Summary of the book: Six Sigma: A Complete Step-by-Step Guide: A Complete Training & Reference Guide for White Belts, Yellow Belts, Green Belts, and Black Belts. Useful for understanding, structuring and memorizing the material.
Bulletpoint Summary Six Sigma: A Complete Step-by-Step Guide
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1. Bulletpoints for memorization
2. Process capacility
3. Glossary
Summary Six Sigma Black Belt Certification, Training Manual
– C.S.S.C.
Chapter 1 What is six sigma? P8................................................................................2
Chapter 2 Six sigma history and application P21..........................................................2
Chapter 3 Other process improvement and quality methods P33...................................3
Chapter 4 Lean concepts P43....................................................................................3
Chapter 5 Basic six sigma concepts P60.....................................................................4
Chapter 6 Approaching the problem P84.....................................................................6
Chapter 7 What is a process? P94..............................................................................6
Chapter 8 Quality P113............................................................................................7
Chapter 9 Selecting the right projects P126................................................................7
Chapter 10 Basic six sigma team management P142....................................................7
Chapter 11 Introduction to DMAIC and DMADV P156....................................................8
Chapter 12 Define P169............................................................................................9
Chapter 13 Measure P182.........................................................................................9
Chapter 14 Analyze P206........................................................................................11
Chapter 15 Improve P224.......................................................................................11
Chapter 16 Control P234.........................................................................................12
Chapter 17 Intermediate graphical analysis P243.......................................................13
Chapter 18 Normal probability distributions P274.......................................................13
Chapter 19 Correlation en regression P310...............................................................15
Chapter 20 Non-normal probability distributions P335................................................16
Chapter 21 Hypothesis testing (see examples in book) P372.......................................19
Chapter 22 Sample size (see examples in book) P396................................................23
Chapter 23 Advanced control charts (see examples in book) P417...............................24
Chapter 24 Applying statistics to business applications through six sigma P455.............26
Chapter 25 Introduction to Minitab P469...................................................................26
Chapter 26 Graphs and quality tools in Minitab P495..................................................27
Chapter 27 The stat menu in Minitab P550................................................................27
Chapter 28 Analysis of variance (1-way ANOVA) P565................................................27
Chapter 29 Design of experiments P593...................................................................28
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, Chapter 30 Interactions, multi-level factorials, and creating experiments P623..............29
Chapter 31 Brainstorming and process improvement tools P641..................................29
Chapter 32 Process maps P656................................................................................31
Chapter 33 Value stream mapping P676...................................................................32
Chapter 1 What is six sigma? P8
Six sigma is a statistical representation for what many experts call a “perfect” process.
Technically, in a Six Sigma process, there are only 3.4 defects per million opportunities.
For most organizations, Six Sigma processes are a constant target. Achieving and
maintaining Six Sigma “perfection” is difficult and requires continuous process
improvement. But even advancing from lower levels of sigma to a four or five Sigma
process has a drastic impact on costs and customer satisfaction.
Common six sigma principles are:
1. Customer-focused improvement
2. Continuous process improvement
3. Variation reduction
4. Removing waste
5. Equipping people
6. Controlling the process
Challenges of six sigma are:
1. Lack of support
2. Lack of resources or knowledge
3. Poor project execution
4. Data access issues
(# of opportunities - # of defects) / # of opportunities * 100% = % yield
Chapter 2 Six sigma history and application P21
Six sigma is based on the normal curve. A process in need of correction is one that is
performing at three sigma. Control charts help organizations maintain improved
performance after a six sigma project.
Improvement in six sigma is guided by the PDCA cycle. Improvement comes when you
recognize a need for change and plan to improve. Next, you do something to test your
ideas. You check if test improvements are working. Then you act, bringing your
2
,improvements into broader practice. Then you start over, which generates continuous
improvement.
Foundations of lean six sigma are:
1. Defining customer values
2. Identifying the value stream for customer needs and desires
3. Identifying waste in the process
4. Creation of a continuous process flow
5. Continually working to reduce the number of steps and time it takes to reach
customer satisfaction
There are some misconceptions of six sigma:
1. Six sigma is solely concerned with statistics and ignores common sense
2. Six sigma is too expensive
3. Six sigma can fix anything
Chapter 3 Other process improvement and quality methods P33
Some other quality methods exist with a similar purpose: serve a customer a product or
service they need while making as much profit as possible.
1. Lean process management (reduce waste – goes together with six sigma)
2. Total quality management (quality focus on enterprise level – came before six
sigma)
3. Business process reengineering (radical change with rigorous testing and change
management)
4. Rummler-Brach (performer/process/organization vs. management/design/goals
matrix)
5. Scrum (agile and quick programming through sprints)
6. The customer experience management method (outside-in approach, processes
translated to face the customer)
7. JumpStart (quickly resolve small-scale problems through brainstorming)
Six sigma should be chosen as a method when:
1. Facing the unknown
2. Problems are widespread and not defined
3. Solving complex problems
4. Costs are closely tied to processes
Chapter 4 Lean concepts P43
Lean and six sigma are often used together. There is a distinction between defects
(customers aren’t satisfied) and waste (unnecessary processing). There are multiple types
of waste:
1. The seven muda
a. Overproduction (too much/early production)
b. Correction (rework because of mistakes)
c. Inventory (excess working capital)
d. Motion (too many people movements)
e. Conveyance (too many product movements)
3
, f. Overprocessing (using more resources than valued by customer)
g. Waiting (idle time for machinery or people)
2. Other waste
a. Talent (people not utilizing their skills)
b. Ideas (not acting on potential improvements)
c. Capital/cash (that could be invested)
Some types of waste are actually essential due to for example regulations (type 1 muda).
Others can be immediately removed (type 2 muda).
Inventory can be reduced by just-in-time manufacturing. Previously, this meant that items
were produced when needed, so upon request. Nowadays companies make predictions to
determine when just in time is going to be. JIT is not very strict, but its principle helps to
eliminate waste.
Chapter 5 Basic six sigma concepts P60
Standard deviation for population data:
1. Calculate the mean
2. Subtract the mean from each value and square the single result
3. Calculate the mean of the squared values (variance)
4. Calculate the square root of the new variance
Standard deviation for sample data: divide by N-1 to compensate less accuracy
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