1. Quality Control Tools
Rabin Bhandari

2. 7 Quality Control Tools
 designation given to a fixed set of graphical techniques
identified as being most helpful in troubleshooting issues
related to quality.
 are called basic because they are suitable for people
with little formal training in statistics and because they
can be used to solve the vast majority of quality-related
issues.

3. Seven Quality Control Tools are:
 Cause-and-effect diagram (also known as the "fishbone"
or Ishikawa diagram)
 Check sheet
 Histogram
 Pareto Chart
 Flow chart
 Scatter Diagram
 Run chart

4. 1. Cause-and-effect diagram
 tool to analyze and illustrate a process by showing the main causes and
sub causes leading to an effect.
 also known as “ Ishikawa Diagram” and “ fishbone diagram”
 Constructing steps:
a. Identify the problems
b. Draw spines and bones
c. Identify different areas where problem may arise from
d. Identify what these specific causes could be
e. Use the finished diagram to brainstorm solutions to the main
problems

5. 1. Cause-effect diagram
Material Machine/Plant Measurement/ Policies
Men/People Methods/Procedures
Quality
Problem

6. Cause-effect diagram
 6 basic categories also known as 5ME
a. Man
b. Method
c. Machine
d. Material
e. Measurement
f. Environment

7. 1 .Why should we use cause-and-
effect diagram?
 It helps to determine the root cause of a problem or quality
characteristic using a structured approach
 It encourages group participation and utilizes group knowledge of
the process
 They use an orderly, easy-to-read format
 It indicates possible causes of variation in a process
 It increases knowledge of the process by helping everyone to learn
more about the factors at work and how they relate
 It identifies areas where data should be collected for further study

8. 2. Check Sheets
 special types of form for data collection
 make easier to collect data, make data collection
effort more accurate and summarize the data which is
very effective for quick analysis
 creates easy to understand data
 clear picture of the facts
 collect data about “how many” or “what type” of
something occurred

9. 2. Check Sheets
1. Defective item check
sheet
2. Defective location
check sheet
3. Defective cause check
sheet
4. Check up confirmation
check sheet

10. 3. Histogram
 A simple tool that allows the user to identify and interpret the
variation found in a set of data points
 Used to summarize and display data in a simple but clear manner
 It do not provide solutions to problems
 They provide a starting point for the improvement process
 If the data is inaccurate then any result obtained from the
histogram is also inaccurate
 Displays large amount to data that are difficult to display in tabular
form
 Bar chart

11. 3. Constructing a histogram
From a set of data, it computes
 sum
 mean (x)
 Max
 Min
 Range (max-min)

12. 3. Constructing a histogram
 Use range to estimate beginning and end
 Calculate the width of each column by dividing the range by the number
of columns
Range
# of Columns
= Width

13. 3. Dominos Pizza Example
 Let’s say the owner wants a distribution of Domino’s Saturday Night Sales
 Data Set from last Saturday(slices)
0 2 1 2 2 4 1 3 1 2 1 2 2 4 3 4 1 4 3 2 2 3 2 1 2 2 1 2 2
1 4 2 2 1 2 1 2 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1
1 2 2 2 3 1 4 2 2 3 2 2 2 1 2 3 2 2 4 2 2 4 4 1 2 2 2 3
2 2 1 2 2 4 2 1 2 4 2 1 7 2 1 2 2 3 1 2 1 1 2 1 2 2 2 1
2 2 1 2 1 2 2 2 4 2 4

14. 3. Dominos Pizza Example
Mean = 2.032258
Max = 7
Min = 0
Range = 7
Question
For 7 columns what would the width be?
Range/Columns=7/7=1 slice

15. 3. Dominos Pizza Example
33
65
8
12
0 0 1
0
10
20
30
40
50
60
70
1 2 3 4 5 6 7
Slices of Pizza
Histogram

16. 3. Constructing a Histogram
How is this helpful to Domino’s?
 2 slices of pizza most common order placed
 Distribution of sales useful for forecasting next Saturday’s
night demand
If you were an Domino’s manager how could you apply
this information?

17. 4. Pareto Chart
 purpose is to prioritize problems because no company has
enough resources to tackle every problems
 graphical tool for ranking causes from most significant to
least significant
 is a series of vertical bars lined up in descending order- from
high to low
 at a glance snapshot of priorities
 80/20 rule: 80% of the problems results from 20% of the
causes
 Use of percentages to show importance

18. 4. Pareto Chart

19. 4. Pareto Chart

20. 4. Pareto Chart

21. 4. Pareto Chart

22. 4. Pareto Chart

23. 5. Flow charts
 A graphical picture of a PROCESS
Process Decision
The process flow

24. 5. Flow charts
Don’t Forget to:
 Define symbols before beginning
 Stay consistent
 Check that process is accurate

25. 5. Flow charts: Domino’s

26. 5. Flow charts
How can we use the flowchart
to analyze improvement ideas
from the Histogram?
 5W1H rule: who, what, when,
where, why, how

27. 6. Scatter diagram
 2 Dimensional X/Y plots
 Used to show relationship between independent(x) and
dependent(y) variables
 How to use it?
a. Collect the data
b. Draw the diagram
c. Plot the paired data
d. Interpret the data

28. 6. Scatter diagram
 Strong positive correlation
 Strong negative correlation
 Weak positive correlation
 Weak negative correlation
 No correlation

29. 6. Scatter diagram for Domino’s Pizza
Minutes Cooking Defective Pies
10 1
45 8
30 5
75 20
60 14
20 4
25 6
In this simple example, you can find the existing relationship
without much difficulty but…

30. 6. Scatter diagram for Domino’s Pizza
0
5
10
15
20
25
0 20 40 60 80
•Easier to see direct
relationship
Time Cooking (minutes)

31. 6. Scatter diagram for Domino’s Pizza
 What does this tell Domino’s management about
their processes?
Improvements?
0
5
10
15
20
25
0 20 40 60 80
Time Cooking (minutes)

32. 7. Run Chart
Time-based (x-axis)
Cyclical
Look for patterns

33. 7. Run Charts
8 9 10 11 12 1 2 3 4 8 9 10 11 12 1 2 3 4 8 9 10 11 12 1 2 3 4
PM- AM PM- AM PM- AM
Thursday
Week 1
Thursday
Week 2
Thursday
Week 3
Slices/hour
Time

34. Control Charts
 To ensure that the process is in control and to monitor process
variation on a continuous basis
 Common Vs Special cause variation
 Deviation from Mean
 Upper and Lower Specification limit
 Range
Variation

35. POKA-YOKE
 is about stopping processes as soon as a defects
occurs, identifying the defect source and preventing it
from happening again.
 Zero defects concepts
 Defined by Shigeo Shingo at Toyota
 Either prevents a mistake from being made or makes
the mistake obvious at glance

36. Principles of Poka-Yoke
 Prediction: recognizing that a defect is about to occur and
providing a warning
eg. Warning message at computer
 Detection: recognizing that defect has occurred and stopping
the process
eg. Antivirus
 PDCA approach