UNIT 3

The seven traditional tools of quality – New management tools – Six-

sigma: Concepts, methodology, applications to manufacturing, service
sector including IT – Bench marking – Reason to bench mark, Bench
marking process – FMEA – Stages, Types.

PART - A (2 MARKS)

1. Give the traditional seven quality control tools. Nov 13

i. Pareto Diagram
ii. Process Flow Diagram
iii. Cause and Effect Diagram
iv. Check Sheets
v. Histogram
vi. Control Charts
vii. Scatter Diagrams

2. What is the use of the control chart?

The control chart is used to keep a continuing record of a particular quality
characteristic. It is a picture of process over time.

3. Give the objectives of the attribute charts?

i. Determine the average quality level.
ii. Bring to the attention of management any changes in the average.
iii. Improve the product quality.
iv. Evaluate the quality performance of operating and management
personnel.
v. Determine acceptance criteria of a product before shipment to the
customer.

4. Define Six Sigma Problem Solving Method.

Define - improvement opportunity with an emphasis on increasing
customer satisfaction.
Measure - determine process capability (Cp/ Cpk) & DPMO (defects per
million opportunities).
Analyze - identify the vital few process input variables that affect key
product output variables (“Finding the knobs”).
Improve - Make changes to process settings, redesign processes, etc. to
reduce the number of defects of key output variables.
 Control - Implement process control plans, install real-time process
monitoring tools, and standardize processes to maintain levels.

5. What are the new seven management tools in quality? Apr 08, Nov 11
i. Affinity Diagram
ii. Interrelationship Digraph
iii. Tree Diagram
iv. Matrix Diagram
v. Prioritization Matrices or Matrix Data Analysis
vi. Process Decision Program Chart or Decision Tree
vii. Activity Network diagram or Arrow Diagram

6. Define Benchmarking. Write its benefits of Benchmarking. Apr 14, Nov

11
Definition: Benchmarking is a systematic method by which organizations
can measure themselves against the best industry practices.
Benefits: The essence of benchmarking is the process of borrowing ideas
and adapting them to gain competitive advantage. It is a tool for
continuous improvement.

7. Enumerate the steps to benchmark?

a) Decide what to benchmark
b) Understand current performance
c) Plan
d) Study others
e) Learn from the data
f) Use the findings

8. What are the types of benchmarking?

i. Internal
ii. Competitive
iii. Process

9. What are the four basic steps included in SPC?

The four basic steps included in Statistical Process Control are
a. Measuring the process
b. Eliminating variances in the process to make it consistent.
c. Monitoring the process.
d. Improving the process to its best target value.
10. Mention the seven basic tools involved in statistic quality control.
i. Pareto Diagram
ii. Process Flow Diagram
iii. Cause and Effect Diagram
iv. Check Sheets
v. Histogram
vi. Control Charts
vii. Scatter Diagrams

11. What is Pareto chart?

A Pareto chart is a special form of a bar graph and is used to display the
relative importance of problems or conditions.

12. Give some applications of Pareto chart. Apr 11

The applications of Pareto chart are,
a. Focusing on critical issues by ranking them in terms of importance
and frequency (Example: which course causes the most difficulty for
students? or which problem with product X is most significant to our
customers?)
b. Prioritizing problems or causes to efficiently initiate problem solving
(Example: which discipline problems should be tackled first? or what is the
most frequent complaint by parents, regarding the school?)

13. What is the use of SPC?

SPC is used to monitor the consistency of processes used to manufacture a
product as designed.

14. Define check sheet. Mention its uses.

The check sheet is a data gathering and interpretation tool.
A check sheet is used for,
a. Distinguishing between fact and opinion (Example: How does the
community perceive the effectiveness of the school in preparing students
for the world of work?)
b. Gathering data about how often a problem is occurring? (Example: How
often are students missing classes?)
c. Gathering data about the type of problem occurring. (Example: What is
the most common type of word processing error created by the students-
grammar, punctuation, transposing letter etc.?)

15. What are the uses of cause and effect diagram?

A cause and effect diagram is used for,
 a. Identifying potential causes of a problem or issue in an orderly way.
(Example: why has membership in the band decreased? Why isn’t the
phone being answered on time? Why is the production process suddenly
producing so many defects?)
b. Summarizing major causes under four categories. (Example: People,
machines, methods and materials or policies, procedures, people and
plant.)

16. What is scatter diagram?

A scatter diagram is used to interpret data by graphically displaying the
relationship between two variables.

17. List some applications of scatter diagram.

The applications of scatter diagram
a. Validating ‘hunches’ about a cause-and-effect relationship between
types of variables
(Examples: I wonder if students who spend more time watching TV having
higher or lower average GPA’s. Is there a relationship between the
production speed of an operator and the number of defective parts made?
Is there relationship between typing speed in WPM and errors made?)
b. Displaying the direction of the relationship (positive negative, etc).
(Examples: will test scores increase or decrease if the students spend more
time in study hall? Will increasing assembly line speed, increase or
decrease the number of defective parts made? Do faster typists make more
or fewer typing errors?)

18. Define histogram.

A histogram is used to display in bar graph format measurement data
distributed by categories.

19. What are the problems that can be interpreted by the histogram?
The problems that can be interpreted by the histogram are,
a. Skew problems
b. Clustering problems.

20. Define control chart.

Control chart is defined as a display of data in the order that they occur
with statistically determined upper and lower limits of expected
common cause variations. It is used to indicate special causes of process
variations to monitor a process for maintenance and to determine if process
changes have has the desired effect.
21. What is line graph?
A line graph is a way to summaries how two pieces of information are
related and how they vary depending on one another. The numbers along a
side of the line graph are called the scale.

22. What is an arrow diagram?

An arrow diagram is another term for a PERT or CPM chart. It is graphic
descriptions of the sequential steps that must be completed before a project
can complete.

23. Give some applications of arrow diagram.

The applications of arrow diagram are,
a. Understanding and managing complex project or task.
b. Understanding and managing a project that is of major importance to
the organization, and the consequences of late completion are sever.
c. Understanding and managing a project in which multiple activities must
take place and be managed simultaneously.
d. Explaining the project status to others.

24. How is an arrow diagram constructed?

Steps in constructing an arrow diagram are,
a. Select a team that is knowledgeable about the project, its task and
subtasks.
b. Record all of the tasks and subtasks necessary to the completion of the
project.
c. Sequence the tasks.
d. Assign time duration to each task.
e. Calculate the shortest possible implementation time schedule using the
critical path method.
f. Calculate the earliest starting and finishing times for each task.
g. Locate tasks with slack (extra) time and calculate total slack.
h. Update the schedule as the project is being completed.

25. What is nominal group technique?

The nominal group technique is a structured process, which identifies and
ranks the major problems or issues that need addressing.

26. State the principle of Pareto Analysis. May 12, May 13

Pareto Principle: The Pareto concept was developed by the describing the
frequency distribution of any given characteristic of a population. Also
 called the 20-80 rule, it means only 20% of problems (defects) account for
80% of the effects.

27. Define process capability. Nov 09, Apr 11

It may be defined as the minimum spread of a specific measurement
variation which will include 99.7% of the measurements from the given
process.
Since 99.7% area in the normal curve is between -3σ and + 3σ, therefore
process capability is equal to 6σ.

28. Define process capability ratio. Nov 09

It measures how well the product requirements match with the process
capabilities. The higher the value of Cp, the better the match between
product and process.

Process Capability Ratio (Cp) = Design Width / Process Width

= (USL –LSL)/ (UCL –LCL) (or)

= (USL –LSL)/ 6σ

29. Write the different concepts of six sigma. Apr 14

1) DMAIC model (for improving existing processes) and

2) DMADV model (for design of new products to achieve six sigma quality).

Sigma Without shift With shift (1.5σ)

(σ) % Process % Process Grade
levels conformance DPMO Capability conformance DPMO Capability
(CP) (CPK)
1 68.27 317,32 0.33 30.23 697,70 -0.167 Non –
0 0 Competitive
2 95.45 45,500 0.67 69.13 308,70 0.167
0
3 99.73 2,700 1.00 93.32 66,810 0.5
4 99.9937 63 1.33 99.379 6,210 0.834 Industry
5 99.999943 0.57 1.67 99.9767 233 1.167 Average
6 99.9999998 0.002 2.00 99.99966 3.4 1.5 World
Class
7 99.999998 0.020

30. Distinguish between discrete and variable data with suitable examples.
Apr 10
Discrete Data Variable Data
The data obtained by counting are The data obtained by actual
Discrete or Attribute. measurement are Continuous or
 Variable.
All qualitative characteristics are Those characteristics that can be
taken. quantified and measurable.
Example: No. of defective pieces Example: Dimension of a part
found in a sample. measure.

31. What is the need for six sigma state? Apr 10

The six sigma is nothing but an extension of the control limits from ± 3σ
limit to ± 6σ. The chance of a part going outside the control limits from the
± 3σ is 27 parts in 10000 and that of ± 6σ is 3.4 parts per million. This
means that the probability of the parts produced going outside the control
limit is much higher in the ± 3σ limit system than in the ± 6σ limit system.

32. What does DMAIC Convey in 6 sigma? May 12

D – Define, M – Measure, A – Analyze, I – Improve, C – Control

33. What are the problems involved in benchmarking a direct competitor?

May 12
 Stagnation of ideas, strategies, best industry practices.
 It should never be the primary strategy for improvement.
 It should not be a substitute for innovation.

34. How is benchmarking used in the industry? Apr 11, Nov 12, Nov 13
It refers to comparisons with a group larger than the direct competitor.
It is used to compare the entire organization within an industry.

35. What are the stages of six sigma? May 13

1) DMAIC model (for improving existing processes) and

D – Define, M- Measure, A – Analyze, I – Improve, C - Control

2) DMADV model (for design of new products to achieve six sigma quality).

D – Define, M- Measure, A – Analyze, D – Design, V - Verify

36. Describe the evolution of six sigma in Motorola Company. Nov 12

Motorola is known for its cool cell phones, but the company's more lasting
contribution to the world is the quality-improvement process called Six
Sigma. In 1986 an engineer named Bill Smith, sold then-Chief Executive
Robert Galvin on a plan to strive for error-free products 99.9997% of the
time. It is the origin of ‘Six Sigma’.

Motorola saved $17 Billion from 1986 to 2004, reflecting hundreds of

individual successes in all Motorola business areas including:
  Sales and Marketing
 Product design
 Manufacturing
 Customer service
 Transactional processes
 Supply chain management

37. Define: Attribute data, Variable data. Nov 13 – Refer Question No. 30

38. What are the types of FMEA? Nov 13

Types of FMEA:
Design FMEA – analysis of potential failures of product or service due to
component or subsystem unreliability.
Process FMEA – Failure analysis of a manufacturing process.

39. What is meant by FEMA? Nov 13

Definition of FMEA: it is also known as Risk Analysis, is a preventive
measure to systematically display the causes, effects and possible
actions regarding observed failures.
FMEA thus uses occurrence, detection, and severity criteria to develop risk
prioritization numbers for prioritizing corrective action.

40. What are the factors that distinguish 6 sigma concepts from
traditional quality management concepts? Nov 13
 Improvement of the process performance
 Decrease variation
 Maintains consistent quality of the process output.
 Defect reduction
 Improvements in profit, product quality and customer satisfaction.

PART - B (16 MARKS)

1. Explain the seven statistical tools or seven traditional tools of quality

with an example. May 13 (16 marks)

Introduction: The Japanese Quality Guru Ishikawa proposed seven basic

tools (Q – 7 Tools) based on statistical techniques to facilitate successful
accomplishment of quality improvement objectives.

Q – 7 Tools:
i. Flow Chart
ii. Check Sheet
iii. Histogram
iv. Pareto Diagram
v. Cause-and-Effect Diagram
vi. Scatter Diagram
vii. Control Chart

I – Pareto Diagram

Introduction: Italian economist Vilfredo Pareto shows on a bar graph which

factors are more significant. This method helps to find the vital few
contributing maximum impact from the trivial many.

Definition: It is a diagnostic tool commonly used for separating the vital

few causes that account for a dominant share of quality loss.

Purpose: The purpose of the Pareto chart is to prioritize problems. No

company has enough resources to tackle every problem, so they must
prioritize.

Pareto Principle: The Pareto concept was developed by the describing the
frequency distribution of any given characteristic of a population. Also called
the 20-80 rule, it means only 20% of problems (defects) account for 80%
of the effects.

Conclusion: The most important thing in improving quality is to start

somewhere, doing something. As you begin using the Pareto chart to decide
where your problems are, you will discover many things about your processes
and will come because you will know where to improve.

Illustration: Table shows data collected from a given production process. The
table shows that there are five possible error types and totally 2165 number of
components is inspected of which 416 components are defective. Type I error
accounts for 47.7%; Type III error accounts for 24.7%; Type II error accounts
for 6.01%; Type IV error accounts for 4.327% and Type V error accounts for
17.31%.

Total no. of components inspected:

Total no. of defective:
Error Type Number of Error Failure Relative Failure
Percentage Percentage
I
II
III
IV
V
Total

Diagram

II - Flowchart

Definition: It is a diagrammatic view of the various steps in sequential

order that form an overall process in an organization.

Purpose: Flow Charts provide a visual illustration of the sequence of

operations required to complete a task.

A picture of the steps the process undergoes to complete its task. Every process
will require input(s) to complete its task, and will provide output(s) when the
task is completed. Flow charts can be drawn in many styles. Flow charts can
be used to describe a single process, parts of a process, or a set of processes.
There is no right or wrong way to draw a flow chart. The true test of a flow
chart is how well those who create and use it can understand it.
Flow Chart Diagram: Input ---------------------Process----------------Output

Sl.no Symbol & Name Meaning

1 Terminator For indicating the start or end of the
flow process chart.

2 Action (Rectangle) For indicating a process or activity or

task or operation.

3 Decision (Diamond) For indicating a decision.

4 Arrows For indicating the direction of flow of

the process.

5 Link For indicating a link to another page

or another flow chart.

III - Cause-and-Effect Diagrams/Fishbone Technique - 1943 by Mr. Kaoru

Ishikawa at the University of Tokyo

Definition: It is a graphical-tabular chart to list and analyze the potential

causes of a given problem.

Purpose: One important part of process improvement is continuously striving

to obtain more information about the process and its output. Cause-and-
effect diagrams allow us to do not just that, but also can lead us to the root
cause, or causes, of problems.
Constructing the Cause-and-Effect Diagram:
Step 1: Select the team members and a leader. Team members should be
knowledgeable about the quality. Team members focus on the problem under
investigation.

Step 2: Write the problem statement on the right hand side of the page, and
draw a box around it with an arrow running to it. This quality concern is now
the effect.

Step 3: Brain-storming. The team members generate ideas as to what is

causing the effect.

Step 4: This step could be combined with step 3. Identify, for each main cause,
its related sub-causes that might affect our quality concern or problem (our
Effect). Always check to see if all the factors contributing to the problem have
been identified. Start by asking why the problem exists.

Step 5: Focus on one or two causes for which an improvement action(s) can be
developed using other quality tools such as Pareto charts, check sheets, and
other gathering and analysis tools.

Conclusion: Improvement requires knowledge. The more information we have

about our processes the better we are at improving them. Cause-and-effect
diagrams are one quality tool that is simple yet very powerful in helping us
better understand our processes.
IV - Check Sheet (Data Collection Sheet)

Definition: It is also known as tally sheet, is a form for systematic data

gathering and registering to get a clear view of the facts.

Purpose: Check sheets allow the user to collect data from a process in an easy,
systematic and organized manner.

Data Collection: Before we can talk about check sheets we need to

understand what we mean by data collection. This collected data needs to be
accurate and relevant to the quality problem. The first is to establish a purpose
for collecting this data. Second, we need to define the type of data that is going
to be collected. Measurable data such as length, size, weight, time and
countable data such as the number of defects. The third step is to determine
who is going to collect that data and when it should be collected.

For example, the check sheet of customer complaints by category.

Sl. Problems Frequency

No.
1 Delivery
2 Packaging
3 Quality or
Performance
4 Personnel
5 Time
Management
6 Price

V- Histograms
Definition: It is a graphical display of the frequency distribution of the
numerical data. The data are displayed as a series of rectangle of equal width
and varying heights.

Purpose: To determine the spread or variation of a set of data points in a

graphical form. It is always a desire to produce things that are equal to their
design values.
Histograms: A histogram is a tool for summarizing, analyzing, and displaying
data. It provides the user with a graphical representation of the amount of
variation found in a set of data.
Constructing a Histogram: The following are the steps followed in the
construction of a histogram:
 Data collection: To ensure good results, a minimum of 50 data points, or
samples, need to be collected.
 Calculate the range of the sample data: The range is the difference
between the largest and smallest data points.
Range = Largest point - smallest point.
 Calculate the size of the class interval: The class interval is the width of
each class on the X axis. It is calculated by the following formula:
Class interval = Range / Number of classes.
Calculate the number of data points (frequency) that are in each class.
 A tally sheet is usually used to find the frequency of data points in each
interval.
For example, Company X manufacturers small resistors with a resistance
value of 100 ohms. The 50 sample’s resistance values are listed in Table
below.

87 84 100 81 83 91 76 76 90 85
90 108 79 94 110 89 74 100 85 82
86 89 90 86 90 100 99 74 91 88
101 80 92 85 100 81 85 79 84 85
83 85 90 100 91 107 85 77 100 99

Range = Highest Value – Lowest Value = 110 – 74 = 36

Class Interval = Range / No. of Classes = 36 / 6 = 6

Class Boundaries Tally Total

1
2
3
4
5
6
Diagram:

Conclusion: Histogram is simple tools that allow the user to identify and
interpret the variation found in a set of data points. It is important to
remember that histograms do not give solutions to problems.

VI - Scatter Diagrams

Definition: it is a simple graphical device to depict the relationship between

two variables. It is the graphical component of regression analysis.

Purpose: To identify correlations that might exist between a quality

characteristic and a factor that might be driving it.

Scatter Diagrams: A scatter diagram is a nonmathematical or graphical

approach for identifying relationships between a performance measure and
factors that might be driving it. This graphical approach is quick, easy to
communicate to others, and generally easy to interpret.

Interpreting the Results: Once all the data points have been plotted onto the
scatter diagram, you are ready to determine whether there exists a relation
between the two selected items or not. When a strong relationship is present,
the change in one item will automatically cause a change in the other. If no
relationship can be detected, the change in one item will not affect the other
item.
There are three basic types of relationships that can be detected to on a scatter
diagram: 1. Positive relationship 2. Negative relationship 3. No relationship

Conclusion: Scatter diagrams allow the user to graphically identify

correlations that could exist between a quality characteristic and a factor that
might be driving it. It is a quality tool that is simple, easy to communicate to
others, and generally easy to interpret.

VII - Control Chart

Definition: It is a graph that displays data taken over time and the variations
of this data. It was developed in the mid 1920's by Walter Shewhart of Bell
labs.

Purpose: Process is in control and to monitor process variation on a

continuous basis. Identifying the tolerance level in the variations. A control
chart is one of the SPC tools that enable us to monitor and control process
variation. To check whether the process is being controlled statistically.

Types of Control Charts:

Control Charts for Variables: For measurable data such as time, length,
temperature, weight, pressure, etc.

Control Charts for Characteristics: For countable data such as number of

defects, typing errors in a report, etc.
A control chart has basically three lines: the upper control limit UCL, the
center line CL and the lower control limit LCL. A minimum of 25 points is
required for a control chart to be accurate.

2. Discuss in detail about the concept of Six-Sigma. Apr 10, Nov 11, May
12, Apr 11, Nov 13

Definition: A vision of quality which equates with only 3.4 defects per
million opportunities (DPMO) for each product or service transaction and
strives for perfection.

It is a systematic method for process and product improvement and for

measuring performance variations. It is also a metric for evaluating
performance quality and a standard of excellence (3.4 DPMO).

Objective: To achieve zero defects or process. It allows 3.4 defects per million
opportunities. (99.999666 percent accuracy)

General Information:

 Motorola embarked on six sigma in the 1987, in its manufacturing division.

 GE adopted six sigma in 1995 for its products (ppm).
 Kodak was also one of the early users.
 Today it is adopted worldwide to improve process performance and is
increasingly popular as a way of organizing an entire organization to become
more quality-oriented and customer-focused.
 Six sigma has been applied not only in manufacturing, but also in product
development, customer service, accounting, and many other business
functions.

Need for Six Sigma:

The six sigma is nothing but an extension of the control limits from ± 3σ limit
to ± 6σ. The chance of a part going outside the control limits from the ± 3σ is
27 parts in 10000 and that of ± 6σ is 3.4 parts per million. This means that
the probability of the parts produced going outside the control limit is much
higher in the ± 3σ limit system than in the ± 6σ limit system.
 Six sigma levels before and after
shift in average

Sigma Without shift With shift (1.5σ)

(σ) % Process % Process Grade
levels conformance DPMO Capability conformance DPMO Capability
(CP) (CPK)
1 68.27 317,32 0.33 30.23 697,70 -0.167 Non –
0 0 Competitive
2 95.45 45,500 0.67 69.13 308,70 0.167
0
3 99.73 2,700 1.00 93.32 66,810 0.5
4 99.9937 63 1.33 99.379 6,210 0.834 Industry
5 99.999943 0.57 1.67 99.9767 233 1.167 Average
6 99.9999998 0.002 2.00 99.99966 3.4 1.5 World
Class
7 99.999998 0.020

Process Capability Ratio: It measures how well the product requirements

match with the process capabilities. The higher the value of C p, the better the
match between product and process.

Process Capability Ratio (Cp) = Design Width / Process Width

= (USL –LSL)/ (UCL –LCL)

Note that a quality level of 3.4 defects per million can be achieved in several
ways, for instance:

The difference between a 4- and 6-sigma quality levels can be surprising. If

your cellular phone system operated at a 4-sigma level, you would be without
service for more than 4 hours each month, whereas at 6-sigma, it would only
be about 9 seconds a month; a 4-sigma process would result in one
nonconforming package for every 3 truckloads while a 6-sigma process
would have only one nonconforming package in more than 5,000
truckloads.

A change from 3 to 4 sigma represents a 10-fold improvement; from 4 to 5

sigma, a 30-fold improvement; and from 5 to 6 sigma, a 70-fold
improvement – difficult challenges for any organization.
SIX SIGMA IMPLEMENTATION MODELS There are two basic models for six
sigma implementation:

1) DMAIC model (for improving existing processes) and

2) DMADV model (for design of new products to achieve six sigma quality).

(1) DMAIC model: It is a 5-step process improvement model. The steps are:
Define, Measure, Analyze, Improve, and Control.

i) Define: Define the six sigma project to be taken up.

 Select the team.

 Identify the customers (internal and external).
 Identify the critical to quality (CTQ) issues, i.e. key performance
measures. Document the existing process.
 Describe the current level of performance.
 Benchmark best performance standards.
 Calculate the cost/revenue implications of the project.
 Decide what needs to be done, by whom, and when.

ii) Measure:

 Identify appropriate measures for assessing performance.

 Define target performance based on customer requirements
(through benchmarking, if necessary).
 Measure current performance and identify the gaps.

iii) Analyze:

 Discover the causes for the gaps/shortfalls/defects.

 Identify key variables which cause the defects (through a cause-
and-effect diagram, if necessary).
 Group the influencing factors into the following three
categories:

Constants (C): these factors cannot be changed.

Noise factors (N): while efforts should be made to reduce noise, these can’t be
eliminated
Experimental factors (X): these factors can be modified to improve the
results.

In this way, identify the parameters to be experimented with in order to

improve the process.

iv) Improve:

 Fix maximum permissible ranges of the key variables.

 Devise a system to measure deviations of the variables.
 Modify the process to ensure that variations occur within the
permissible range.
 Implement the solution on a pilot basis.
 Monitor and measure performance.
 Standardize the improved method if performance is successful.

v) Control: Put in place systems and procedures to ensure that key variables
remain within the maximum permissible ranges continuously. These might
include establishing new standards and procedures, training the workforce,
and instituting controls to make sure that improvements do not die over time.

(2) DMADV model: DMADV stands for Define, Measure, Analyze, Design, and
Verify. It is employed for design of new products to achieve 6-sigma quality.

i) Define: This phase is similar to the DMAIC model. The only difference is that
‘document the existing process’ and ‘describe the current level of
performance’ do not arise.

ii) Measure: Identify customer needs and convert them into technical
requirements through Quality Function Deployment (QFD) technique. Define
measures for each of the technical requirements and define performance
standards for the process.

iii) Analyze: Generate various design options for the concept. Evaluate them
and select the right option.

iv) Design: Detailed design stage involving finer details and identifying all the
required steps in the process. This is followed by system integration. This step
may involve the fabrication of prototypes or establishing a pilot plant.

v) Verify: Verify and validate the functionality of the product or process.

Document the findings and transfer to regular production.
Six Sigma Implementation:

In large organizations, six sigma is implemented in a seamless manner at 3

levels: process level, operations level, and business level. The time taken for
implementation normally is 6 to 8 weeks at the process level, 12 to 18 months
at the operations level, and a few years at the business level. Many projects
may be going on simultaneously at the different levels.

Roles of Personnel Involved in Six Sigma (based on Karate terms):

1. Green Belt: Process owners. They should be familiar with basic statistical
tools.

2. Black Belt: Junior level with 5 years or more experience. Thorough with
basic and advanced statistical tools. One Black Belt per 100 employees. They
work on full-time basis, and are responsible for specific six sigma projects.
They undergo four, one-week training programs.

3. Master Black Belt: Senior level persons. One Master Black Belt for
every 30 Black Belts. They train Black Belts and Green Belts, and work full
time on six sigma projects.
4. Champion: A senior management person who identifies improvement
projects to be taken up. There is one Champion per business group/site.

Case Studies:

Inventor of Six Sigma:

Motorola is known for its cool cell phones, but the company's more lasting
contribution to the world is the quality-improvement process called Six Sigma.
In 1986 an engineer named Bill Smith, sold then-Chief Executive Robert
Galvin on a plan to strive for error-free products 99.9997% of the time. It is
the origin of ‘Six Sigma’.

Motorola saved $17 Billion from 1986 to 2004, reflecting hundreds of

individual successes in all Motorola business areas including:
– Sales and Marketing
– Product design
– Manufacturing
– Customer service
– Transactional processes
– Supply chain management

General Electric:
– Saved $750 million by the end of 1998
– Cut invoice defects and disputes by 98 percent, speeding payment,
and creating better productivity
– Streamlined contract review process, leading to faster completion
of deals and annual savings of $1 million
Honeywell:
– Initiated Six Sigma efforts in 1992 and saved more than $600
million a year by 1999.
– Reduced time from design to certification of new projects like
aircraft engines from 42 to 33 months.
– Increased market value by a compounded 27% per year through
fiscal year 1998.
5. What are the reasons for Benchmarking? Explain six important steps in
the process of Benchmarking with its pros and cons. Nov 11, May 12, May
13, Nov 12, Nov 13

Definition: Benchmarking is a systematic method by which organizations can

measure themselves against the best industry practices.

APQC has defined the benchmarking as the process of identifying,

understanding and adapting outstanding practices and processes from
organizations anywhere in the world to an organization to improve its
performance.

It helps them learn how the “best in class” do things, understand how these
best practices differ from their own, and implement change to close the gap.

Essence of Benchmarking: To borrow ideas and adapting them to gain

competitive advantage. It is a tool for continuous improvement.

Used by Different Companies: It is used extensively by both manufacturing

and service organizations, including Xerox, AT&T, Motorola, Ford, Toyota and
many others. It is a common element in many quality standards.

Proposed: Robert C. Camp (1989)

Concept: Benchmarking considers the experience of others and uses it. It

makes sense to learn from others what they do right and imitate it to avoid
‘reinventing the wheel’.

What is our What are others’

Performance level? Performance levels?
How do we do it? How did they get there?

How do we do it?
Creative
Adaptation

Breakthrough performance
Key Elements: Benchmarking involves two key elements.

First, measuring performance requires some units of measure. These are called
‘metrics’. The numbers achieved by the best-in-class benchmark are the
target.

Second, benchmarking requires managers to understand why their

performance differs from the best-in-class. An understanding of the
differences allows managers to organize their improvement efforts to meet the
goal.

Weakness: Best-in-class performance is a moving target.

Reasons to Benchmark:

i] It reduces the chance of being caught unawares by competition.

ii] It allows goals to be set objectively, based on external information.

iii] It saves time and cost since it involves imitation and adaptation rather than
pure invention.

iv] It provides a readymade model of an improved process, which reduces some

of the planning, testing, and prototyping effort.

v) It aims at searching for industry best practices.

vi) It aims at identifying a technological break-through.

vii) It aims at motivating and stimulating company employees towards the goal
of Continuous Quality Improvement.

Benchmarking Process: It consists of the following six steps:

[1] Decide what to benchmark.

[2] Understand current performance.

[3] Plan.

[4] Study others.

[5] Learn from the data.

[6] Use the findings.

[1] Decide what to benchmark:

Benchmarking can be applied to virtually any business or production process.

In general, it is best to begin by thinking about the mission and the critical
success factors of the organization. Some other questions that can be raised to
decide high impact areas to benchmark are:

Which processes are causing the most trouble?

Which processes are not performing up to expectations?

Which processes contribute most to customer satisfaction?

What are the competitive pressures impacting the organization the most?

What processes or functions have the most potential for differentiating our
organization from the competition?

[2] Understand current performance:

It is first necessary to thoroughly understand and document the current

process. Those working in the process know the most about it. Hence the
benchmarking team should be comprised of those who own or work in the
process. Examples of key metrics for measurement are: unit costs, hourly
rates, quality measures, etc. Techniques such as flow diagrams and cause-and-
effect diagrams aid understanding.

[3] Plan:

A benchmarking team is chosen. The team should decide what type of

benchmarking to perform, what type of data is to be collected, the method of
data collection, and the candidate organizations to be benchmarked, and the
time table for the various tasks required to be performed.

There are three main types of benchmarking: internal, competitive, and

process.

Internal: In most large firms, similar activities are performed in different

operating divisions. Data are easy to obtain for internal comparisons.

Competitive: Product competitors are an obvious choice to benchmark.

However, some organizations would never knowingly share proprietary
information. But there are several ways to obtain such data – information in
public domain, and through third parties. Buying a competitor’s product to
take apart and test is another common practice.
Process: Many processes are common across industry boundaries, and
innovations from other types of organizations can be applied across industries.
For example, every industry has payroll and accounts functions. All kinds of
organizations design new products and have logistics functions. Motorola,
Domino’s Pizza and Federal Express for the best ways to speed up delivery
systems.

Thus best practices can be found internally, in a competitor, in the industry, in

another indigenous organization, or in a global organization.

[4] Study others:

Benchmarking studies look for two types of information: a description of how

best-in-class processes are practiced and the measurable results of these
practices. Primary data, secondary data and site visits are useful sources of
information for carrying out the studies.

[5] Learn from the data:

Learning from the data collected in a benchmarking study involves answering a

series of questions:

Is there a gap between the organization’s performance and that of the best-in-
class organizations?

What is the gap?

How much is it?

Why is there a gap?

What does the best-in-class do differently that is better?

If the best-in-class practices were adopted, what would be the resulting

improvement?

Summary measures and ratios, such as activity costs, return on assets, defect
rates, customer satisfaction levels, etc. can be calculated and compared.

[6] Use the findings:

To effect change, the findings must be communicated to all concerned. The

findings must translate to objectives, goals and action plans.
Benchmarking is a continuous improvement tool. In order to avoid
complacency, it must be used continuously to pursue emerging new ideas.

Diagram:

Planning Analysis Integration Action

Maturity

6. Explain the different steps involved in FMEA with an examples. Apr 14,
May 12, May 13

Failure Mode and Effect Analysis (FMEA)

Definition of FMEA: it is also known as Risk Analysis, is a preventive

measure to systematically display the causes, effects and possible actions
regarding observed failures.
FMEA thus uses occurrence, detection, and severity criteria to develop risk
prioritization numbers for prioritizing corrective action.

Types of FMEA:
Design FMEA – analysis of potential failures of product or service due to
component or subsystem unreliability.
Process FMEA – Failure analysis of a manufacturing process.

Stages of FMEA:
There are four stages of FMEA. These are:
Stage 1 – Specifying Possibilities. i) Functions, ii) Possible failure modes, iii)
Root causes, iv) Effects, v) Detection/Prevention.
Stage 2 – Quantifying Risk. i) Probability of cause, ii) Severity of effect, iii)
Effectiveness of control to prevent cause, iv) Risk Priority Number
Stage 3 – Correcting High Risk Causes. i) Prioritizing work, ii) Detailing action,
iii) Assigning action responsibility, iv) Check points on completion
Stage 4 – Re-evaluation of Risk. i) Recalculation of Risk Priority Number
FMEA Procedure:
The process for conducting an FMEA is straightforward. The basic steps are
outlined below.

1. Describe the product/process and its function

2. Create a Block Diagram of the product or process

3. Complete the header on the FMEA Form worksheet
Product/System, Subsys./Assy., Component, Design Lead,
Prepared By, Date, Revision (letter or number), and Revision Date. Modify
these headings as needed.

4. Listing items or functions

5. Identify Potential Failure Modes

A failure mode is defined as the manner in which a component,
subsystem, system, process, etc. could potentially fail to meet the design
intent.
Examples of potential failure modes include:
 Corrosion
 Hydrogen embrittlement
 Electrical Short or Open
 Torque Fatigue
 Deformation
 Cracking

6. Describe the effects of those Failure Modes:

A failure effect is defined as the result of a failure mode on the
function of the product/process as perceived by the customer.
Examples of failure effects include:
 Injury to the user
 Inoperability of the product or process
 Improper appearance of the product or process
 Odors
 Degraded performance
 Noise

7. Establish a numerical ranking for the severity of the effect.

A common industry standard scale uses 1 to represent no effect
and 10 to indicate very severe with failure affecting system operation and
safety without warning.
Severity (S): It is the assessment of the seriousness of the failure effect.

8. Identify the potential causes for each failure mode.

A failure cause is defined as a design weakness that may result
in a failure. The potential causes for each failure mode should be identified
 and documented. The causes should be listed in technical terms and not in
terms of symptoms.
Examples of potential causes include:
 Improper torque applied
 Improper operating conditions
 Contamination
 Erroneous algorithms
 Improper alignment
 Excessive loading
 Excessive voltage

9. Enter the Probability Factor

A numerical weight should be assigned to each cause that
indicates how likely that cause is (probability of the cause occuring). A
common industry standard scale uses 1 to represent not likely and 10 to
indicate inevitable (predictable).
Occurrence (O): it is the chance that one of the specific causes with occurs.

10. Identify Current Controls (design or process)

11. Determine the likelihood of Detection.

Detection (D) is an assessment of the likelihood that the Current Controls
(design and process) will detect the Cause of the Failure Mode or the Failure
Mode itself. The likelihood of detection is based on a 1to 10 scale, with 1
being the certain of detection and 10 being the absolute uncertainty of
detection.

12. Review Risk Priority Numbers (RPN).

The Risk Priority Number is a mathematical product of the numerical
Severity, Probability, and Detection ratings.
         RPN = (Severity) x (Probability) x (Detection)
The RPN is used to prioritize items that require additional quality planning
or action.

13. Determine Recommended Action(s) to address potential failures that

have a high RPN.

14. Assign Responsibility and a Target Completion Date for these actions.

15. Indicate Actions Taken.

 16. Update the FMEA as the design or process changes, the assessment
changes or new information becomes known.

Diagram:

Failure Mode and Effect Analysis

(Design/Process FMEA)
FMEA Number _____________________
Page_____________of ________________

Item _____ Design/Process Responsibility ___________ Prepared by _________

Model Number/year ____ Key Date _________ FMEA Date _____ Rev _________

Core Team _________________________________________________________________

Product/ Potential Potential S Potential O Current D R Recommended Responsibility Action

Process Failure Effects of Causes Controls P Actions and Target Taken
Function Mode Failure of N Completion
Requirements Failure Dates

Body Cracking Non- 10 Thermal 2 Design 2 40

operational Stresses Checking

Handle Breaking Temporary 6 Mechanic 6 Design 2 72

Disuse al Abuse Checking
Washer Melting Non- 6 Overheati 4 Design 3 72
operational ng Checking

3. List out the seven new management tools and its applications in detail.
Apr 08, Apr 14, Apr 10, Nov 12, Nov 13

Introduction:
The seven basic quality tools are mostly useful for quantitative problems,
whereas the new seven management tools are defined for the qualitative
problems.
In 1976, the Union of Japanese Scientists and Engineers (JUSE) saw
the need for tools to promote innovation, communicate information and
successfully plan major projects. A team researched and developed the seven
new quality control tools, often called the seven management and planning
(MP) tools, or simply the seven management tools. Not all the tools were
new, but their collection and promotion were.

Management Tools:
  Affinity Diagram
 Relationship Diagram
 Tree Diagram
 Matrix Diagram
 Matrix Data Analysis
 Decision Tree
 Arrow Diagram

The seven MP tools, listed in an order that moves from abstract analysis to
detailed planning, are:

1. Affinity diagram: organizes a large number of ideas into their natural

relationships.
2. Relations diagram: shows cause-and-effect relationships and helps you
analyze the natural links between different aspects of a complex situation.
3. Tree diagram: breaks down broad categories into finer and finer levels of
detail, helping you move your thinking step by step from generalities to
specifics.
4. Matrix diagram: shows the relationship between two, three or four groups of
information and can give information about the relationship, such as its
strength, the roles played by various individuals, or measurements.
5. Matrix data analysis: a complex mathematical technique for analyzing
matrices, often replaced in this list by the similar prioritization matrix. One of
the most rigorous, careful and time- consuming of decision-making tools, a
prioritization matrix is an L-shaped matrix that uses pair wise comparisons of
a list of options to a set of criteria in order to choose the best option(s).
6. Arrow diagram: shows the required order of tasks in a project or process,
the best schedule for the entire project, and potential scheduling and resource
problems and their solutions.
7. Process decision program chart (PDPC): systematically identifies what
might go wrong in a plan under development.

AFFINITY DIAGRAM (KJ DIAGRAM)

Definition: it is a tool to collect a large amount of verbal expressions and

organize them in groups according to natural relationships between individual
items.

Purpose: For synthesizing, classifying, organizing indefinite ideas.

This tool takes large amounts of disorganized data and information and
enables one to organize it into groupings based on natural relationships. It was
created in the 1960s by Japanese anthropologist Jiro Kawakita.

Diagram:

Define Problem ----- Generate Ideas -------- Record Ideas on Cards -----
Display Cards in Random Order ------- Arrange Cards in Grouping ------
Create headers for Groupings ----- Draw the Affinity Diagram

Affinity Diagram: REFER PHOTOCOPY

INTERRELATIONSHIP DIAGRAPH OR RELATIONSHIP DIAGRAM

Definition: A tool for finding causes to a problem.

Purpose: For isolating cause and effect relationship.

This tool displays all the interrelated cause-and-effect relationships and

factors involved in a complex problem and describes desired outcomes.
The process of creating an interrelationship diagraph helps a group analyze the
natural links between different aspects of a complex situation.

Diagram: REFER PHOTOCOPY

TREE DIAGRAM

Definition: it is a systematically breaks down a topic into its component

elements, and shows the logical and sequential links between these elements.

Purpose: For developing general concepts into details.

This tool is used to break down broad categories into finer and finer levels of
detail. It can map levels of details of tasks that are required to accomplish a
goal or task. It can be used to break down broad general subjects into finer and
finer levels of detail. Developing the tree diagram helps one move their thinking
from generalities to specifics.

Diagram: REFER PHOTOCOPY

MATRIX DIAGRAM

Definition: It is a tool which depicts the relation between two, three or four
sets of factors in the form of a table or a matrix.

Purpose: For correlating in a logical form, in order to evaluate, select and

decide.

This tool shows the relationship between items. At each intersection a

relationship is either absent or present. It then gives information about the
relationship, such as its strength, the roles played by various individuals or
measurements. Six differently shaped matrices are possible: L, T, Y, X, C and
roof-shaped, depending on how many groups must be compared.
Diagram: REFER PHOTOCOPY

MATRIX DATA ANALYSIS OR PRIORITIZATION MATRIX

Definition: it is very much similar to a matrix diagram with a difference that

numerical data is used instead of symbols indicating the existence and
strength relationships.

Purpose: For quantifying relationships

This tool is used to prioritize items and describe them in terms of weighted
criteria. It uses a combination of tree and matrix diagramming techniques to do
a pair-wise evaluation of items and to narrow down options to the most desired
or most effective.

Diagram: REFER PHOTOCOPY

PROCESS DECISION PROGRAM CHART (PDPC) OR DECISION TREE

Definition: It is a planning tool to outline every conceivable and likely

occurrence in any planning. It forces proactive thinking on what can go wrong
with one’s plan and what would one do to overcome the effect of such adverse
occurrences.
Purpose: For identifying alternatives.

A useful way of planning is to break down tasks into a hierarchy, using a Tree
Diagram. The PDPC extends the tree diagram a couple of levels to identify risks
and countermeasures for the bottom level tasks. Different shaped boxes are
used to highlight risks and identify possible countermeasures (often shown as
'clouds' to indicate their uncertain nature). The PDPC is similar to the Failure
Modes and Effects Analysis (FMEA) in that both identify risks, consequences of
failure, and contingency actions; the FMEA also rates relative risk levels for
each potential failure point.

Diagram: REFER PHOTOCOPY

ACTIVITY NETWORK DIAGRAM OR PERT OR ARROW DIAGRAM

Definition: It is a graphic description of the sequential steps that must be

completed before a project can be completed.
PERT - Program/Project Evaluation and Review Technique and CPM – Critical
Path Method are the best known arrow diagrams.

Purpose: For planning.

This tool is used to plan the appropriate sequence or schedule for a set of tasks
and related subtasks. It is used when subtasks must occur in parallel. The
diagram enables one to determine the critical path (longest sequence of tasks).
(See also PERT diagram.)

Diagram: REFER PHOTOCOPY