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An Introduction to Six Sigma
Before Getting to Know “Six Sigma”
It is Important to Understand, What is Quality?
Compliance to customer requirements / specifications
In different industries the concept of quality may differ
Banking Industries – Time bound and accurate delivery of services
Manufacturing Industries – Production of product with in the specified specifications
BPO Services – Time Bound Response
but consequences of compromised quality are same
“Loss in Revenue, Damage to Brand Image”
Total Quality Management (TQM)
Total Quality Management may be defined as “ managing the entire organization so that it excels on all
dimensions of products and services that are important to the customer”
It has two fundament operational goals
Careful design of the product or service
Ensuring that the organization’s system can consistently produce the design
Maintaining the quality of the product or service is the prime responsibility of Top Management
Top management is responsible, if an organization is not delivering quality product or service to its customers
Developing Quality Specifications…
Design Quality – It refers to inherent value of the product in the marketplace and is
thus a strategic decision for the firm.
The dimensions of quality are:-
• Performance – Primary product or service characteristics
• Features- Added touches, bells and whistles, secondary characteristics
• Reliability / durability – Consistency or Performance over time, Probability of failing, useful life
Developing Quality Specifications…
• Serviceability – Ease of repair
• Aesthetics – Sensory Characteristics (sound, feel, look and so on)
• Perceived Quality – Part performance and reputation
Example of Dimensions of Quality
Product Example Service Example
DIMENSION LASER Printer Checking Account at a Bank
Pages per minute
Time to process customer requests
Multiple paper trays
Automatic bill Paying
Mean time between failures Variability of time to process request
Availability of authorized repairs
centers, Modular design
Online Reports, Ease of getting updated
Controls buttons layout, Case style,
Courtesy of dealer
Appearance of bank lobby, Courtesy of teller
Brand name recognition, Rating in
Endorsed by community leaders
Developing Quality Specifications…
• Conformance Quality – It refers to the degree to which the product or service design
specifications are met. It is evident that a product or service can have high design quality but
low conformance quality, and vice versa (e.g. Six Sigma process)
• Quality at source- It can also be understood as conformance of quality, while producing the
product or delivering a service i.e. production of products should be done such a way that
the chance of bad quality is zero. With efficient POKA YOKE, a quality product can be ensure
at the source.
Both quality of design and quality of conformance should provide products that meet the customer’s objective for those
products. This is often termed the product’s fitness for use, and it entails identifying the dimensions of the product or
service that the customer wants ( that is the voice of the customer) and developing a quality and control program to
ensure that these dimensions are met.
PDCA in TQM
• When to Use Plan–Do–Check–Act
-As a model for continuous improvement.
-When starting a new improvement
-When developing a new or improved
design of a process, product or service.
-When defining a repetitive work process.
-When planning data collection and
analysis in order to verify and prioritize
problems or root causes.
-When implementing any change.
The plan–do–check–act cycle (Figure) is a four–step model for carrying out change. Just as
a circle has no end, the PDCA cycle should be repeated again and again for continuous
• Plan- Recognize an opportunity and plan a change.
• Do- Test the change. Carry out a small-scale study.
• Check- Review the test, analyze the results and identify what you’ve learned.
• Act- Take action based on what you learned in the study step: If the change did not work, go
through the cycle again with a different plan. If you were successful, incorporate what you
learned from the test into wider changes. Use what you learned to plan new improvements,
beginning the cycle again.
Cost Of Quality
• It refers to all the cost attributable to the production of quality that is not 100% perfect.
• It is been observed that bad quality of product may cost as large as 15%-20% of sales value.
• The cost of quality are generally classified into four types:-
1. Appraisal Cost- Cost of Inspection, testing and other task to ensure that the product or process is acceptable.
2. Prevention Costs- The sum of all the cost to prevent defects, such as the costs to indentify the cause of the
defect, to implement corrective action to eliminate the cause, to train personnel, to redesign the product or
system, and to purchase new equipment or make modifications.
3. Internal Failure Costs- Costs for defects incurred within the system: scrap, rework, repair.
4. External Failure Costs- Cost for defects that pass through the system: customer warranty replacements, loss of
customer goodwill, handling complaints and product repair.
Costs incurred in measuring and controlling current production to assure conformance to
requirements, such as
A. Purchasing appraisal costs
1. Receiving or incoming inspections and tests
2. Measurement equipment
3. Qualification of supplier product
4. Source inspection and control programs
B. Operations (manufacturing or service) appraisal costs 1. Planned operations inspections, tests, audits
a. Checking labor
b. Product or service quality audits
c. Inspection and test materials
1. Set-up inspections and tests
2. Special tests (manufacturing)
3. Process control measurements
4. Laboratory support
1. Measurement equipment
1. Depreciation allowances
2. Measurement equipment expenses
3. Maintenance and calibration labor
5. Outside endorsements and certifications
C. External appraisal costs
1. Field performance evaluation
2. Special product evaluations
3. Evaluation of field stock and spare parts
D. Review of tests and inspection data
E. Miscellaneous quality evaluations
Costs incurred to prevent the occurrence of non-conformances in the future, such as
1. Marketing research
2. Customer/user perception surveys/clinics
3. Contract/document review
B. Product/service/design development
1. Design quality progress reviews
2. Design support activities
3. Product design qualification test
4. Service design qualification
5. Field tests
1. Supplier reviews
2. Supplier rating
3. Purchase order tech data reviews
4. Supplier quality planning
D. Operations (manufacturing or service)
1. Operations process validation
1. Operations quality planning
2. a. Design and development of quality measurement and control equipment
2. Operations support quality planning
3. Operator quality education
4. Operator SPC/process control
Internal failure cost
Costs generated before a product is shipped as a result of non-conformance to requirements, such as
A. Product/service design failure costs (internal)
1. Design corrective action
2. Rework due to design changes
3. Scrap due to design changes
B. Purchasing failure costs
1. Purchased material reject disposition costs
2. Purchased material replacement costs
3. Supplier corrective action
4. Rework of supplier rejects
5. Uncontrolled material losses
Internal failure cost
C. Operations (product or service) failure costs
1. Material review and corrective action costs
a. Disposition costs
b. Troubleshooting or failure analysis costs (operations)
c. Investigation support costs
d. Operations corrective action
2. Operations rework and repair costs
3. Re-inspection / retest costs
Internal failure cost
4. Extra operations
5. Scrap costs (operations)
6. Downgraded end product or service
7. Internal failure labor losses
D. Other internal failure costs
External Failure Costs
Costs generated after a product is shipped as a result of non-conformance to requirements, such as
A. Complaint investigation/customer or user service
B. Returned goods
C. Retrofit costs
D. Recall costs
E. Warranty claims
F. Liability costs
H. Customer/user goodwill
I. Lost sales
J. Other external failure costs
Introduction to Six-Sigma Theory
The Theory of Six Sigma
• Six Sigma reflects the goal of having customer
specification limits of the item produced by a
process be twice the natural variation (±3σ) of
the process output
• In another way, the process variation should be
half of the specification limits
• Where σ is the standard deviation of the
• Theory of Six Sigma assumes that the process is
• A 3σ process defines 99.73% outcomes are within the specification limits
• That means 0.27% of outcomes are out of the specification limits or 2700 defects out of one million
• To make the process compliance to 6σ, the standard deviation of the process has to be reduced to half
of 3σ process
• A 6σ process defines 99.99966% outcomes are within the specification limits, that means 0.00034%
outcomes are outside the specification limits i.e. 2 parts per billion
Six Sigma Quality
One of the benefits of Six Sigma thinking is that is allows managers to readily describe the
performance of a process in terms of its variability and to compare different process using a
common metric. This metric is defects per million opportunities (DPMO).
This calculation requires three pieces of data :
1. Unit : The items produced or being seviced
2. Defect : Any item or event that does not meet the customer’s requirements.
3. Opportunity : A chance for a defect to occur
Six Sigma Quality
The customer of a mortgage bank expect to have their mortgage application processed with in 10 days of
This would be called a Critical Customer Requirement, or CCR, in Six Sigma terms.
Suppose all defects are counted (loan in a monthly sample taking more than 10 days to process), and it is
determined that there are 150 loans in the 1000 application processed last month that don’t meet this
Thus the DPMO= 150/1000X1,000,000 , or 150000 loans out of every million processed that fail to meet a
Put differently, it means that only 850,000 loans out of a million are approved with in time expectations.
Statistically, 15% of the loans are defective and 85% are correct.
DPMO and σ level (Process Capability)
• There are two ways by which we can know the sigma level the process is
performing in :
1. Direct Method: This involves directly comparing the DPMO value with the chart to find the
sigma level the process is performing in.
From the previous example, the DPMO was found out to be 150,000
From the table the sigma level can be found out to be around 2.53
2. From Excel
A more accurate sigma level can be found out from using
Use the formulae
=NORMSINV (1-(No of defect/Number of opportunities))+ 1.5
For the above example, the sigma level was found that the
process has a capability of operating at 2.53σ
• Six Sigma's methods include many of the statistical tools that were employed in other quality movement.
• Six Sigma method is employed in a project orented fashion through-
• Define, Measure, Analyze, Improve, Control (DMAIC) cycle.
• The DMAIC cycle is more detailed version of Deming PDCA cycle which consist of four steps Plan, Do, Check and
Act – that underly Continuous Improvement
• Continuous Improvement- Also know as “Kaizen” seeks continuous improvement of Machinery, Material,
labor utilization, and production methods through application of suggestions and ideas of company team.
• Six Sigma also emphasizes the scientific methods, particularly hypothesis testing about the relationships
between process inputs (X’s) and outputs (Y’s) using design of experiments (DOE) methods
The Standard approach to Six Sigma project is DMAIC methodology developed by General Electric, as describe below
1. Define (D)
• Identify customer and their priorities
• Identify a project suitable for Six Sigma efforts based on business objectives as well as customer needs and feedback
• Identify CTQs (Critical-To-Quality characteristics) that the customer consider to have the most impact on quality
2. Measure (M)
• Determine how to measure the process and how it is performing
• Identify the key internal processes that influence CTQs and measure the defects currently generated relative to those
3. Analyze (A)
• Determine the most likely cause defects
• Understand why defects are generated by identifying the key variables that are most likely to create process variation
4. Improve (I)
• Identify means to remove the cause the defects
• Confirm the key variable and qualify their effects on the CTQs
• Identify the maximum acceptance range of the key variables and a system for measuring deviations of the variables
• Modify the process to stay in the acceptable range
5. Control (C)
• Determine how to maintain the improvements
• Put tools in place to ensure that the key variables remain within the maximum acceptable range under modified
As a Management system
• It has been observed that although most organizations can show solid successes at the project
level, a collection of projects typically doesn’t add up to the breakthrough performance and
sustainable improvement that Six Sigma has a reputation for delivery.
• What’s missing from such project-oriented implementations is an infrastructure that links
leadership behavior and management systems to project selection, coaching and oversight.
• Organizations are looking for the statistical leaders who can launch an implementation and teach
the methodology to project teams. Most of these recruitment efforts occur through resume
screening and conversations at the project level. In other words MBBs (Master Black Belts) are
hired mainly, and often only, based on the technical requirements of a statistical leader .
• In fact only about one third of an MBB’s role is technical, rest is about leading, yet nobody’s
testing for leadership
As a Management system
Five leadership behaviors that are crucial to support an infrastructure of breakthrough improvement:
Passion for creating customer value
Leading through fact-based decision making
Moving through performance metrics
Advocacy for breakthrough improvement
When hiring Six Sigma leaders, organization should look for evidence of these behaviors in addition
to technical abilities. Existing MBBs, as well as champions and other Six Sigma leaders for that
matter, should also consciously develop these behaviors to improve the effectiveness of their
A Management System that Drives Six Sigma
• Breakthrough Six Sigma performance can only occur when Six Sigma is aligned with an
organization’s overall business strategy.
• The more closely an individual project is tied to organizational goals, the better its chances for
producing far reaching and lasting results.
• The more fluidly the work of Black Belts, Green belts, and improvement teams fits into the large
stream of daily operations, the more essential that work will appear to the rest of the
• A management system should integrate the following strategic business methods and approaches
to guide Six Sigma project selection and reward Six Sigma staff:
• Scorecards to prioritize business objectives
• Dashboards to track operational metrics
• Performance management system to rewards Six Sigma staff in way that is consistent with recognition for
non Six Sigma staff
Elements of Six Sigma
Elements of Six Sigma
There are three key elements of quality:
Everything a organization should do to remain a world-class quality company focuses on these three
• Customers should be the center of a business
• Customers define quality of product and services
• They expect performance, reliability, competitive
prices, on-time delivery, service, clear and correct
transaction processing and more.
• In every attribute that influences customer
• Just being good is not enough. Delighting our
customers is a necessity. Because if you don't do it,
someone else will!
Outside-In Thinking (GE View)
• Product Quality requires us to look at business from the customer's perspective
• Look at processes from the outside-in view
• Understanding the transaction lifecycle from the customer's needs and processes, to discover
what customers are seeing and feeling
• This knowledge will identify areas where significant values or improvements may be added from
• People create results. Involving all employees is essential to a
quality approach. Organization should be committed to providing
opportunities and incentives for employees to focus their talents
and energies on satisfying customers.
• All employees should be trained in the strategy, statistical tools
and techniques of Six Sigma quality.
• Quality Overview Seminars: basic Six Sigma awareness.
• Team Training: basic tool introduction to equip employees to
participate on Six Sigma teams.
• Master Black Belt, Black Belt and Green Belt Training: In-depth
quality training that includes high-level statistical tools, basic
quality control tools, Change Acceleration Process and Flow
• Quality is the responsibility of every employee. Every employee
must be involved, motivated and knowledgeable for a successful
Analytical Tools for Six Sigma and Continuous Improvement
Analytical Tools for Six Sigma
The analytical tools of Six Sigma have been used for many years in traditional quality improvement
programs. What makes their application to six sigma unique is the integration of these tools in a
corporate management system.
1. Quality Function Deployment (QFD)
2. Cause and effect matrix
3. Failure mode and effect analysis (FMEA)
4. Control Chart
5. T- Test
6. Design of Experiment (DOE)
Quality Function Deployment (QFD)
In Six Sigma DMAIC, Quality Function Deployment (QFD) is a methodology and tool used in the Define
QFD is used to:
• Collect customer’s requirements/desires as specified by the customers in their own words
• Prioritize these desires
• Translate them into engineering/process requirements
• Establish targets to meet the requirements.
• QFD is also termed as:
• Voice of the Customer
• House of Quality
• Customer-Driven Engineering
• Matrix Product Planning
QFD is a customer driven product or service planning process. It is a methodology for translating customer
requirements into company requirements at each stage from Concept Definition (R&D) to Process Engineering and
Production and into the marketplace.
The QFD matrix is a tool to translate CCRs (Critical Customer Requirements ) into CTQs (Critical to Quality).
Quality Function Deployment (QFD)
QFD collects the voice of the customer (VOC) in their own lingo and incorporates this VOC into the
companies cross-functional team’s project management of the integrated development process. The
QFD process establishes customer objectives and measures and records them on a series of matrices
QFD matrix translates the CCRs into CTQs.
The final score helps prioritize the CTQs and
helps you decide which CTQs to tackle first.
The QFD Methodology
Identify both internal and external customers.
Create a list of customer requirements/desires (Whats) by
Asking the customer, questions such as “What are the important features of The Product”
Capturing the customer’s own words or “Voice of the Customer” or VOC
Categorizing the Whats into groups/buckets if needed.
Prioritize the above collected Whats on a scale of 1-5, with 5 being the most important. This ranking is
based on the VOC (Voice of Customer) data.
The CCRs (Whats) are listed vertically in the first column and all related CTQs (Hows) are listed horizontally
across the top . In the second column, assign 1 to 5 based on the importance of the CCRs, where 5 is the
most critical to the customer.
Score each CTQ (Hows) on how strongly it correlates to each CCR. Remember we are looking at the
absolution value of the correlation. It could be either positively correlated or negatively correlated. Use 5
for a strong correlation and 1 is a weak one. Leave it blank if there is no correlation. Some CCRs will have
few CTQs that relate and rest unrelated.
Compile list of CTQs (Hows) necessary to achieve the CCRs (Whats.)
Translate the CCRs from VOC (Whats) into CTQs (Hows)
The QFD Methodology..
Arrows show direction for improvement (up for increasing, down for decreasing, etc.)
For each What, find out the correlation with each How. If the correlation is strong use 5. If its week
use 1. If its in between, use a number 2,3,4 based on how strong the correlation is.
Next multiply the importance rating for the CCR by the correlation score for each CTQ.
Add up the scores vertically for each CTQ and place that value in the bottom score row.
Once the score is computed for all CTQs, the ones with the highest scores are the highest priority Six
Sigma project objectives to work on.
Cause and Effect Matrix
Cause and effect diagram is a very simple and very
effective method for root cause analysis of quality
Causes are usually grouped into major categories to
identify these sources of variation. The categories typically
• People: Anyone involved with the process
• Methods: How the process is performed and the
specific requirements for doing it, such as policies,
procedures, rules, regulations and laws
• Machines: Any equipment, computers, tools, etc.
required to accomplish the job
• Materials: Raw materials, parts, pens, paper, etc. used
to produce the final product
• Measurements: Data generated from the process that
are used to evaluate its quality
• Environment: The conditions, such as location, time,
temperature, and culture in which the process operates
FMEA (Failure Mode Effect Analysis)
Failure Modes and Effects Analysis (FMEA) is a systematic, proactive method for evaluating a process to
identify where and how it might fail and to assess the relative impact of different failures, in order to
identify the parts of the process that are most in need of change. FMEA includes review of the following:
• Steps in the process
• Failure modes (What could go wrong?)
• Failure causes (Why would the failure happen?)
• Failure effects (What would be the consequences of each failure?)
• Based on severity of the failure mode of the process a severity number “S” is given (range 1-10)
• Based on occurrence of the failure an occurrence number “O” is given (range 1-10)
• Based on detection techniques available in the process to detect the failure in the process a detection
number “D” is given (range 1-10)
• The effectiveness of process is calculated by Risk Priority Number (RPN) that is RPN=S X O X D range
• RPN number indication of risk of failure in the process, threshold value of RPN is decided by the team
involved in the FMEA (Industry standard is RPN=90~100)
• Any process with RPN more than threshold, must have recommended actions to reduce the RPN
Note:- RPN number is an indicator of risk, but improvement actions are required for any process
with severity more than 9
RPN for item A is 90, but for item B RPN is 112, therefore as per RPN threshold theory recommended
actions are required for Item B.
But As severity of Item A is high “9”, therefore recommended action for item A is also required.
There are three main elements of a control chart as shown in Figure
A control chart begins with a time series graph.
A central line (X) is added as a visual reference for detecting shifts or trends – this is also referred to
as the process location.
Upper and lower control limits (UCL and LCL) are computed from available data and placed
equidistant from the central line. This is also referred to as process dispersion.
Control limits (CLs) ensure time is not wasted looking for unnecessary trouble – the goal of any
process improvement practitioner should be to only take action when warranted. Control limits are
• Estimating the standard deviation, σ, of the sample data
• Multiplying that number by three
• Adding (3 x σ to the average) for the UCL and subtracting (3 x σ from the average) for the LCL
Mathematically, the calculation of control limits looks like:
(Note: The hat over the sigma symbol indicates that this is an estimate of standard deviation, not the
true population standard deviation.)
Because control limits are calculated from process data, they are independent of customer
expectations or specification limits.
Controlled variation is characterized by a stable and consistent pattern of variation over time, and is
associated with common causes. A process operating with controlled variation has an outcome that
is predictable within the bounds of the control limits.
Uncontrolled variation is characterized by variation that changes over time and is associated with
special causes. The outcomes of this process are unpredictable; a customer may be satisfied or
unsatisfied given this unpredictability.
Please note: process control and process capability are two different things. A process should be
stable and in control before process capability is assessed.
The X BAR CHART is used to evaluate consistency of process averages by plotting the average of
each subgroup. It is efficient at detecting relatively large shifts (typically plus or minus 1.5 σ or
larger) in the process average.
The R chart, on the other hand, plot the ranges of each subgroup. The R chart is used to evaluate the
consistency of process variation. Look at the R chart first; if the R chart is out of control, then the
control limits on the X bar chart are meaningless.
“The range over which the natural variation of a process occurs as determined by the system of
common causes. It is measured by the proportion of output that can be produced within design
Three situations are possible:
Case I: When the process capability is less than the tolerance (6σ<USL-LSL)
USL – Upper specification limit
LSL – Lower specification limit
Case II: When the process capability is equal to the tolerance (6σ=USL-LSL)
Case III: When the process capability is less than the tolerance 6σ>USL-LSL
Process Capability Index
Introduction to Minitab- A tool for Statistics
Minitab Analyze your data and improve your products and services with the leading statistical
software used for quality improvement worldwide
Minitab can –
• Exploring data with graphs
• Conducting statistical analyses and procedures
• Assessing quality
• Designing an experiment
There will be detiled content on Minitab in upcoming classes
To have a little flavour of Minitab, lets hypothesis testing with Minitab
Performing an ANOVA
• One of the most commonly used methods in statistical decisions is hypothesis testing. Minitab offers
many hypothesis testing options, including t-tests and analysis of variance. Generally, a hypothesis test
assumes an initial claim to be true, then tests this claim using sample data.
• Hypothesis tests include two hypotheses: the null hypothesis (denoted by H0) and the alternative
hypothesis (denoted by H1). The null hypothesis is the initial claim and is often specified using
previous research or common knowledge. The alternative hypothesis is what you may believe to
Perform an ANOVA
1 Choose Stat ➤ ANOVA ➤ One-Way.
2 In Response, enter Days. In Factor, enter Center.
In many dialog boxes for statistical commands, you
can choose frequently used or required options.
Use the sub dialog box buttons to choose other
Perform an ANOVA
3 Click Comparisons.
4 Check Tukey’s, family error rate, then click OK.
5 Click Graphs.
For many statistical commands, Minitab
includes built-in graphs that help you
interpret the results and assess the validity
of statistical assumptions.
6 Check Individual value plot and Boxplots of data.
7 Under Residual Plots, choose Four in one.
8 Click OK in each dialog box.
t-Test in Six Sigma
• The 1-Sample T test evaluates whether some chosen number is likely to be the true mean of
a population, based on information from a sample.
• The 2-Sample T Test evaluates whether two samples were likely drawn from different
• The Paired T Test is similar to the 2-Sample test, but is for data that occur in natural pairs.
One Sample test
The data show reductions in Blood Pressure in a sample of 17 people after a certain treatment. We
wish to test whether the average reduction in BP was at least 13%, a benchmark set by some other
treatment that we wish to match or better
15 BP Reduction
Probability Plot of BP Reduction
Normal - 95% CI
One Sample t-test – Minitab results
The p-value of 0.20 indicates that the reduction in BP could not be proven to be greater than 13%.
There is a 0.20 probability that it is not greater than 13%.
Two Sample t-test
You realize that though the overall reduction is not proven to be more than 13%, there seems to be
a difference between how men and women react to the treatment. You separate the 17
observations by gender, and wish to test whether there is in fact a significant difference between
95% Bonferroni Confidence Intervals for StDevs
Test Statistic 0.96
Test Statistic 0.14
Test for Equal Variances for BP ReductionM F
Two Sample t-test
The test for equal variances shows that they are not different for the 2 samples. Thus a 2-sample t
test may be conducted. The results are shown below. The p-value indicates there is a significant
difference between the genders in their reaction to the treatment.
Design of Experiment (DOE)
Design of Experiments (DOE) techniques enables designers to determine simultaneously the
individual and interactive effects of many factors that could affect the output results in any
design. DOE also provides a full insight of interaction between design elements; therefore, it
helps turn any standard design into a robust one. Simply put, DOE helps to pin point the
sensitive parts and sensitive areas in designs that cause problems in Yield. Designers are then
able to fix these problems and produce robust and higher yield designs prior going into
Let us assume that we have designed an amplifier and we need to design an experiment to
investigate the sensitivity of this amplifier to process variation. In other words, we would like
to find out if there are any elements in the design that largely affect the output response due
to their high sensitivities to the output measure.
In this example, let us chose three elements where we want to see their effects on the Gain of the amplifier. These
elements are: W (the width of the microstrip lines), a resistor (R), and a Capacitor (C).
Since we chose three elements, we must construct 8 experiments (2^3) for a Full factorial experiment. We assign a -1 and
+1 values to each of the elements. For example the nominal value of the Resistor is described with a “0”. A “-1”
represents a -5% variation from its nominal value and a “+1” represents a +5% variation from its nominal value. Therefore
if our resistor’s nominal value is 20 ohms, a “-1” represents a 19 ohms value, and a “+1” represents a 21 ohms value.
Start by choosing variables that affect the response
Example: For W
-1 corresponds to 9.5 µm
+1 corresponds to 10.5 µm
0 corresponds to nominal value, 10µm
Next, we run the simulation eight times to get the gain (our output measure) for all the combination
of +1’s and -1’s of the three elements and this is what we get:
From the results above, let us extract the main effects of Capacitor, C on the Gain. We calculate the
average Gain when C is “-1” and when C is “+1” and determine the total gain variation due to the
The table below shows that this gain variation (due to C) is .044 dB.
Main Effect of Capacitors, C on Gain
Next we do the same thing for the Resistor. Notice that the gain variation due to the Resistor is .85
dB, which is much higher than that of the Capacitor. (See table below). This already tells us that the
resistor is a trouble component and causes higher variation in the gain.
The main effects can be plotted for easier view of the components’ sensitivities to Gain. Below is the
main effects plot of the Capacitor and the resistor (calculated above) on the Gain variation.
DOE is also very useful in getting information on the interactions between the elements in a design
and how these interactions affect the variation in the output measure (Gain, in our example)
The table below calculates the interaction effect between W and R. The interaction is very small and
negligible (.0088 dB).
Doing the same procedure for all elements and their interactions, we obtain the following results.
Obtaining the Rest of the Coefficients
Construct a linear equation to represent the experiment results:
Gain=13.8 + .09W + .85R + .044C + .0088WR + …. Etc.
Pareto Charts are very useful in DOE. The results can be plotted on a Pareto type chart in order to make it
much easier to visualize the main and interaction effects of all components to the Gain variation.
It is very clear from the results above that the Resistor R has the most contribution to the Gain variability
The designer will then focus his / her efforts in reducing that variation due to the resistor. One way to do
that in Board or MIC designs is to buy a screened part that has +/- 1% tolerance instead of a +/- 5%
tolerance. In MMIC design, the designer would want to either use a different resistive layer of lower
sensitivity, or make the resistor as wide as possible since this would reduce its sensitivity.
Why six sigma fails
• No concept of Customer expectations
• No vision related to Customer expectations
• No follow-up on the annual operating plan
• Lack of alignment (horizontal or vertical)
• No visible leadership at the executive level
• Business executives do not show up for report-outs (conveys a lack of priority)
• Deploying Six Sigma without a goal (reason for deployment)
• Deploying Six Sigma with a goal but no plan on how to get there
• Abdicating the deployment plan to a consulting company
• Trying to change the organization without a detailed change process
• Not having metrics in place for management participation
• No metrics for Champions
• Champions do not show up for report-outs
• Having metrics in place but no feedback (or limited feedback annually, semi-annually, quarterly)
• Not having multiple projects queued up for each MBB, BB or GB (so when they complete a project the
next one has already been selected)
• Not communicating deployment plans effectively through the organization
• No rewards or recognition program
• A rewards or recognition program that does not recognize teams
• No retention program for trained personnel
Voice of Customer (VOC)
“The “voice of the customer” is a process used to capture the requirements/feedback from the
customer (internal or external) to provide the customers with the best in class service/product
quality. This process is all about being proactive and constantly innovative to capture the changing
requirements of the customers with time”
The “voice of the customer” is the term used to describe the stated and unstated needs or
requirements of the customer. The voice of the customer can be captured in a variety of ways: Direct
discussion or interviews, surveys, focus groups, customer specifications, observation, warranty data,
field reports, complaint logs, etc.
This data is used to identify the quality attributes needed for a supplied component or material to
incorporate in the process or product.
Six Sigma COPIS/ SIPOC Model
The Voice of the Customer (VOC) is aggressively evaluated and used to determine
needed outputs and hence the optimal process configuration needed to yield those
outputs and their necessary inputs for which the best suppliers are identified and allied
Six Sigma COPIS/ SIPOC Model
The SIPOC is often presented at the outset of process improvement efforts such as Kaizen events or
during the "define" phase of the DMAIC process. It has three typical uses depending on the
• To give people who are unfamiliar with a process a high-level overview
• To reacquaint people whose familiarity with a process has faded or become out-of-date due to
• To help people in defining a new process
Several aspects of the SIPOC that may not be readily apparent are:
• Suppliers and customers may be internal or external to the organization that performs the
• Inputs and outputs may be materials, services, or information.
• The focus is on capturing the set of inputs and outputs rather than the individual steps in the
Example SIPOC: Automobile Repair
Supplier Input Process Output Customer
Vehicle for repair
Parts for approved
Prepare work order
Notify that service is
and cost estimates
Parts for approved
“A systematic approach to identifying and eliminating waste(non-value-added activities)
through continuous improvement by flowing the product at the pull of the customer in pursuit
Types of waste (MUDA)
Theory Of Constraints
• Maximum speed of the process is the speed of the slowest operation
• Any improvements will be wasted unless the bottleneck is relieved
“Bottlenecks must be identified and improved if the process is to be improved”
Identification of constraints allows management to take action to alleviate the constraint in the future
• Reduce cycle time : Time from receipt of customer order to shipment
• Improve manufacturing cycle efficiency (MCE) : Processing time / total cycle time
Theory of constraints
Based on the concepts of drum, buffer and ropes
Output of the constraint is the drumbeat
• Sets the tempo for other operations
• Tells upstream operations what to produce
• Tells downstream operations what to expect
Stockpile of work in process in front of constraint
• Precaution to keep constraint running if upstream operations are interrupted
Sequence of processes prior to and including the constraint
• Want to “pull” the rope at the maximum speed
• Speed of the constraint
Quick response manufacturing
QRM Includes all Activities in the Customer Chain, Including:
• Material Planning
• Shop Floor Control (POLCA)
• Supply Chain
• Customers & Sales Function
• Up-Front, Office Operations
• Mindset and Performance Measures
Factory Physics – An Overview
Toyota Production System
• JIT(Just in time)
• Autonomation ( Automation with a human touch)
Setup reduction (SMED)
Motivation: Small lot sequences not feasible with large setups.
• Internal vs. External Setups:
– External – performed while machine is still running
– Internal – performed while machine is down
• Separate the internal setup from the external setup
• Convert as much as possible of the internal setup to the external setup
• Eliminate the adjustment process
• Abolish the setup itself (e.g., uniform product design, combined
production, parallel machines)
Factory Physics- Continued…
•float where needed
•appreciate line-wide perspective
•provide more heads per problem area
•can be done by adjacent stations
•reduces variability in tasks, and hence line stoppages/quality problems
Fool proofing (poka-yoke)
Factory Physics- Continued…
A “kanban” is a sign-board or card in Japanese and is the name of the flow control system developed
Kanban is a tool for realizing just-in-time. For this tool to work fairly well, the production process
must be managed to flow as much as possible. This is really the basic condition. Other important
conditions are leveling production as much as possible and always working in accordance with
standard work methods.
Push vs. Pull: Kanban is a “pull system”
– Push systems schedule releases
– Pull systems authorize releases
Factory Physics- Continued…
Integrality to JIT:
•JIT requires high quality to work
•JIT promotes high quality
•identification of problems
•facilitates rapid detection of problems
•pressure to improve quality
• Process Control (SPC)
• Easy-to-See Quality
• Insistence on Compliance (quality first, output second)
• Line Stop
• Correcting One's Own Errors (no rework loops)
• 100 Percent Check (not statistical sampling)
• Continual Improvement
• Small Lots
• Vendor Certification
• Total Preventive Maintenance
Six Sigma Way of Transformation
Six Sigma Way
Six Sigma Way is:
Mindset/Way of thinking
A way of doing
1. A manager states that his process is really working well, out of 1500 parts, 1477 were produced
free of a particular defect and passed inspection. Based upon Six-Sigma theory, how would you
rate this performance, other things being equal.
2. Professor Chase is frustrated by his inability to make a good cup of coffee in the morning. Show
how you would use a fishbone diagram to analyze the process he uses to make a cup of his evil
3. Use the benchmarking process and as many DMAIC analytical tools as you can to show how you
can improve your performance in your weakest course in school.
4. Consider a simple repair performance job that you performed that did not turn out particularly
well. Analyze the mistakes
5. Prepare a SIPOC flowchart of the major steps in the process of boarding a commercial flight.
Start the process with the passenger arriving curbside at your local airport.
6. Prepare an opportunity flow diagram for the same process of boarding a commercial flight.
7. A shoe manufacturing firm learned through a Lean Six Sigma project their boot soles
could be made of a different material requiring two less steps in the process. Removal
of these two steps yielded a monthly cost savings of $7,500. Therefore the reported
financial savings for this LSS project were _____________.
8. A Belt utilized a diamond symbol in a Process Map she created for the process that
was subject to her LSS project. By use of the diamond symbol she was showing a(n)
_______________ point in the process.
d. Repair station
9. When in the process of trying to identify the Critical X’s for a LSS project a Belt creates
a(n) _____________ because frequently it is 20% of the inputs that have an 80%
impact on the output.
a. Pareto Chart
c. Np Chart
d. X-Y Diagram