1. Statistical process control

2. TOOLS OF TQM

3. Statistical interpretation
INTRODUCTION
Data-Driven Methodology
Data generated by processes
Statistical interpretation
Seasonal variations
New Technology

4. THE ‘SEVEN SIMPLE TOOLS’
Flowcharts
Cause and Effect (Ishikawa / fishbone) Diagrams
Check sheets
Pareto Charts
Histograms
Run Charts and Control Charts
Scatter plots and Correlation Analysis

5. Patient Transport Process Example
Request made
Log & prioritize request
Dispatch transport
Take patient to X-ray
Doctor determines patient needs X-ray
Information taken & request is logged
Required equipment is found
Transporter arrives on ward
Patient transferred from bed
Ward contacts dispatcher
Request prioritized
Transport is dispatched
Patient taken to X-ray

6. Types of Flowcharts
LAYOUT FLOWCHART
DATA FLOW DIAGRAMS

7. ISHIKAWA DIAGRAMS Also known as Fishbone or Cause-and-Effect Diagrams
Non-quantitative tools (Qualitative)
Sometimes called the 5M Diagram (Men, Machine, Materials, Measurements and methods)

8. ISHIKAWA DIAGRAM

10. CHECKSHEETS Central tool for Quality Assurance programs
Specially useful for operational procedures
Could be derived from the flowchart and fishbone diagrams

11. Example check sheets Patient Transport Problem Sheet
Area: Ward 3b Period: June 1996
Type
Tally
Subtotal
Equipment broken
IIIII 5
Patient not ready
IIIII II 7
Not enough staff
III 3
Patient having another exam etc.
IIIII IIIII II 12

12. The Basic Seven (B7) Tools of Quality
Control Charts
Deviation from Mean
Upper and Lower Spec’s
Range
Control charts are a means of regulating a process. It tracks the output of a process and its conformance to the company’s standards. As long as the process stays within the upper and lower limits then the process is “safe” and normal. Any observations made outside of the limits are irregular and problematic. They need to be immediately researched to improve quality. A process that consistently stays “safe” is a good quality process.

13. Control Charts Upper Limit Lower Limit Unacceptable deviation X
X= mean
The majority of observations have fallen close the average. The one that’s under the lower limit is irregular, it needs to be examined and fixed.
Unacceptable deviation

14. Control Charts
Acme Pizza Management wants to get in on the control chart action
Average Diameter = 16 inches
Upper Limit = 17 inches
Lower Limit = 15 inches
The average Diameter can be calculated by taking the average of a sample number of pizzas. As long as the sample’s average is close enough to 16 inches to satisfy management (ex. Within +/- .01 inches) then the average can be said to be 16 inches. Then from that management can decide what is the biggest/smallest allowable pies that are acceptable.

15. Acme example Control Charts
Upper Limit
17 inches
Lower Limit
15 Inches X
16 inches=
Monitoring the pizza process, this example shows how almost every pie is within specifications. The process should be analyzed to discover why the one small pie was produced and corrected to improve quality.
Small Pie

16. The Basic Seven (B7) Tools of Quality
Scatter Plots
2 Dimensional X/Y plots
Used to show relationship between independent(x) and dependent(y) variables
Scatter plots take place on an X and Y graph. Whichever variable is on the bottom should be the dependent variable. This means that the Y variable changes according to changes in X. In the upcoming example, Minutes cooking the pizza’s will directly affect the number of defective pies that are produced.
Scatter plots are useful for finding direct or indirect relationships which can then be used to analyze/improve quality.

17. Acme Pizza (Scatter Diagram)
Minutes Cooking Defective Pies In this simple example, you can find the existing relationship without much difficulty but…
This is meant to show the data. It isn’t too difficult for students to see that there is a direct relationship between Minutes cooking and defects. But the Scatter Plot will make this easier to see.

18. Scatter Diagrams Easier to see direct relationship Defective Pizzas
There is a direct relationship between time spent cooking by employees and defects. As Time cooking increases, so does the amount of defects.
Time Cooking (minutes)

19. Scatter Diagrams As a quality tool
What does this tell Acme management about their processes?
Improvements?
Answer: There is obviously some kind of process problem with the number of defective pies being produced. Maybe the cooks are getting sloppy from working too fast. Or maybe morale is low and there is just apathetic work being done. Whatever the case, if this was actually happening, quality improvements would have to be studied and implemented.
Defective Pizzas
Time Cooking (minutes)

20. The Basic Seven (B7) Tools of Quality
Run charts
Time-based (x-axis)
Cyclical
Look for patterns
Run Charts are used to plot data based on time. It’s very useful for identifying trends and cycles. The X-axis is usually the time element and the y axis is the process to be tracked. The following slide shows another Acme example that should make this easy to understand.

21. Run Charts PM- AM PM- AM PM- AM 8 9 10 11 12 1 2 3 4
Slices/hour
Ask the class what trends they can identify. Week 2’s Thursday was a rainy day. Business Peaks between 1 and 3 each night so this is very valuable information to the management. Also with the exception of the rainy day, business seems to increase with warmer weather. Have the class come up with any other trends they can see or ideas to help improve quality based on this information. Such as higher staffing between 1 and 3 or higher inventory levels/preparation etc.
Time
PM- AM
PM- AM
PM- AM
Thursday
Week 1
Thursday
Week 2
Thursday
Week 3

22. New Management Tools 1. WHY, WHY 2. FORCED FIELD ANALYSIS 
Define the objective.
 Determine criteria for evaluating the effectiveness of the improvement action.
 Brainstorm the forces.
 Prioritize the forces from greatest to least.
 Take action.

23. 3. NOMINAL GROUP TECHNIQUE
4. AFFINITY DIAGRAM
5. INTER-RELATIONSHIP DIGRAPH
6. TREE DIAGRAM
7. MATRIX DIAGRAM
8. PRIORITIZATION MATRICES
9. PROCESS DECISION PROGRAM CHART
10.ACTIVITY NETWORK DIAGRAM