A process is “In Control” if products vary CONSISTENTLY within expected limits over TIME. Normal expectations when displayed by frequency of occurrence will present a curve or distribution showing a central peak and tapering off smoothly to tails on either side..5.4.3.6.7.2.8 When the normal distribution exits the process is operating consistently and we can predict the process behavior.

13. Controlling a Process 2. Get the Process to a normal distribution. (Remove assignable causes) You don’t want to control a broken process. 1. To control a process means to keep the bell shape normal. 3. Monitor the process property at an interval that can detect deterioration of the property and allow correction before rejections. Example: If the property was effected by a belt that wears over time, checking once a week may be adequate. If the property were to use a batch of epoxy in the working range before it cures to much, checking every 15 minutes would be appropriate. (The time interval is called “Frequency”) 4. Take corrective action before defects are produced.

14. Assignable Causes Easy to identify and correct. (low cost)

15. What is poor Quality? Not meeting customer expectations, implied or specified!

16. B A Customer Dis-satisfaction Target Lower SpecUpper Spec A = more variation on target? or B = less variation off target? Reject No Question Perfection – Not Required

17. What causes defects? 6 M’s Man (associated operator error) Machine (improper, misadjusted or broken) Material (wrong or defective) Measurement (wrong, bad or misread instrument) Method (improper, unclear or incomplete) Mother Nature (environment – temp – moisture …)

18. Good or Bad? 66 66 Customer Specification Bad (Out of Spec.) The Bell shape has nothing to do with good/bad only Normal. LCL UCL

19. When do you have rejects? When Specification Limits are imposed. (Customer or Company Spec.)

20. Capability USL xxx xxxxx xxxxxxx xxxxxxxxx xxxxxxxxxxx xxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxx LCLUCL LSL USL Capable Not Capable 66 CP Specification Limits Control limits

21. Precise and Accurate Not Precise and Not Accurate Accurate and not Precise Precise and Not Accurate

22. Capability Improvement Variation Reduction

23. Capability xxx xxxxx xxxxxxx xxxxxxxxx xxxxxxxxxxx xxxxxxxxxxxxx xxxxxxxxxxxxxx x xxxxxxxxxxxxxxxxx xxx xxxxx xxxxxxx xxxxxxxxx xxxxxxxxxxx xxxxxxxxxxxxxx xxxxxxxxxxxx xxxxxxxxxxxxxxxxx Six Sigma Normal Shift CPk US L Not Capable Capable Avg. USL Avg-USL/3  /2 Or LSL-Avg/ 3  /2 Cpk=min

24. Variation of the Mean

25. Two Distributions Working Together xxx xxxxx xxxxxxx xxxxxxxxx xxxxxxxxxxx xxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxx xxx xxxxx xxxxxxx xxxxxxxxx xxxxxxxxxxx xxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxx Bimodal Six Sigma (Movement: right, left or up, down or clockwise, counterclockwise …) (mixed materials, different lots of material, different operators…) (If parts tighter tolerance parts were selected out it would look like this.)

26. Control Limits, the six sigma points 6 sigma Mean (Average) LCLUCL +3  - 3 

27. Making a time related distribution. Display the measurements in the order taken. Each point is an average from the samples measured (5 smpls)

28. Add Control Lines to charts 6 sigma Mean (Average) LCL UCL +3  - 3 

29. Xbar and Range Charts Xbar = X = The average of measured samples (5) Range = R = Highest reading – Lowest reading in sample (5)

31. Plotting Procedure 1. Take five measurements / data points, noting any decimal points required. 2. If you are using the current date and time skip step 3. 3. Enter your earlier date and time in military format 10/18/03 14:15 in the Override Date/Time cell 4. Enter your data into the cells provided. Sample 1 2 3 4 5 (Yellow cells) (Note: Click on the yellow Cell under the number 1 to start entering data, use the Tab key to move to the next cell.) 5. On the last entry use the down arrow to enter and proceed to the Initials cell (otherwise click the Initials cell). Enter your Initials, Press Tab. 6. Press the "plot button" in the lower right corner and observe that your data point has been plotted. 7. If there appears to be an error in the data, you can click on the defective data and reenter it. Press Tab, then click the Replot Button. 8. Once the point is correctly plotted, Observe if any Run Rules have been violated. If not, enter "none" in the action cell, then click the "Tab then Action Button." (lower right corner). Otherwise, take and log the corrective action taken. 9. Observe that the data cells are empty, indicating a successful transaction. The lower scroll pane (two rows at the bottom of screen) can be used to observe the calculations and action entered. (Just click the down scroll arrow until the last row is displayed. (80 rows maximum can be entered.) Run Rules 1. Any point that crosses the upper or lower control limit on the XBar Chart or the upper control limit on the R Chart. 2. 7 points in a row on one side of the center line on the Bar Chart. 3. 7 points in a continuing upward or downward direction on the Bar Chart or R - Range (lower) chart (Trend). 4. 7 points in a row at the upper and lower extremes (no points on or near the centerline) Bar Chart. 5. 7 points in a row clustered closely around the center line on the X Bar Chart (Capture improvement or speed up the process). 6. 7 points in a row clustered near bottom of R Chart or trending toward bottom (Capture improvement or speed up the process)

32. Run Rules (normal no action required) Any point that crosses the upper or lower control limit on the Xbar Chart or the upper control limit on the R chart. Xbar (upper chart) Range – R (lower chart) * Note random points, some near control lines some near center.

33. Run Rules (when to take action) Any point that crosses the upper or lower control limit on the Xbar Chart or the upper control limit on the R chart. Xbar (upper chart) Range – R (lower chart) * Check for possible bad measurement or data entry error.

34. Run Rules (when to take action - Run) 7 points in a row on one side of the center line on the upper chart. Xbar (upper chart) Or *Check material, lot, operator, machine adjustment…

35. Run Rules (when to take action - trends) Xbar (upper chart) Or 7 points in a continuing downward or upward direction on X chart * Check machine wear, material, method or operator fatigue…

36. Run Rule (when to take action - trends) Range R (lower chart) Or 7 points in a continuing downward or upward direction on R chart Improving – capture or speed up Getting Worse - correct * Check machine wear, material, method or operator fatigue…

37. Run Rule (clustered points) 7 points in a row clustered around the center line on the Xbar chart or clustered around zero (bottom line) on the R Range chart Xbar (upper chart) Range – R (lower chart) Improved – capture or speed up “Over controlled” If bell was normal points would be near the edges.

38. Run Rules (when to take action – Unusual pattern) Xbar (upper chart) No points near the center (possibly bimodal) *Two lots of material, two operators, selected parts removed…

39. Attribute Data Non-measurable data Good, Bad; Pass, Fail; True, False; Go, NoGo; Present, Missing… Charts: P (Percent Defective), NP (Number Defective) C (Defects per unit), U (Defects per Subgroup) Simple if sample size is constant and equated easily to 100. Ex: Number defective from sample 50 multiply by 2, 25x4, 10x10, 5x20, 2x50 EXAMPLE: 5 bad in sample of 25 (5x4) =20% The software will do the math but keeping a fixed sample size is preferred. Fixed sample size will keep the control lines straight and understood.

41. Plotting Procedure 1. Count out the sample size and note the number defective. 2. If you are using the current date and time skip step 3. 3. Enter your earlier date and time in military format 10/18/03 14:15 in the Override Date/Time cell 4. Enter your data into the cells provided. Sample Size, Qty Defective (Yellow cells) (Note: Click on the yellow Cell to start entering data, use the Tab key and or arrow keys to move to the next yellow cell.) 5. On the last entry use the arrow keys to enter and procede to the Initials cell (otherwise click the Initials cell). Enter your Initials, Press Tab. 6. Press the "plot button" in the lower right corner and observe that your data point has been plotted. 7. If there appears to be an error in the data, you can click on the defective data and reenter it. Press Tab, then click the Replot Button. 8. Once the point is correctly plotted, Observe if any Run Rules have been violated. If not, enter "none" in the action cell, then click the "Tab then Action Button." (lower right corner). Otherwise, take and log the corrective action taken. 9. Observe that the data cells are empty, indicating a successful transaction. The lower scroll pane (two rows at the bottom of screen) can be used to observe the calculations and action entered. (Just click the down scroll arrow until the last row is displayed. (80 rows maximum can be entered.) Run Rules 1. Any point that crosses the upper or lower control limit on the P Chart 2. 7 points in a row on one side of the center line. 3. 7 points in a continuing upward or downward direction on the P chart (Trend). 4. 7 points in a row at the upper and lower extremes (no points on or near the centerline) 5. 7 points in a row clustered near bottom of R Chart or trending toward bottom (Capture improvement or speed up the process)

42. The End