1. 4-1 Collect & Interpret Data The Quality Improvement Model Use SPC to Maintain Current Process Collect & Interpret Data Select Measures Define Process Is Process Capable ? Improve Process Capability Is Process Stable ? Investigate & Fix Special Causes No Yes No Yes Collect & Interpret Data: Displaying Measures Purpose:Begin collecting and analyzing data from the process.

2. 4-2 Collect & Interpret Data Graphical Tools for Displaying Measures from Processes l Run Charts l Histograms l Pareto Charts

3. 4-3 Collect & Interpret Data Run Charts l A plot of the data in time order. l Time is on the horizontal axis and the data values are plotted on the vertical axis. l Run charts show the process variation over time. -100 -50 0 50 100 150 200 51015202530 Day Measure

4. 4-4 Collect & Interpret Data Histograms l A bar chart showing frequency of occurrence is shown on the vertical axis. l Histograms show the pattern of variation. -50050100150200 Frequency Measure 0 5 10 15 20 25

5. 4-5 Collect & Interpret Data Pareto Charts l A bar chart showing the relative importance of some observed characteristic. l The frequency, percent or cost is shown on the vertical axis. l The characteristic (type of defect, cause, etc.) is shown on the horizontal axis. l The characteristic is usually plotted in order of decreasing magnitude. Frequency Cause 0 5 10 15 20 25 CAEBDF

6. 4-6 Collect & Interpret Data Pump Maintenance For each week (time period) record the number of pump failures. One possible run chart would be to plot the number of pump failures for each week (time period). The opportunity for failures should remain constant from week to week. Collect information about causes for each failure for use in a Pareto Chart. Pareto Charts could also be based on pump location, pump environment, etc. Week # FailuresFailure Type 16Seal, Align... 21Fitting, Seal... 32Align, Gear... 44Seal, Fitting...... 207Align, Seal... Pump Maintenance Pump Maintenance Pump Failure Week 1Week 2Week 3Week 4Week 20 6 failed1 failed2 failed4 failed 7 failed

7. 4-7 Collect & Interpret Data Pump Maintenance Data Run Chart Number of Failures Week Pareto Chart SealAlignmentFittingGearOther 0 10 20 30 40 50 60 # Failures Type Failure Frequency 0-12-34-56-78-910-1112-13 0 1 2 3 4 5 6 Histogram # Failures

8. 4-8 Collect & Interpret Data Shipping Process Shipping On-Time Shipments Made On-Time Late On-Time For a specified time period: n = Shipments Made x = Late Shipments p = x/n A good run chart would be to plot p for each time period. A time period could be a week or month. It would also be good to collect other information about the late shipments for use in a Pareto Chart. Weekn# Late p Reason 175100.13 A,C,F... 28460.07 B,F,A... 378120.15 F,B,B........ 3070100.14 B,F,I...

9. 4-9 Collect & Interpret Data Shipping Data Run Chart 0.00 0.05 0.10 0.15 0.20 0.25 24681012141618202224262830 Proportion LateProportion Late Week 0.0500.0750.1000.1250.1500.1750.200 Histogram Frequency Proportion Late

10. 4-10 Collect & Interpret Data Purchase Order Process Purchase Order Process Purchase Order Process Completed Purchase Orders 5 Purchase Orders are selected each week. The time (in days) it took to process each of the 5 PO’s is recorded, and the average of the 5 calculated. The average is the measure tracked. A possibility would be to subgroup the data( i.e. combine 5 purchase orders and plot their average.) It might also be informative to plot a histogram of all the times to see the pattern of variation. WeekABCDEAverage 1275454.6 23 102534.6 3573 1215.6 4478355.4.............. 20339244.2 Week 1 Week 2 Week 3 Week 4 Week 20 2,7,5,4,5 3,10,2,5,3 5,7,3,12,1 4,7,8,3,5 3,3,9,2,4

11. 4-11 Collect & Interpret Data Purchase Order Data Run Chart of 20 Averages (of size 5) Time (Days) Histogram of 100 total observations Time (Days) Frequency Week Sample Taken 123456789101112131415>15 0 5 10 15 20 25

12. 4-12 Collect & Interpret Data Polymer Manufacturing Process One possibility would be to collect a sample of the product every 4 hours, and measure the characteristic of interest on that sample. A run chart could then be constructed of this data. It would also be informative to plot a histogram of all the times to see the pattern of variation. Production Process Material Produced (lots) Samples A quality characteristic is measured on each sample. Sample b* 11.51 21.89 31.42.. 1341.63 b* is a measure of yellowness

13. 4-13 Collect & Interpret Data Polymer Manufacturing Data 0 1 2 3 4 5 6 20406080100120140 b* Sample Run Chart Note: b* is a measure of yellowness LS is the Lower Specification Limit US is the Upper Specification Limit 012345 b* Histogram LS US

14. 4-14 Collect & Interpret Data Real data from Organic Chemicals Division. Found in the Hq file in the Minitab Datasets folder. Minitab: Open the Dataset

15. 4-15 Collect & Interpret Data Make a run chart of the HQ % Water data by following the instructions below. The final output should look like this: Minitab: Making a Run Chart

16. 4-16 Collect & Interpret Data Minitab: Creating a Histogram Make a histogram of the HQ % Water data by following the instructions below. The final output should look like this:

17. 4-17 Collect & Interpret Data Minitab: Copy and Paste Output into PowerPoint If you paste the graph into PowerPoint, you can double-click the graph to edit it using MINITAB. To make the graph “static” and reduce its file size, select “Edit ► Paste Special…” and select a Picture format.

18. 4-18 Collect & Interpret Data The Catapult Process Distance (inches) 30 Consecutive “deliveries” were made. One set of conditions was used. Landing Point

19. 4-19 Collect & Interpret Data Catapult Data 96.0 98.0 100.0 102.0 104.0 106.0 108.0 110.0 112.0 114.0 116.0 118.0 120.0 24681012141618202224262830 Distance (inches) Run Order Run Chart 100105110101102103104106107108109111112113 1 2 3 4 5 6 7 0 Distance (inches) Frequency Histogram

20. 4-20 Collect & Interpret Data Exercises 1.)Your Catapult Team should complete pages 6 and 7 of the blue “Catapult Process” handout. 2) Be ready to make a PowerPoint presentation of your results. Limit yourselves to 15 minutes for this exercise.