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7 QC Tools
Basic QC Tools
1. Pareto Diagram
2. Cause & Effect Diagram
3. Graph
4. Check Sheet
5. Scatter Diagram
6. Histogram
7. Control Chart
7 Tools
Pareto Diagram
 Pareto charts are a type of bar chart in which the horizontal axis
represents categories of interest, rather than a continuous scale. The
categories are often “defects.”
 This tool is based on the idea that the majority of defects are
caused by few defective item, which classifies the quality problem into
the “vital few” and “trivial many” (80-20 rule).
 A cumulative percentage line helps you judge the
added contribution of each category.
 Pareto charts can help to focus improvement efforts on
areas where the largest gains can be made.
rate
facto
r incorrect
co
nfusing
f
orma
t
Wrongaddr
esss
paym
en
t notcred
ited
wro
ng se
rvice cod
e
5
6
8
10
21
10.0
12.0
16.0
20.0
42.0
100.0
90.0
78.0
62.0
42.0
50
40
30
20
10
0
100
80
60
40
20
0
Defect
Count
Percent
Cum %
Percent
Count
Pareto Chart
80-20 rule
Figure 1 : Example of Pareto diagram
Example
Procedure
1. Decide on the problem to be addressed or items to study and
collect data.
2. Decide also the period for which the data is to be collected.
3. Arrange the data in order of decreasing size.
4. Calculate the cumulative number and percentage.
5. Draw horizontal and vertical axes on graph paper.
6. Draw the bar graph.
7. Draw the vertical axis on the right edge and scale it.
8. Draw the cumulative curve.
Complete the diagram with titles and units of reference.( Figure 1)
Cause and Effect Diagram
 The cause and effect diagram analysis was first developed by
Professor Kaoru Ishikawa of the University of Tokyo in the 1940s’, is
also known as the ‘Fishbone Diagram’ or the ‘Ishikawa Diagram’.
 His first application of this technique was in the Fulsai iron work
1953. Due to its’ final form, some people called it the “Fishbone
Diagram”.
 This tool is a picture of lines and symbols designed to represent the
relationship between the effects as problems and the causes
influencing them.
There is no “correct” way to construct a fishbone diagram, some
types lend themselves well to many different situations.
Figure 2 : Example of Cause and Effect Diagram
tools
Missing maintanance
Solder joints
wire destroyed by mice
Bad transmitter
Wire
Speaker
con
Defective volume
Intermitten
voltage
Irregular
instruction
Poor
attitudes
training
Lack of
Manpower
Machines
Methods
Measurements
Cause and Ef f ect Diagram
Cone
Coil
Backbone
Factor
Middle bone
Small bone Effect
Example
Uses of Ishikawa Diagram
1. To recognize important causes
2. To understand all effects and causes
3. To compare operational procedures
4. To find major solutions
5. To figure out, what to do?
6. To improve the process
1. State the problem as precisely as possible and draw the back bone.
2. Draw the large bone.
3. Get all members involved by participating in the brainstorming
session to obtain as many ideas as possible.
4. The ideas collected are then critically examined to classify them
into the main grouping and subsequent grouping (middle bone, small
bone and fine bone). (Figure 2)
5. Dram the middle bones, small bones and fine bones.
6. Check to see whether any causes have been left.
7. Identify the important causes by members vote, proper analysis of
data and Pareto diagram.
8. Fill in all related information such title, product, process, etc..
Procedure
Graph
 Graph refer to the results of statistical analysis of data (numbers)
which are shown in diagrammatic form to communicate information.
 There are numerous types of graphs as listed are commonly use;
a. Bar graph
b. Line graph
c. Radar graph
f. Pie graph
 Each of above graphs is applicable based on analysis requirement.
Attandance Chart
95%
5%
0
1
2
3
Self Improvement
Leadership
Team Spirit
Communication
Knowledge
Decisive
Before After
Weekly Brown Stain Fallout
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1 2 3 4 5 6 7 8
week
%
Brown Stain Fallout
0.000
0.200
0.400
0.600
0.800
1.000
1.200
1.400
1 2 3 4 5 6 7 8 9 10 11 12
week
%
Bar Graph
Radar Graph
Line Graph
Pie Graph
Example
Check sheets are sheets that are design in advance to collect the
necessary data easily and systematically, which allow the efficient
checking of all items for inspection and verification.
Check Sheet
Procedure
1. Specify the aim of collecting data
2. Decide on the item to be check
3. Decide on the method for stratification
4. Format the check sheet
5. Analyze the data
6. Make clear the causes
7. Implementation of counter measure
8. Grasp the effect
9. Standardization of operations to practice the new and improves
method properly.
Scatter Diagram
 Scatter diagram is a diagram where the relationship between two
characteristic value are plotted and analyze as to whether a
correlation exists between the two set of data.
 Several types of correlation could be found from scatter diagram
are;
1. Positive strong correlation
2. Negative strong correlation
3. Positive moderate correlation
4. Negative moderate correlation
5. Absence of correlation
Figure 3 : Example of Scatter Diagram (Positive strong correlation)
Example
20
15
10
5
19
14
9
4
BTU.Out
BTU.In
Scatter Diagram f or BTU
Procedure
1. Collect and count the number of data
2. Determine the largest (L) and smallest (S) value of data
3. Select number of classes (bars)
Number of Data Number of Classes (K)
30 - 50 5 - 8
51 - 100 6 - 10
101 - 300 7 - 13
4. Find class interval (H)
H = L - S / K
5. Determine starting point of classes
6. Calculate mid value of each class (half of the measurement unit)
7. Count frequency of data
8. Prepare the histogram
Histogram
 A histogram is a vertical bar chart that depicts the distribution of a
set of data.
 It is a useful tool to study the dispersion of data and analyze
certain quality characteristic of the product or service to which the
data in histogram refers.
 A histogram does not reflect the process behavior over time
Example
601
600
599
598
20
10
0
Supp1
Frequency
Histogram f or Camshaf t
Figure 4 : Example of Histogram
Procedure
1. Collect and count the number of data
2. Determine the largest (L) and smallest (S) value of data
3. Select number of classes (bars)
Number of Data Number of Classes (K)
30 - 50 5 - 8
51 - 100 6 - 10
101 - 300 7 - 13
4. Find class interval (H)
H = L - S / K
5. Determine starting point of classes
6. Calculate mid value of each class (half of the measurement unit)
7. Count frequency of data
8. Prepare the histogram

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The 7 QC Tools - English (19 Pages).ppt

  • 2. Basic QC Tools 1. Pareto Diagram 2. Cause & Effect Diagram 3. Graph 4. Check Sheet 5. Scatter Diagram 6. Histogram 7. Control Chart 7 Tools
  • 3. Pareto Diagram  Pareto charts are a type of bar chart in which the horizontal axis represents categories of interest, rather than a continuous scale. The categories are often “defects.”  This tool is based on the idea that the majority of defects are caused by few defective item, which classifies the quality problem into the “vital few” and “trivial many” (80-20 rule).  A cumulative percentage line helps you judge the added contribution of each category.  Pareto charts can help to focus improvement efforts on areas where the largest gains can be made.
  • 4. rate facto r incorrect co nfusing f orma t Wrongaddr esss paym en t notcred ited wro ng se rvice cod e 5 6 8 10 21 10.0 12.0 16.0 20.0 42.0 100.0 90.0 78.0 62.0 42.0 50 40 30 20 10 0 100 80 60 40 20 0 Defect Count Percent Cum % Percent Count Pareto Chart 80-20 rule Figure 1 : Example of Pareto diagram Example
  • 5. Procedure 1. Decide on the problem to be addressed or items to study and collect data. 2. Decide also the period for which the data is to be collected. 3. Arrange the data in order of decreasing size. 4. Calculate the cumulative number and percentage. 5. Draw horizontal and vertical axes on graph paper. 6. Draw the bar graph. 7. Draw the vertical axis on the right edge and scale it. 8. Draw the cumulative curve. Complete the diagram with titles and units of reference.( Figure 1)
  • 6. Cause and Effect Diagram  The cause and effect diagram analysis was first developed by Professor Kaoru Ishikawa of the University of Tokyo in the 1940s’, is also known as the ‘Fishbone Diagram’ or the ‘Ishikawa Diagram’.  His first application of this technique was in the Fulsai iron work 1953. Due to its’ final form, some people called it the “Fishbone Diagram”.  This tool is a picture of lines and symbols designed to represent the relationship between the effects as problems and the causes influencing them. There is no “correct” way to construct a fishbone diagram, some types lend themselves well to many different situations.
  • 7. Figure 2 : Example of Cause and Effect Diagram tools Missing maintanance Solder joints wire destroyed by mice Bad transmitter Wire Speaker con Defective volume Intermitten voltage Irregular instruction Poor attitudes training Lack of Manpower Machines Methods Measurements Cause and Ef f ect Diagram Cone Coil Backbone Factor Middle bone Small bone Effect Example
  • 8. Uses of Ishikawa Diagram 1. To recognize important causes 2. To understand all effects and causes 3. To compare operational procedures 4. To find major solutions 5. To figure out, what to do? 6. To improve the process
  • 9. 1. State the problem as precisely as possible and draw the back bone. 2. Draw the large bone. 3. Get all members involved by participating in the brainstorming session to obtain as many ideas as possible. 4. The ideas collected are then critically examined to classify them into the main grouping and subsequent grouping (middle bone, small bone and fine bone). (Figure 2) 5. Dram the middle bones, small bones and fine bones. 6. Check to see whether any causes have been left. 7. Identify the important causes by members vote, proper analysis of data and Pareto diagram. 8. Fill in all related information such title, product, process, etc.. Procedure
  • 10. Graph  Graph refer to the results of statistical analysis of data (numbers) which are shown in diagrammatic form to communicate information.  There are numerous types of graphs as listed are commonly use; a. Bar graph b. Line graph c. Radar graph f. Pie graph  Each of above graphs is applicable based on analysis requirement.
  • 11. Attandance Chart 95% 5% 0 1 2 3 Self Improvement Leadership Team Spirit Communication Knowledge Decisive Before After Weekly Brown Stain Fallout 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1 2 3 4 5 6 7 8 week % Brown Stain Fallout 0.000 0.200 0.400 0.600 0.800 1.000 1.200 1.400 1 2 3 4 5 6 7 8 9 10 11 12 week % Bar Graph Radar Graph Line Graph Pie Graph Example
  • 12. Check sheets are sheets that are design in advance to collect the necessary data easily and systematically, which allow the efficient checking of all items for inspection and verification. Check Sheet
  • 13. Procedure 1. Specify the aim of collecting data 2. Decide on the item to be check 3. Decide on the method for stratification 4. Format the check sheet 5. Analyze the data 6. Make clear the causes 7. Implementation of counter measure 8. Grasp the effect 9. Standardization of operations to practice the new and improves method properly.
  • 14. Scatter Diagram  Scatter diagram is a diagram where the relationship between two characteristic value are plotted and analyze as to whether a correlation exists between the two set of data.  Several types of correlation could be found from scatter diagram are; 1. Positive strong correlation 2. Negative strong correlation 3. Positive moderate correlation 4. Negative moderate correlation 5. Absence of correlation
  • 15. Figure 3 : Example of Scatter Diagram (Positive strong correlation) Example 20 15 10 5 19 14 9 4 BTU.Out BTU.In Scatter Diagram f or BTU
  • 16. Procedure 1. Collect and count the number of data 2. Determine the largest (L) and smallest (S) value of data 3. Select number of classes (bars) Number of Data Number of Classes (K) 30 - 50 5 - 8 51 - 100 6 - 10 101 - 300 7 - 13 4. Find class interval (H) H = L - S / K 5. Determine starting point of classes 6. Calculate mid value of each class (half of the measurement unit) 7. Count frequency of data 8. Prepare the histogram
  • 17. Histogram  A histogram is a vertical bar chart that depicts the distribution of a set of data.  It is a useful tool to study the dispersion of data and analyze certain quality characteristic of the product or service to which the data in histogram refers.  A histogram does not reflect the process behavior over time
  • 18. Example 601 600 599 598 20 10 0 Supp1 Frequency Histogram f or Camshaf t Figure 4 : Example of Histogram
  • 19. Procedure 1. Collect and count the number of data 2. Determine the largest (L) and smallest (S) value of data 3. Select number of classes (bars) Number of Data Number of Classes (K) 30 - 50 5 - 8 51 - 100 6 - 10 101 - 300 7 - 13 4. Find class interval (H) H = L - S / K 5. Determine starting point of classes 6. Calculate mid value of each class (half of the measurement unit) 7. Count frequency of data 8. Prepare the histogram