7 QC Tool

1. Presented by:
Romel Escano
7 QC Tools

2. TRAINING OBJECTIVES :
 Enumerate and explain the various quantitative tools and problem
solving techniques for decision making ; and
 Apply the appropriate tools and techniques in problem solving for
quality and productivity improvement.

3. Decision Making Approaches Best Applications Primary Dangers
Directive – leader decides alone &
announces the decision
Emergency, Confidential
Information
Discourage involvement
Consultative – leader gets ideas from
members individually or in a meeting,
then decide
Time Deadline Discourages critical
thinking
Democratic – team members vote and
majority rules.
Routine Issues, Very
Large Group,
commitment not needed
Win-lose situation
Consensus – all members participate in
reaching a decision that all will support
Commitment Needed,
consideration required
Takes time, Requires skill
Decision Making
- The process of assembling and evaluating information relating to each of several
alternatives so as to select the one most likely to achieve our objective.
Decision Making Approaches

4. Problem Solving
- Is the process of correcting a situation that is keeping them
from achieving something they want. ( e.g. a goal or objective,
a norm or standard of desired performance.
Data vs. Information
Data ( logbook, time cards ) Information
Raw, unorganized
facts
By itself, it is seldom
useful
Data organized so that it is
useful in decision making
Useful Data

5. Steps in Data Gathering
 Set the objectives for collecting data.
 Determine the data needed based on the set of objectives.
 Determine the method to be used in data gathering and
define the comprehensive data collection points.
 Design data gathering forms to be used.
 Collect data
 Organize, summarize and consolidate data gathered.
 Analyze data using the different tools and techniques.
 Compare resulting information with standards, targets and
customer requirements.
 Decide what action to take based on information gathered.

9. 1. Checksheet
2. Pareto Chart
3. Cause and effect Diagram (Ishikawa diagram)
4. Scattered diagram
5. Charts and graph
6. Histogram
7. Control chart
7 QC TOOLS

10. 1. Check1. Check
sheetsheet is a form (document) used to collect data in real time at the
location where the data is generated. It be quantitative or
qualitative.

11. Use of Check sheet :
• To check the shape of the probability distribution
of a process
• To quantify defects by type
• To quantify defects by location
• To quantify defects by cause (machine, worker)
• To keep track of the completion of steps in a
multistep procedure

12. 2. Pareto2. Pareto
ChartChart is a graphical overview of the process problems, in ranking
order of the most frequent, down to the least frequent, in
descending order from left to right. Thus, the Pareto diagram
illustrates the frequency of fault types.

13. Concept of Pareto Chart

14. 3. Fishbone Diagram (Ishikawa3. Fishbone Diagram (Ishikawa
Diagram)Diagram) also called a cause and effect diagram or Ishikawa diagram,
is a visualization tool for categorizing the potential causes of a
problem in order to identify its root causes.

15. Use of Fishbone Diagram:
• Discover the root cause of the
problem.
• Uncover the bottlenecks on the
process
• Identify where and why process
isn’t working.
• “Brain storm" the potential causes
and resolutions to solve the
variation problem.

16. It is important to prepare your group with the main theme
that "NO IDEA OR THOUGHT IS STUPID!" Every idea
should be presented, anything that pops into anyone's
head should be brought out. Even if the one idea is not
seen as appropriate to the group, it could very well trigger
another thought or idea in someone else. Thus, it is
imperative that you have your group understand, that
there are no silly thoughts, no suggestions that should go
unconsidered and everyone's ideas and input are needed.

17. 4. Scatter Diagram4. Scatter Diagram
 is a tool for analyzing relationships between two variables.
One variable is plotted on the horizontal axis and the other is
plotted on the vertical axis. The pattern of their intersecting
points can graphically show relationship patterns.

18. When to use Scatter Diagram?
• When you have paired numerical data.
• When your dependent variable may have multiple values
for each value of your independent variable.
• When trying to determine whether the two variables are
related, such as…
• When trying to identify potential root causes of problems.
• After brainstorming causes and effects using a fishbone diagram,
to determine objectively whether a particular cause and effect are
related.
• When determining whether two effects that appear to be related
both occur with the same cause.
• When testing for autocorrelation before constructing a control
chart.

19. Ice Cream Sales vs
Temperature
Temperatu
re °C
Ice Cream
Sales
14.2° $215
16.4° $325
11.9° $185
15.2° $332
18.5° $406
22.1° $522
19.4° $412
25.1° $614
23.4° $544
18.1° $421
22.6° $445
17.2° $408
Scatter DiagramData
Scatter Diagram Sample
Graph says that warmer weather leads to more sales, but the
relationship is not perfect.

20. Scatter Diagram (Correlation)

21. 5. Histogram5. Histogram
 A bar chart that shows the distribution of the data.
 A snapshot of data taken from a process.

23. The Histogram
The common person believes that if a part is made in mass production from a
machine, all of the parts will be exactly alike.
The truth is that even with the best of machines and processes, no two parts are
exactly the same.
The product will have a main or "mean" specification limit, with plus/minus
tolerance that states that as long as the part is produced within this range, to that
range, it is an acceptable part. The object is to hit the target specification,
however, that is not always totally possible.
The purpose of a Histogram is to take the data that is collected from a process
and then display it graphically to view how the distribution of the data, centers
itself around the mean, or main specification. From the data, the histogram will
graphically show:
1.The center of the data.
2.The spread of the data.
3.Any data skewness (slant, bias or run at an angle).
4.The presence of outliers (product outside the specification range).
5.The presence of multiple modes (or peaks) within the data.

24. 6. Control Charts6. Control Charts
 also known as Shewhart charts (after Walter A. Shewhart)
or process-behavior charts. Tools used to determine if a
manufacturing or business process is in a state of statistical
control

25. Use of Control Charts
 Help you recognize and understand variability and how to control it.
 Identify special causes of variation and changes in performance.
 Keep you from fixing a process that is varying randomly within
control limits; that is no special causes are present. If you want to
improve it, you have to objectively identify and eliminate the root
causes of the process variation.
 Assist in the diagnosis of process problems.
 Determine if process improvement effects are having the desired
affects.

26. 7. Stratification7. Stratification
 is the process of dividing members of the population into
homogeneous subgroups before sampling. In case of Quality
Control, stratification generally means to divide data into several
groups according to common factors and tendencies ( eg; types
of defects and cause of defects).

27. When to use Stratification?
 Help you recognize and understand variability and how to control it.
 Identify special causes of variation and changes in performance.
 Keep you from fixing a process that is varying randomly within
control limits; that is no special causes are present. If you want to
improve it, you have to objectively identify and eliminate the root
causes of the process variation.
 Assist in the diagnosis of process problems.
 Determine if process improvement effects are having the desired
affects.

28. A common step in analyzing an output is to group your data by a
stratification variable.
Suppose you stratify these same data by facility.
Now, it appears B is doing something better.
Stratification ExampleStratification Example
Plant Average On Time Delivery
A 75 %
B 85 %
C 80 %

29. Stratification and Root CauseStratification and Root Cause
Although Facility B has the best performance, this input variable itself
may not explain the root cause of the differences.
Root cause is more likely related to:
Differences in the methods being used
Differences in how personnel are trained.
Differences in tracking systems used.
Although stratification variables may not identify the root cause,
they often narrow the search.

30. Pie chart
No. of Defects
0
5
10
15
20
25
30
35
40
45
ShortshotBlack
spotFlowm
ark
CrackScratches
Others
No. of Defects
Charts and graphs
No. of Claims
0
1
2
3
4
5
Jan Feb Mar Apr May Jun
No. of Claims
Bar graph Run chart
0 10 20 30 40 50
Short shot
Black spot
Flowmark
Crack
Scratches
Others
After
Before
Run chart