1. THE 7 BASIC QUALITY TOOLS AS A PROBLEM SOLVING SYSTEM Kelly Roggenkamp

2. SEVEN BASIC QUALITY TOOLS Check sheets Pareto Charts Scatterplots / Stratification Histograms Control Charts Process Maps Cause and Effect Diagram (fishbone) or Affinity Diagram 2

3. CHECK SHEETS Simple data gather 3

4. CHECK SHEETS: What is a check sheet Isn’t this too simple to work? How to set up the check sheet Determine categories, operational definitions Organization of record keeping sheets Training of operators How to mark occurrences Where to mark occurrences Operational definitions Testing and calibration 4

5. CHECK SHEETS: Placement and facilitation of use Audits during study Data collection and analysis Graphical Analysis Pareto Analysis Scatterplots Stratification Histograms / distributions 5

6. PARETO CHART What is most important? 6

7. PARETO CHART Purpose Of A Pareto Chart A pareto chart is used to graphically summarize and display the relative importance of the differences between groups of data. When it is used A Pareto Chart points out the vital few from the trivial noise. Remember that sometimes you need to make the chart in two ways by count and cost then compare the results. A problem may not happen often so its bar is small (ie., # of file server crashes), but when it does happen the cost could be high (i.e.., cost of associates sitting around unable to process work). 7

8. PARETO CHART (PROCESS) Process The left Y axis is cost or frequency. Each bar is its contribution to the total of all bars. The right Y axis is in percentages, and the bars are connected by a cumulative line that ends at 100%. The X axis is each bar. 8

9. SCATTERPLOTS / STRATIFICATION What is related? 9

10. SCATTER PLOTS A Scatter Plot gives a graphical picture of variable “X” versus variable “Y” to see if one variable is correlated to another. It works with both attribute and variables data. A Scatter Plot will tell you if there is a relationship, A Scatter Plot may suggest you have a correlation (or cause and effect relationship) when that is not really the case at all! There may be something else that drives the correlation of both variables. In general, when the points on the graph fall along a straight line, this implies the points are correlated linearly. 11/8/201210 Strong Correlation Weak or no Correlation Positive Correlation Negative Correlation

11. SCATTER PLOT When it is used A quick first step using a graph to see if one variable is correlated (related) to another (i.e., as one variable goes up the other also increases). Process The X axis is the independent variable. The Y axis is the dependent variable. Hint – does Y change in response to changes in X? Minitab requires two columns, X and Y, to produce the Scatter Plot. Two important points about the data used in the Scatter Plot should be followed. One, make sure the range of X values is wide enough to represent what you are studying. Two, use data that is specifically collected for the study rather than adding other “interesting” variables after the fact. 11

12. STRATIFICATION Stratification uses categories to separate the data into slices to see if any of the categories appear to make a difference. 12

13. STRATIFICATION If we are concerned with cycle time, we graph scatterplots of cycle time vs all other continuous variables 13 No strong relationships

14. STRATIFICATION Stratification can also be used for attributes 11/8/201214 NO YES!

15. HISTOGRAMS Is the data normal? 15

16. HISTOGRAMS Is our data normal? This affects the process analysis tools we use, and shows the shape of the data. We can see how much the process varies. 16

17. CONTROL CHARTS When is the process out of control? 17

18. CONTROL CHARTS Control charts help us understand how our process performs, and keeps us from over-reacting to process outcomes that may or may not meet customer specifications, but are expected based on normal process variation 18

19. CONTROL CHARTS Often, customer specifications are difficult to meet due to the normal and expected variation of the process. Control charts help us to understand process performance over time. 19 Statistical process Upper control limit Customer specificatio n limit

20. CONTROL CHARTS Many types of control charts are available for use, and all are valuable in determining when we have a problem, and if our process has or has not changed Control charts are as valuable for letting us know when NOT to take action as they are for when to take action 20

21. PROCESS MAPS What does the process look like? Now that we know the quantity and category of problems, we can look at our process to understand the source 21

22. 22 PROCESS MAPS

23. 23 PROCESS MAPS Process maps help to understand your system May help you to understand simple system based issues

24. CAUSE EFFECT (FISHBONE) OR AFFINITY DIAGRAM What contributes to the issue? What is the root cause? 24

25. FISHBONE / AFFINITY 25

26. FISHBONE / AFFINITY 26

27. 27 FISHBONE / AFFINITY Help to identify root cause Help to identify possible solutions

28. 28 SUMMARY Check sheets – Simple data gather Pareto Charts – What is the problem? Scatterplots / Stratification – Where is the problem? Histograms – What does the population look like? Control Charts – Is this a process or specification problem? Process Maps – How does the process work? Cause and Effect Diagram (fishbone) or Affinity Diagram – What should we try to fix the problem?