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Comprehensive Lean Six Sigma Contract
Program
Lean
Six Sigma Flow Chart
Contact
Information
Program
Overview and Format
Program Outline
• Program Participants
• Lean Six Sigma Assessment
• Management Overview/Strategy
and Deployment
• Yellow Belt Training
• Green Belt Training
• Black Belt Training
Program Delivery
• Location
• Dates and Times
• Client will Provide
Program
Overview and Format
Elimination of waste and improved process capabilities are
common goals of both Lean and Six Sigma. The integration of
these systems provides a process improvement methodology that
addresses the responsiveness and capability of the entire
value delivery system. Through aggressive identification and
elimination of non-value added activities (waste), optimum
value flow is achieved. Cycle times are reduced and defects
removed. Travel distances, inventories, set-up times, equipment
downtime, scrap, rework, and other wastes of the "hidden
factory” are attacked. Lean focuses on delivered value
from a customer's prospective through the entire supply chain.
Six Sigma is a proven, statistically based problem solving
process that generates superior data driven solutions, productive
yields, and dramatic bottom-line results. The objectives of
our Lean Six Sigma training are to teach organizations to:
• Reduce time to market for new products
• Reduce delivery time
• Reduce waste and costs
• Reduce work-in-process inventory
• Reduce variability
• Increase profits and customer satisfaction
The training program will consist of the following modules
to be delivered over a 3-4 month period.
• Lean Six Sigma assessment
• Management overview/strategy and deployment training
• Twelve (12) days Green Belt training
• Kaizen event training and facilitation
• Twelve (12) days Black Belt training
Our Lean Six Sigma program is instructor-led and will involve
participants in extensive interactive training. Participants
will be exposed in depth to each topic through classroom assignments
and structured shop floor exercises within team environments.
Each team will perform a Kaizen event in an area as selected
by the executive management team.
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Program
Outline
Program
Participants
There will be a maximum of 20 participants for each of the
Green Belt training and Black Belt training sessions. A subset
of the participants who complete the Green Belt training will
continue on for the Black Belt training.
Lean Six Sigma
Assessment (1 day on-site)
The assessment will focus on the current state of implementation
of Lean Six Sigma using 28 elements. This includes a pre-assessment
questionnaire, on-site interviewing and observation, a written
report detailing the strengths and areas for improvement,
and a summary presentation to management. This assessment
will be used to tailor the training.
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Management
Overview/Strategy and Deployment (one-day seminar and two
days mentoring throughout the implementation of the Lean Six
Sigma Program)
• Lean and Six Sigma overview
• Review strategic plan and operating plan for the facility
• Establish plant productivity baseline
• Define product families
• Select key projects with leadership support
• Estimate project value to business, timing to complete,
and the resources required
• Assign accountability
• Select training participants
• Manage the projects
• Sustain the Gains
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Yellow Belt Training
(3 days)
The Yellow Belt program is available for organizations that
already have at least one or more Green Belts and one or more
Black Belts in order to provide mentoring for the Yellow Belts.
The following topics will be presented during the three day
training:
Lean Six Sigma Enterprise Approach to Improvement
This is an approach to process improvement that merges the
complementary concepts and tools from both Six Sigma and Lean
approaches. The resulting approach will have greater impact
than one that centers on only Six Sigma or Lean. Participants
will learn a short history of each approach and how they can
complement each other. They will be introduced to the Define,
Measure, Analyze, Improve, Control improvement process and
some of the tools associated with each stage.
Change
We will discuss the reason why change fails. We will talk
about the eight steps to producing sustained change within
a manufacturing environment. We will discuss the organizational
structures necessary to support Lean Six Sigma efforts. Lastly,
we will talk about different thoughts and ways to promote,
communicate and reward the challenge of driving change.
5-S and Visual Controls
Participants will learn what is involved in implementing a
sustainable 5-S program. They will be taught the steps in
5-S, what a 5-S audit should look like, and they will have
a classroom game exercise that will reinforce the center concept
of 5-S and why it is not simply a “clean-up” program.
Participants will see examples of visual controls that will
stimulate their thoughts on how they can apply these concepts
to real world situations.
Cost of Quality
Participants will learn about the costs associated with quality,
both internal and external. Exercises will reinforce the costs
associated with poor quality, including the costs associated
with the “hidden factory.”
Team Building/Leadership
Team dynamics plays an important role in the successful completion
of projects. This interactive session will include identifying
team members, guidelines for effective meetings, stages in
team development (forming, storming, norming, performing),
team member roles and individual styles, and characteristics
of successful teams. The Project Charter will be further explained,
including project scoping.
Problem Solving Process/Tools
These tools find the root causes of problems. They are tools
for thinking about problems, obtaining data, identifying possible
solutions, and implementing solutions.
Cause-Effect Matrix
This is a simple Quality Function Deployment matrix used to
emphasize the importance of understanding customer requirements.
It relates the key inputs to the key outputs, which can be
derived from Input/Output Mapping. Key outputs are scored
by their importance to the customer and key inputs are scored
by their relationship to key outputs.
Statistical Thinking
This method of thinking about processes is to note that all
work occurs in a series of connected processes; and that one
primary objective of process improvement is reduction of variation
in these processes. Participants will be introduced to statistical
thinking with examples, and will learn how to become “process
thinkers” to reduce variation in their areas.
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Green Belt Training
(13 days)
Each participant will be required to complete a project of
significant value to his/her organization. These projects
will require the completion of a Project Charter describing
the project and detailing the objectives, team members, costs,
and timeline. The Charter must be approved by both the organization’s
management, as well as RIT. The participants will present
progress reports during the training period. Coaching for
the projects is built into the contract.
Day 1
Six Sigma/Lean Enterprise Approach to Improvement
This is an approach to process improvement that merges the
complementary concepts and tools from both Six Sigma and Lean
approaches. The resulting approach will have greater impact
than one that centers on only Six Sigma or Lean. Participants
will learn a short history of each approach and how they can
complement each other. They will be introduced to the Define,
Measure, Analyze, Improve, Control improvement process and
some of the tools associated with each stage.
Change
We will discuss the reason why change fails. We will talk
about the eight steps to producing sustained change within
a manufacturing environment. We will discuss the organizational
structures necessary to support Lean Six Sigma efforts. Lastly,
we will talk about different thoughts and ways to promote,
communicate and reward the challenge of driving change.
Day 2
5-S and Visual Controls
Participants will learn what is involved in implementing a
sustainable 5-S program. They will be taught the steps in
5-S, what a 5-S audit should look like, and they will have
a classroom game exercise that will reinforce the center concept
of 5-S and why it is not simply a “clean-up” program.
Participants will see examples of visual controls that will
stimulate their thoughts on how they can apply these concepts
to real world situations.
Cost of Quality
Participants will learn about the costs associated with quality,
both internal and external. Exercises will reinforce the costs
associated with poor quality, including the costs associated
with the “hidden factory.”
Team Building/Leadership
Team dynamics plays an important role in the successful completion
of projects. This interactive session will include identifying
team members, guidelines for effective meetings, stages in
team development (forming, storming, norming, performing),
team member roles and individual styles, and characteristics
of successful teams.
Day 3
VSM (Value Stream Mapping), Current State
Participants will experience a combination of classroom material,
classroom exercises and shop floor observations. Participants
will review the theory and value of VSM and why it serves
as a road map for an organization’s Lean Six Sigma journey.
Included in this topic will be discussion surrounding process
mapping, information flow, material flow, and distribution
methods.
Standard Work
Participants will learn why standard work is a building block
for continuous improvement, how to create it, and how to visually
present it to the associates on the manufacturing floor. They
will be exposed to the forms and the methods needed to collect
elements. There will be a classroom exercise that drives home
the predictable and repeatable process by eliminating method,
machine, and materials variation.
Day 4
Project Charter
Participants will present the Project Charter for their project.
Day 5
Solving Process/Tools
These tools find the root causes of problems. They are tools
for thinking about problems, obtaining data, identifying possible
solutions, and implementing solutions.
Cause-Effect Matrix
This is a simple Quality Function Deployment matrix used to
emphasize the importance of understanding customer requirements.
It relates the key inputs to the key outputs, which can be
derived from Input/Output Mapping. Key outputs are scored
by their importance to the customer and key inputs are scored
by their relationship to key outputs.
FMEA (Failure Mode and Effects Analysis)
Failure Mode and Effects Analysis is a time-proven “bottom-up”
technique for systematically finding failure causes. When
carried out on a process, each process step is investigated
to examine ways in which it could falter or fail and what
countermeasures can be used to prevent it. Participants will
learn the importance and the essential elements of FMEA.
Day 6
Statistical Thinking
This method of thinking about processes is to note that all
work occurs in a series of connected processes; and that one
primary objective of process improvement is reduction of variation
in these processes. Participants will be introduced to statistical
thinking with examples, and will learn how to become “process
thinkers” to reduce variation in their areas.
Sampling Issues
Sampling is the process of evaluating a portion of a population
or process for the purpose of determining the characteristics
of the total population. Issues associated with when to sample
and how to sample will be discussed.
Basic Statistics
Participants will be introduced to the concepts of variability;
stability; measures of the shape, center, and spread of a
distribution; the normal distribution, and graphical techniques
for data analysis.
Day 7
Components of Variance
Multi-vari charts provide a graphical way to examine different
sources of variation. These sources of variance are known
as components of variance. Participants will be shown how
numerical measures of these components can be valuable tools
in process analysis.
Measurement Systems Analysis
Participants will learn the qualities of a good measurement
system, such as good operational definitions, accuracy and
precision. They will also see the problems created by poor
measurement systems, and understand the value of conducting
measurement system analyses.
Correlation & Regression Analysis
When both input and output variables are continuous, these
methods can be used to see whether the input variables can
predict the output. Participants will learn what correlation
and regression is, what it is not, and its importance in process
improvement.
Day 8
Capability Analysis
Participants will learn to measure if a process, when free
of special causes, is capable of meeting customer specifications.
They will also see how this analysis can be used to estimate
defect matrix, and understand the difficulty of conducting
such an analysis on a process for which special causes are
still present.
Control Plans
Participants will see how information collected on key process
variables can be included in a control plan. Examples will
be used to illustrate the technique.
SPC/Control Charts
Every process has variability that becomes evident whenever
a quality characteristic of the product is measured. Understanding
how much of the variability is inherent in the process (common
cause) and how much can be assigned to other causes (special
causes) are the first steps to reducing the variation and,
consequently, lowering waste. Participants will be introduced
to important statistical techniques to identify these sources
of variation.
Day 9
Design of Experiments – Introduction
Control charts and multi-vari charts are excellent tools for
analyses of a current process. Design of Experiments is a
powerful technique to improve processes. Participants will
learn fundamental ideas about experimentation. Through exercises,
participants will design and analyze an experiment. Graphical
techniques will be emphasized.
A two level full factorial experiment is one in which each
factor is studied at exactly two levels and in which all combinations
of factor level are studied. The value of this approach over
standard one-factor-at-a-time methods can be enormous. The
full-factorial approach allows the variability of the process
to be taken into account, while at the same time reducing
its impact and allowing so-called interactions (features of
process complexity) to be measured.
t-tests
When two groups are being compared, a t-test is a technique
to see if the means of the two groups differ. This can be
used as one way to compare two populations, two processes,
or two settings of a process parameter. This method also provides
an entrée to two-level factorial designs.
Day 10
Line and Cell Design
Participants will learn the fundamentals of cell and line
design. They will learn various methods to design work cells,
how to properly resource them, how to “right-size”
equipment, material presentation and how to facilitate operator
movement. Also in this segment we will begin to tie together
the application of other tools, such as standard work, visual
controls and pacing methods.
Kaizen Event Training
Participants will learn how to structure a Kaizen event, including
pre-event preparation, tools and forms to be used, and documentation
methods. From this, they will understand the necessity of
a structured approach to Kaizen and the importance of a Kaizen
that is driven as directed by the future state map.
Project Reports
Participants will present a progress report on their project.
This will be a Power Point presentation highlighting the tools
utilized and progress made for each of the steps in the DMAIC
process. It also is a time to receive feedback from the faculty
and ask questions.
Day 11
Setup Reduction
Participants will learn to breakdown a set-up into four individual
tasks: internal, external, adjustment, and actual set-up.
They will be exposed to examples of techniques used to reduce
and/or eliminate unnecessary activities. Participants will
understand why quick changeovers are critical to key business
metrics such as capacity.
Total Productive Maintenance (TPM)
TPM, or total productive maintenance, is a set of methods
designed to ensure that all machines perform their tasks,
so that the flow of production is not interrupted. Participants
will learn the differences between preventive maintenance
programs and total productive maintenance programs. They will
also learn how to calculate, monitor and improve overall equipment
effectiveness.
Day 12
Kanban
Participants will learn where and when to apply supermarket
concepts, the mathematical calculations for sizing, and a
variety of signaling methods used to signal production. They
will also learn to use in-process Kanbans as start/stop signals
to prevent overproduction. There will be a discussion on how
the role of traditional MRP/ERP systems changes in a pull
environment. Participants will go to the floor with these
tools and report what they observed in existing supermarkets
and the potential enhancements to them.
Day 13
Participants will make a final Power Point report on their
projects. This report should include a discussion of the tools
used and the actions taken for each step in the DMAIC process.
The report also should include analyses of any data and a
work plan indicating any future steps to complete the project.
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Black Belt Training
(14 days)
A prerequisite for the black Belt training is completion
of the Green Belt program or its equivalent. Participants
will be required to complete a project, which likely will
continue beyond the training. These projects frequently return
$50,000 or more in value to the organization, providing an
immediate payoff that more than covers the total expense of
the Lean Six Sigma training.
The following topics will be presented during the Black Belt
training, building on what already has been covered during
the Green Belt training:
Day 1 (1/2 Day)
LSS Black Belt Introduction - Projects
This session focuses on the stages and skills for project
management and includes a brief review of the key elements
of Lean Six Sigma. Participants will learn how to manage a
project during its various stages, prioritize project opportunities,
develop the project charter, prepare a work breakdown structure,
determine the critical path for activity sequencing, identify
resources and requirements, and track performance.
Day 2 (1 Day)
Statistical Inference
Inference is a method by which we try to generalize from the
specific to the more general. Statistical inference incorporates
statistical thinking and methods into this inference to help
ensure that it is sound, and to point out any weaknesses in
making inference. Taking measurements on a random sample of
units from a large population, and generalizing these results
to the population, involves statistical inference.
Hypothesis Testing
A fundamental technique in making broader inferences from
a sample of values involves a hypothesis test. For example,
if a change is made in a process, we would want to know if
the change had any noticeable effect. For example we may want
to test if the mean of some process feature (such as length,
or time to delivery) changed. Because of natural process variation,
this question may be difficult to answer. Hypothesis testing
provides a mechanism for testing this, and related, ideas
in a statistically objective manner.
Participants will learn about types of errors when a decision
is made about a statistical property of a population or a
process. They will learn about the meaning of p-values and
how to use them. They will perform power analysis as a tool
for planning an efficient sample size.
Confidence Intervals
Confidence intervals are, in a sense, an extension of hypothesis
tests. A hypothesis test often tests one particular value—for
example, to see if process mean changed at all, we would test
if the mean change might equal zero. In this example, a confidence
interval is intended to provide a range that includes all
the mean changes that are consistent with the data. For example,
a hypothesis test might find that the mean time to delivery
did change. In a confidence interval, we might claim that
“we are 95% confident that the mean change in the time
to delivery was a decrease of 3 to 5 days.” Participants
will learn how to find confidence intervals in a wide range
of practical situations and what the relationship between
a confidence interval and a hypothesis test is.
Day 3 (1 Day)
Correlation and Multiple Linear Regression
When both input and output variables are continuous, these
methods can be used to see whether the input variables can
predict the output. In multiple linear regression, a number
of inputs can be used to predict the output. Participants
will learn fundamental techniques of regression and how to
apply them in process investigations. They will learn about
confidence and prediction intervals, how to correct problems
with a regression model through transformations, and how to
deal with qualitative variables by using dummy variables.
Day 4 (1 Day)
Project Leadership, Organization Learning and Presenting
Skills
Black Belts are often required to not only lead projects,
but also to increase understanding of Lean Six Sigma throughout
the organization and make presentations. This hands-on session
will introduce the participants with the skills required to
not only be a good leader, but also to be able to develop
PowerPoint presentations and deliver training modules. As
homework, the participants are required to develop a brief
training module.
Day 5 (1/2 Day)
Project Report (Charter)
Participants will present the current status of their projects
using the project template to indicate the tools utilized,
the data gathered and analyzed, and the next steps that are
planned. This also is an opportunity to receive feedback from
the program faculty and to ask questions about the project
and/or tools.
Day 6 (1 Day)
Measurement Systems Analysis (MSA)
Participants will review the qualities of a good measurement
system, such as good operational definitions, accuracy and
precision. They will also analyze data from a number of measurement-system
studies, including the most common studies, gage R&R (repeatability
and reproducibility) studies, and will discuss their plans
for conducting a measurement system analysis for their project.
Components of Variance/Multi-Vari Charts
Multi-Vari charts provide a graphical way to examine different
sources of variation. These sources of variance are known
as components of variance. Participants will analyze a number
of data sets. For each data set they will perform an informal,
graphical, analysis with Multi-Vari charts, and then a formal,
statistical, analysis using a statistical technique known
as analysis of variance, or ANOVA. Participants will also
learn the connection between these analyses and gage R&R
studies, and will learn and use important statistical ideas
such as crossed and nested, and fixed and random, factors.
Reliability Indices
Many MSA’s are performed with continuous data, but when
the data are discrete (such as pass/fail), many standard MSA
techniques can not be used. A method of testing the quality
of a measurement system is introduced for working with discrete
data. Participants will understand how to study discrete data,
how to summarize the quality of the measurements with a measure
called the reliability index (also known as kappa). They will
examine this through a series of data sets that they will
analyze.
Day 7 (1/2 Day)
Project Status Review/Consultation
Day 8 (1 Day)
Design of Experiments
Control charts and Multi-Vari charts are excellent tools for
passive analyses of a current process. Design of Experiments
is a powerful active technique to improve processes. Participants
will review fundamental ideas about experimentation.
Two-Level Factorial Design
A two level full factorial experiment is one in which each
factor is studied at exactly two levels and in which all combinations
of factor levels are studied. The value of this approach over
standard one-factor-at-a-time methods can be enormous. The
full-factorial approach allows the variability of the process
to be taken into account, while at the same time reducing
its impact and allowing so-called interactions (features of
process complexity) to be measured. Participants will learn
key terminology, when and how to design an experiment in an
organization, and how to analyze and summarize data from an
experiment. Both graphical and numerical techniques will be
emphasized. Participant will analyze numerous experimental
case studies, and design and analyze an experiment in a simulated
study.
Day 9 (1 Day)
Two-Level Factorial Design, Two-Level Fractional Factorial
In the early stages of many experiments, the large number
of factors one would like to study precludes the use of a
full factorial design. For example, to study eight factors
each at two levels would require 28 = 256 runs in a full factorial
design. This problem can be solved by using fractional factorial
designs, in which only a carefully selected fraction of the
total number of runs is made. For example, eight factors can
often be studied quite well in only 16 runs. Participants
will learn the idea behind fractional factorial designs, how
to construct these designs, the advantages and disadvantages
of different fractional factorial designs, and how to analyze
experiments from these designs through a number of examples.
Day 10 (1/2 Day)
Training Module Presentation
Each participant will present a training module that he/she
has developed, and will receive feedback from the instructors.
Days 11 and 12 (2 Days)
Two-Level Fractional Factorial, Response Surface Methods
Two-level designs are useful to gain a good understanding
of which factors are important and which factors interact.
Sometimes more detailed information on these factors is needed.
Response surface methods are useful to learn more information
about these factors when they are continuous. Participants
will learn the value of these designs, see the connection
between two-level designs and these designs, learn how to
design response-surface experiments, and how to analyze them.
They will also learn how to make intelligent tradeoffs among
several responses using the method of desirability functions.
Day 13 (1 Day)
SPC/Control Charts
Participants will learn the fundamentals of control charts
for variables (continuous) data and for count data, including
how to set up control charts for their processes. The effect
of size, sampling frequency, and subgrouping will be illustrated
with examples. Alternatives to classical control charts when
productions runs are short, or defects rates are low, will
also be discussed.
Capability Analysis
Participants will learn to calculate metrics for potential
and actual capability of a process from a sample, or from
control charts, for the situation when the process is in statistical
control. The difficulty of conducting such an analysis on
a process for which special causes are still present, or for
a process whose distribution is non-normal, will be discussed.
Day 14 (1/2 Day)
Project Reports
This is the final presentation of the project. Participants’
supervisors are invited to this session. For the presentation,
participants will present the actions taken following the
DMAIC process, the Lean Six Sigma tools that were used, the
data that was gathered and any analyses that were performed,
the improvement strategies that were developed with the resulting
financial benefit, and a plan for any steps that remain to
be taken.
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Program
Delivery
Location
This program may be held either at RIT or at the client’s
facility.
Dates and Times
The dates and times for all activities will be established
based on the client’s requirements and RIT staff availability.
Client will Provide
If the program is held at the client’s organization,
the client will provide a training room suitable for adult
learning equipped with pc/laptop compatible projection system,
standard overhead projector, lab area and equipment (as specified
by the instructor and agreed to by the client and a white
board and markers. One IBM-PC, or compatible, computer and
printer for every two-to-three participants will be required
for at least a portion of the training.
For additional information
contact:
Donald Baker
Director
CQAS
585-475-5070
ddbcqa@rit.edu
Greg Evershed
Director of Business Development
KGCOE
585-475-5442
greg.evershed@rit.edu
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