The document discusses various quality improvement tools and techniques. It describes 9 different management tools that can be used for process improvement, including forced field analysis, nominal group technique, affinity diagrams, and prioritization matrices. It also covers 7 reactive improvement tools that are part of statistical process control, such as Pareto diagrams, process flow diagrams, cause-and-effect diagrams, check sheets, and control charts. Examples are provided to illustrate how many of these tools are constructed and used.

1. Continuous
Improvements
By Prof. Raghavendran V

2. Proactive
Improvements
By. Prof. Raghavendran V 2

3. There are some improvements that they
wont use hard data but rely on subjective
information. Application of these tools has
proven useful in process
improvement, cost reduction, policy
making & deployment and New-Product
Development.
Proactive Improvements
By. Prof. Raghavendran V 3

4. The tools are very simple, it is effective and
it can be key to finding the root cause of a
problem in specific terms and then ask
why.
You may have to ask why 2 or more times
to obtain root cause of the problem.
Proactive Improvements
By. Prof. Raghavendran V 4

5.  There are 9 different techniques involved and
also called as “Management tools Technique”.
There are listed as follows:
1. Forced Field Analysis
2. Nominal Group Technique
3. Affinity Diagram
4. Interrelationship Digraph
5. Tree Diagram
6. Matrix Diagram
7. Prioritization Matrices
8. Process Decision Program Chart(PDPC)
9. Activity Network Diagram
Management Tools & Techniques
By. Prof. Raghavendran V 5

6.  This analysis is used to identify the force
& factors that may influence the problem
or goal.
 It helps an organization to better
understand promoting & inhibiting forces
so that the positives can be reinforced &
the negatives can be reduced.
 The procedure is define the
Objective, determine the criteria for
evaluating effectiveness of action
Forced Field Technique
By. Prof. Raghavendran V 6

7. For Illustration:
Objective: Stop Smoking
Promoting Forces to stop Inhibiting forces to cant
smoking stop Smoking
Poor Health Habit
Smelly Clothing Addiction
Cost Taste
Impact on others Advertisement
Setting an Example Stress
The Benefit are the determination of the
positives and negatives, encouraging people
to prioritize the competing forces and identify
root causes.
Forced Field Technique
By. Prof. Raghavendran V 7

8. This provides for issue/idea input from
everyone on the team and for effective
decisions.
For Example: Indian cricket team decides
which problem to work on. All players
write down on the papers the problems
they think is most important.
Ranking is consider to evaluate the
problem. The highest number is consider
as most important problem.
Nominal Group Technique
By. Prof. Raghavendran V 8

9.  This diagram allows the team to creatively
generate large number of issues/ideas
and logically group them for problem
understanding and possible breakthrough
solutions.
 The procedure is to state the issues in a
full sentences, brain storm.
(large group must be divided into small
groups with appropriate headings)
Affinity Diagram
By. Prof. Raghavendran V 9

10. For Illustration for scrambled idea:
Fatigue Pitch
What are issues involved in
losing the world cup for
England
Ambience of the
Big crowd
Grounds
No form
Not Fear of Terrorism
players
enough
experienc
e players
Spin
Tracks No seriousness
in playing
Affinity Diagram
By. Prof. Raghavendran V 10

11. For Illustration for Ordered idea:
What are issues involved in
losing the world cup for
England
About Technical
aspects
Not enough Ambience of the
Fatigue Pitch experience players crowd
No seriousness in
Big Grounds Fear of Terrorism
playing
Spin Tracks No form players About Public Factors
About Players
Affinity Diagram
By. Prof. Raghavendran V 11

12.  The Interrelationship Diagraph clarifies
the inter relationship of many factors of a
complex situation. It allows to team to
classify the cause & effect relationships
among the all the factors.
 The procedure is complicated & as follows
1. The team should agree on the issue or
problem statement.
2. All the ideas or issues must be laid out
Interrelationship Diagraph(ID)
By. Prof. Raghavendran V 12

13. 3. Start with first issue & evaluate with the
other issue using cause-effect relationship.
4. The second iteration is to compare second
issue with other issue and followed by.
5. The entire diagram should be reviewed
where necessary. It is good idea to obtain
information from others people Upstream or
Downstream.
6. The diagram is completed by tallying the
incoming & outgoing arrows and placing
this information below the box.
Interrelationship Diagraph(ID)
By. Prof. Raghavendran V 13

14.  Benefits of Interrelationship Diagraph(ID)
 It allows a team to identify root causes
from subjective data systematically.
 Cause and effect relationships
 Encourage members to think in
multidirectional
 Develops team harmony and
effectiveness.
Interrelationship Diagraph(ID)
By. Prof. Raghavendran V 14

15.  This tool is used to reduced any broad
objective into increasing levels in detail in
order to achieve objective.
 Procedure to choose action oriented
objective statement.
 Secondly, brainstorming, choose the
major headings
 Thirdly, generate the next level analyzing
the major heading.
Tree Diagram
By. Prof. Raghavendran V 15

16.  Here diagram allows individuals or teams
to identify, analyze and rate the
relationship among two or more variable.
 Data are presented in table form and can
be objective or subjective, which can be
given symbols with or without numerical
values.
 There are different formats 2 or variables
L-shaped (2V), T or C or Y-shaped(3V) and
X Shaped (4V).
Matrix Diagram
By. Prof. Raghavendran V 16

17.  For Illustration:
Tool/ Use Creativity Analysis Consensu Action
s
Affinity o o
ID o 
Tree  
Diagram
Prioritizat o
ion Matrix
Matrix   
Diagram
o Always
 Frequently
Occasionally
By. Prof. Raghavendran V 17

18. These tools prioritize
issues, tasks, characteristics, and based
on weighted criteria using combination of
tree and matrix diagram techniques.
 Prioritization matrices are designed to
reduce the teams options rationally before
detailed implementation planning occurs.
Prioritization Matrices
By. Prof. Raghavendran V 18

19.  Construct an L-shaped matrix combing
the options
 Determine implementation criteria
Nominal Group technique.
 Prioritize the criteria using NGT, each
member weights the criteria so that total
weights equal to 1.00
 Rank order the options in terms of
importance by each criterion
 Compute the option importance score
Construction of Prioritization
Matrices
By. Prof. Raghavendran V 19

20.  Programs to achieve particular objectives
do not always go according to plan, and
unexpected developments may have
serious consequences. The PDPC avoids
surprises and identifies possible
countermeasures.
Process Decision Program Chart
By. Prof. Raghavendran V 20

21. Plan successful conferences
Facilities
Registration  Presentations
Audio/Visual
Speakers Late Too Long
Fails
Have
Have Backup Use AV Use Time
Substitute Person Keeper
By. Prof. Raghavendran V 21
PDPC

22.  This tool goes by a number of different
names and deviations, such as program
evaluation and review technique, Critical
Path Method, arrow diagram and activity
on node.
 It allows team to schedule a project
efficiently.
Activity Network Diagram
By. Prof. Raghavendran V 22

23. 1) The team brainstorm/document all the
tasks to complete project.
2) The first task is always started from
extreme left.
3) Any tasks that can be done simultaneously.
4) Repeat step 2 & 3 until all tasks are placed
5) Number each task & draw connecting
arrows. Determine the completion time and
post it in the lower left box. Completion
times recorded in hours/days/weeks
6) Determine the critical path by completing
the four remaining boxes in each task.
These boxes are Earliest start time(ES),
Earliest Finish(EF), Latest Start(LS) and
latest Finish (LF).
By. Prof. Raghavendran V 23

24. Reactive
Improvements
By. Prof. Raghavendran V 24

25.  Reactive Improvements is also known as
Statistical Process Control. This is one of
the best technical tools for improving
product and service quality. There are
seven basic technique and they are:
1. Pareto diagram
Some what Statistical
2. Process flow diagram
3. Cause and effect diagram
4. Check sheets
5. Graphs- Histogram, Line graphs, Pie
charts
6. Scatter diagram
7. Control Charts By. Prof. Raghavendran V 25

26. Alfred Pareto conducted extensive studies
of the distribution of wealth in Europe.
Pareto diagram is a graph of that ranks
data classification in descending order of
their numerical value of their frequency of
occurrence from left to right in
accordance with the variables.
Variables are problems, complaints, causes,
type of non conformities.
Pareto Diagram
By. Prof. Raghavendran V 26

27. Pareto Diagram Concepts:
50
45
40
35
30 Series 1
25 Series 2
20 Series 3
15 Series 4
10
5
0
Category of data
Pareto Diagram
By. Prof. Raghavendran V 27

28.  Determine the method of classifying the
data (Problem, cause, non conformity and
so forth)
 Decide if rupees, frequency or both are to
be used to rank the characteristics.
 Collect data for an appropriate time
interval or use historical data.
 Summarize the data and rank order
categories from largest to smallest.
 Construct the diagram and find the vital
few.
Construction of Pareto diagram
By. Prof. Raghavendran V 28

29. Solve the problem:
In an recent 1st internal assessment
conducted for 7th mechanical
students, the following result declared for
48 students
0-14 marks: 31 Students
15-20 marks: 13 Students
21-25 marks: 04 Students.
Categorize them using Pareto Diagram.
By. Prof. Raghavendran V 29

30. 35
31
30
25
20 0-14
15 13 15-20
65%
21-25
10
5 4
27%
08%
0
Students marks
Pareto Diagram
By. Prof. Raghavendran V 30

31.  It shows different activities of a process
operation, for a product or services as it
moves through the various processing
operations.
 The diagram makes it easy to visualize
the entire system, identify potential
trouble spots and locate control activities.
Process Flow Diagram
By. Prof. Raghavendran V 31

32.  For Illustration: let us consider vehicle
parking operation in a bus terminus.
Customer gets the tkt for
Parking Receive tkt from the customer
Customers parks the car
Stamp the exit time on ticket
Customers comes back to
parking lot to leave
Read difference time
Customers drives the car to and collect the time
exit
Put the tkt in Storage
Bin
Cashier System
Customer Drives the car
Process Flow Diagram
End of the day complete Owner of the parking lot
report By. Prof. Raghavendran V 32
gets the accounting report

33.  A C&E diagram is a picture composed of
lines and symbols designed to represent
meaningful relationship between effect
and causes.
 It was developed by Dr. Kaoru Ishikawa
1943 and it is referred as fishbone
diagram because of it shape.
Cause and Effect Diagram
By. Prof. Raghavendran V 33

34. Causes
People
Materials Work Methods
Quality
Characteristics
Effect
Environment Equipment Measurement
Cause and Effect Diagram
By. Prof. Raghavendran V 34

35.  The main purpose of check sheets is to
ensure that the data is collected carefully
and accurately by operating personnel.
 Data should be collected in such a way
that it can quickly and easily used and
analyzed.
 For Illustration: Check sheet for paint
nonconformities
Check Sheets
By. Prof. Raghavendran V 35

36. Check Sheet
Product: Bicycle 32 Number inspected: 2222
Nonconformity Type Check Total
Blister 21
Light Spray 38
Drips 22
Overspray 11
Runs 47
Others 5
Total 144
Number
113
Non Conforming
Check Sheets
By. Prof. Raghavendran V 36

37.  Arguably the first „Statistical‟ technique.
 It describe the variation in the process.
 The histogram graphically estimates the
process capability.
 For any histogram there will graphical and
analytical techniques for summarization.
Graphical technique is a plot or picture of a
frequency distribution, which is a
summarization of how the data points
occur within each subdivision of observed
values.
Histogram
By. Prof. Raghavendran V 37

38. Analytical technique, summarize data by
computing measure of the central
tendency (Average, Median, Mode)and
measure of the dispersion ( Range and
standard Deviation).
Illustration for Ungrouped data:
Number of daily accounting errors.
0 1 3 0 1 0 1 0
1 5 4 1 2 1 2 0
1 0 2 0 0 2 0 1
2 1 1 1 2 1 1
0 4 1 3 1 1 1
Histogram 1 3 4 0 0 0 0
1 3 0 1 2 2 3
By. Prof. Raghavendran V 38

39.  Tally of number of daily accounting errors
Number Tabulation Frequency
Nonconforming
0 15
1 20
2 8
3 5
4 3
5 1
By. Prof. Raghavendran V 39

40.  Illustration for Grouped data: Cell
Interval
40
35 34
F Boundary
r 30
e 24
q 25 22
Series 1
u 20
e Series 2
15
n Series 3
c 10
y
5 Mid Point
0
Temperature
Histogram
By. Prof. Raghavendran V 40

41.  There are 6 different types of histogram
And they are
1. Symmetrical
2. Skewed right
3. Skewed left
4. Peaked
5. Flat
6. Bimodal
Histogram
By. Prof. Raghavendran V 41

42. This is simplest way to determine, if a
C&E relationship exists between two
variables.
For Illustrations: in a relationship between
automotive speed and mileage.
As speed increases, mileage decreases.
Automotive Speed is plotted on the axis
and is the independent variable.
Gas mileage is plotted on y axis and this is
dependent variable.
Scatter Diagram
By. Prof. Raghavendran V 42

43. Y-Values
45
40
M 35
i 30
l
25
e
a 20 Y-Values
g 15
e 10
/ 5
l 0
Speed –Mi/hour
t
r 0 20 40 60 80 100
Scatter Diagram
By. Prof. Raghavendran V 43

44.  Other examples for relationship are:
 Cutting speed and tool life
 Temperature and Lipstick hardness
 Training and errors
 Breakdowns and equipment age
Scatter Diagram
By. Prof. Raghavendran V 44

45.  A control chart is a graphical
representation of collected information
and common tool used in industries in
controlling the quality of products or
quality characteristics.
 It is an aid for analyzing the quality in
repetitive process.
 It is developed by Dr. W.A Shewhart
Control Charts
By. Prof. Raghavendran V 45

46.  Control charts is classified into types and
they are:
1. Variable (Continuous Data)
2. Discrete Data (Discontinuous Data)
Variable: Data which can take any value
depending on the accuracy of the
measuring instrument is called continuous
data.
For Ex: Weight of Object can be 1.2 or 1.23
or 1.234 Kg Depends on the accuracy of
the instrument.
Control Charts
By. Prof. Raghavendran V 46

47. Discrete: Data which can take only definite
is called discrete data. The values are
whole number.
It will be only whole number. For ex:
Number of wickets took by bowler.
By. Prof. Raghavendran V 47

48.  It is common phenomenon, in nature and
also in the product produced in industry.
There will be lot of variations on so many
factors in a twin children.
 It is impossible to produce identical parts.
Henceforth, tolerance limits came in
picture. Variations are due to 2 causes:
1. Variation due to chance causes
2. Variation due to assignable causes.
Variables
By. Prof. Raghavendran V 48

49. 1. Variation due to chance causes
The variations due to sheer chance. This is
not permanent factor for variation.
For Ex: Voltage Variation, Vibrations on
Machine tool.( It is difficult to avoid the
variation)
2. Variation due to assignable causes
Variations caused by assigned job. These
are easily traceable.
For Ex: Difference among the
M/c‟s, Men, materials
Variables
By. Prof. Raghavendran V 49

50.  Based on data, we have:
1. Control Charts for
Continuous Data or Variable
2. Control Charts for Discrete
Data or Attributes
Variable
By. Prof. Raghavendran V 50

51.  The data collected for control charts for
variable will be measured in two types
and they are:
Mean and Range charts also called
R Charts
 Mean and Standard Deviation also called
Charts.
Mean is most common method of measure of central
tendency.
R and are most common method to measure of dispersion.
Control Charts for Continuous
Data or Variable
By. Prof. Raghavendran V 51

52. Procedure for drawing Charts:
1. Collect good number of samples of
constant sample size „n‟ at random at
different intervals of time.
2. Measure all the quality characteristics of
all which is to be controlled of all the
pieces in the sample and of all the
samples and record the same in tables.
3. Find the mean of the all the samples.
4. Find the mean of the mean .
Mean and Range charts
By. Prof. Raghavendran V 52

53. 5. Find the range of the samples
6. Find the mean of the range of all
samples.
7. Compute the trial control limits or 3
control limits or control for X and R as
follows:
Control limits for X chart:
CLX= X± 3 X = X ± 3A2R
Mean and Range charts
By. Prof. Raghavendran V 53

54. Control for R Chart:
UCLR=D4R
LCLR=D3R
Where A2, D3, D4 are factors obtained
from Table B, factors for controlling
limits.
8. Draw X and R Charts
Mean and Range charts
By. Prof. Raghavendran V 54