ASQ Six Sigma
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Transcript of ASQ Six Sigma
Workshop on Structured Problem Solving Using DMAIC Methodology
Agenda
Day 1:
TQM
Introduction to Six Sigma
Define Phase
Project Charter
Day 2:
Seven QC Tools
Process Mapping
Day 3:
FMEA
Process Capability
Control Charts
Day 4:
Lean Enterprise
Day 5:
VSM Exercise
NTPC Case Study
Exam & Wrap Up
The Evolution of Quality
• Provides a framework for understanding the history of the quality movement.
• Expands the definition of quality.
Juran’s Definition of Quality
Defined as “fitness for use” based on:• Customer’s perceptions of product design.• Degree to which a product conforms to
design.• Product’s availability, reliability, and
maintainability.• Available customer service.
ISO Definition of Quality
• Degree to which a set of characteristics fulfills requirements
Requirements:Convenience and speed
Product:Telephone
Characteristic:Speed dial
Crosby’s Definition of Quality
• Quality is conformance to requirements.• Requirements are answers to key
organizational questions:
– How quickly will orders ship?– What is our return policy?– What forms of payment are
acceptable?
Quality Evolution: Medieval Guilds
Guilds: Developed strict rules for
products and services. Used stamps to identify
flawless goods.
Y ea r a n d P er io d1200-1799 1 9 0 0 -1 9 4 0 1 9 4 6 -P re se n t1 8 0 0 -1 8 9 9 1 9 4 1 -1 9 4 5G u ild s o f
m ed ieva l E u rop eP ro d u c t
o rie n ta tio nP ro c e ss
o rie n ta tio nQ u a lity d u rin gW o rld W a r II
B ir th o fto ta l q u a lity
Quality Evolution: Product Orientation
Master craftsmen trained apprentices.
Industrial Revolution divided trades into specialized tasks; inspectors guaranteed quality.
Taylor system increased productivity; inspection departments found defects.
Y ea r a n d P er io d1 2 0 0 -1 7 9 9 1 9 0 0 -1 9 4 0 1 9 4 6 -P re se n t1800-1899 1 9 4 1 -1 9 4 5G u ild s o f
m e d ie v a l E u ro p eP rod u ct
or ien ta tionP ro c e ss
o rie n ta tio nQ u a lity d u rin gW o rld W a r II
B ir th o fto ta l q u a lity
Quality Evolution: Process Orientation
Processes became critical. Shewhart identified statistical
quality control. Developed strict rules for
products and services. Quality became relevant for
process, not just product.
Y ea r a n d P er io d1 2 0 0 -1 7 9 9 1900-1940 1 9 4 6 -P re se n t1 8 0 0 -1 8 9 9 1 9 4 1 -1 9 4 5G u ild s o f
m e d ie v a l E u ro p eP ro d u c t
o rie n ta tio nP rocess
or ien ta tionQ u a lity d u rin gW o rld W a r II
B ir th o fto ta l q u a lity
Quality Evolution: Wartime
Quality became a safety issue.
The military developed a sampling inspection system and trained suppliers.
Y ea r a n d P er io d1 2 0 0 -1 7 9 9 1 9 0 0 -1 9 4 0 1 9 4 6 -P re se n t1 8 0 0 -1 8 9 9 1941-1945G u ild s o f
m e d ie v a l E u ro p eP ro d u c t
o rie n ta tio nP ro c e ss
o rie n ta tio nQ u ality d u r in gW orld W ar II
B irth o fto ta l q u a lity
Quality Evolution: Total Quality Movement
Developed in response to Japanese quality movement.
Focused on improving all processes through people who used them.
Y ea r a n d P er io d1 2 0 0 -1 7 9 9 1 9 0 0 -1 9 4 0 1946-P resen t1 8 0 0 -1 8 9 9 1 9 4 1 -1 9 4 5G u ild s o f
m e d ie v a l E u ro p eP ro d u c t
o rie n ta tio nP ro c e ss
o rie n ta tio nQ u a lity d u rin gW o rld W a r II
B irth o fto ta l q u a lity
W. Edwards Deming
Quality keys:• Understanding
customer needs• Process
improvement• Statistical analysis• Expertise of workers• PDCA cycle
Joseph M. Juran
Quality keys:• Features that
satisfy customers• Freedom from
deficiencies• Juran Trilogy®
– Quality planning– Quality control– Quality
improvement
Kaoru Ishikawa
Quality keys:• Company-wide
participation• Quality control circles• Advanced statistical
methods and tools• Nationwide quality
control promotion
Armand V. Feigenbaum
Quality keys:• Total quality control• Integration of quality
development, maintenance, and improvement
• Focus on internal and external customers
Genichi Taguchi
Quality keys:• Quality should be
designed in.• Quality should
minimize deviations from a target.
• DOE optimizes performance.
Philip Crosby
Quality keys:• Conformance to
requirements• Prevention• Zero Defects• Price of
nonconformance
Total Quality Management
Total quality management (TQM):
• A management approach
• Centered on quality
• Based on company-wide participation
• Aimed at long-term success
• Through customer satisfaction
3 Cs of TQM
Customer relationships
Continuous improvement
Company-wide participation
1
2
3
Customer Definitions
1
P u ck er U p L em on ad e , In c .
In tern a l C u sto m ersL oad in g D ock
B ottlin g D ep artm en tM ix in g D ep artm en t
S ortin g D ep artm en tJu ic in g D ep artm en t
S ortin g D ep artm en tJu ic in g D ep artm en tM ix in g D ep artm en t
E x tern a lC u sto m ers
C on su m ers
Levels of Customer Satisfaction
Noriaki Kano identified threelevels:• Expected quality• Desired quality• Excited quality
1
Customer Feedback
1
Has two parts: Efforts to capture
what customers say about company’s
products/services Efforts to drive
feedback back intoorganization
Partnering with customer: Extension of
listening to customer feedback Most direct route to
customer satisfaction
PDCA
• A well-known model for continuous process improvement is the Plan-Do-Check-Act cycle.
2
P la nA ct• A n a ly ze rea so n
fo r n o t m a k in gd esired resu lts .
C h eck D o
• W h a t to d o .• H o w to a cco m p lish it.
• C a rry o u t th e p la n .• S ee if th e d es ired resu ltsw ere o b ta in ed .
• D eterm in e w h a tch a n g es to m a k e tob etter a ch iev e d esiredresu lts .
• S ta n d a rd ize if d esiredresu lts a ch iev ed .
3
Company-Wide Participation
• Leadership must come from management.• All employees must be involved.• Employee involvement usually requires
employees to work in cross-functional teams.
Employee Involvement
Benefits• Improved
productivity and cost reduction
• Increased participation and job satisfaction
• Opportunities for professional development
Barriers• “It Won’t Work
Here”• Perception of loss
of management authority
• Employees feeling “used”
• “Flavor of the month”
3
Quality Benefits
• Tangible– Increase in
earnings– Decrease in
waste– Increase in
productivity
• Intangible– Customer
goodwill– Alignment
between business activities
W. Edwards Deming on Quality
• Meeting customer needs + wants = quality.
• Quality improves products/services and processes.
• Improved products/services and processes = profitability.
A Quality Approach Benefits . . .
Employees Organizations
Suppliers Society
Customers
Benefits to Employees
Product quality
Greater job security/benefits
Process quality
Profit
Customer satisfaction
Pride in products andservices
Job satisfaction
Improved communicationsStreamlined work processesHappier customersStrong customer
relationships
Benefits to Organizations
Q u a lity
O rg a n iza tio n s
C o st
M a rk etS h a re
P ro fit
Quality Studies and Standards
Released the Profit Impact of Market Strategy (PIMS) study.
Partnered with the Baldrige recognition program.
Both organizations support the link betweenquality and profitability.
Strategic PlanningInstitute
National Institute ofStandards and
Technology
External and Internal Customers
PublicationDepartment
SalesDepartment Customer
Benefits to Customers
Quality results in:• Increased choices.• Improved goods
and services.• Expectations met or
exceeded.
Benefits to Suppliers
• Achievement of performance requirements
• Streamlined processes
• Efficient communication
• Increased customer satisfaction
Benefits to Society
Economic growth and stability
Increased employment opportunities
Product safety
Process Management
Quality improvements are applied to single processes within manufacturing.
Quality improvements are applied to all organizational activities through process management.
Before TQM
After TQM
Organizational Process
P ro cess
• P eo p le• E q u ip m en t• M a ter ia l• M o n ey• T im e
R eso u rces
In p u t O u tp u tD
PC
P reced in gP ro cess
S u b seq u en tP ro cess
C u stom er In flu en ce
Introduction to Six Sigma
What is Lean Six Sigma?Introduction
• Six Sigma goal is process perfection through defect reduction.
• Lean goal is cycle time reduction through elimination of waste.
“Only those companies that eliminate their defects will have what it takes to win.”
“Breakthrough companies strive for 100 percent DEFECT-FREE products and services.”
Larry Bossidy
CEO of AlliedSignal
“Only those companies that eliminate their defects will have what it takes to win.”
“Breakthrough companies strive for 100 percent DEFECT-FREE products and services.”
Larry Bossidy
CEO of AlliedSignal
What is Six Sigma?Methodology and Improvement Strategy
• Six Sigma is an overall strategy to accelerate improvements in processes, products, and services–create breakthrough.
• Six Sigma measures how effective strategies are in eliminating defects and variations from processes, products, and services.
=
Y
+
x3 …)x2,
+ ...+
f(x1,
Process output (Y) is a function of (f) the inputs (Xs). Understanding and controlling this relationship is a major aspect of Six Sigma projects.
Focus on Variation• Sigma (σ) refers to standard deviation, a measure of process
variation (smaller is better).• Process Sigma is the number of units of standard deviations
between the process center and the closest specification limit (larger is better).
• A Six Sigma process has six standard deviations (short term) between the target and the closest specification limit.
6 Sigma
UpperSpec
LowerSpec
6 Standard Deviations
Target
UpperControl
LowerControl
Process Center
Sources of Variation
$ Process Capabili
ty
Measurement System
Material
Design
Harvesting the Fruit of Six Sigma
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Sweet Fruit Design for Manufacturability
Bulk of FruitProcess Characterization and Optimization
Low Hanging FruitSeven Basic Tools
Ground FruitLogic and Intuition
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
3 s Wall - Demand improvement3 s Wall - Demand improvement
4 s Wall - Must Improve Internally4 s Wall - Must Improve Internally
5 s Wall - Must Address Designs5 s Wall - Must Address Designs
The walls crumble faster when working WITH suppliers and CONCURRENTLY addressing design and process issues
Discretedata
The Focus of Six Sigma
· Y· Dependent· Output· Effect· Symptom· Monitor
· X1 . . . XN
· Independent· Input-Process· Cause· Problem· Control
f (X) Y
Would you control shooter or target to get the Gold Medal at Olympics
Six Sigma Defines Problems Statistically
Y - Outputs Dependent Output Effect Symptom Able to
Monitor
X1 . . . XN - Inputs
Independent Inputs,
process Cause Problem Controllable
The product is used to evaluate the process.
Y= f (X) Should we focus on the process outputs (Y) or inputs (X)?
The process is used to control the product.
20,000 lost articles of mail per hour
Unsafe drinking water for almost 15 minutes each day
5,000 incorrect surgical operations per week
Two short or long landings at most major airports each day
200,000 wrong drug prescriptions each year
No electricity for almost seven hours each month
Seven articles lost per hour
One unsafe minute every seven months
1.7 incorrect operations per week
One short or long landing every five years
68 wrong prescriptions per year
One hour without electricity every 34 years
99.99966% Good (6 Sigma)99% Good (3.8 Sigma)
Define Phase
The Define Phase
The define phase module provides an
overview of the following tools:
1. Project selection
2. Project charter
3. Supplier, Input, Output, Customer (SIPOC)
diagram
4. Collecting Voice of the Customer (VOC)
Projects Must be …
Sorting Projects from Messes
• A mess is a morass of unsettling
symptoms, causes, data, pressures,
shortfalls, opportunities, etc.
• A problem is a well-defined situation that is
capable of resolution
• Identifying a problem from within the mess
is frequently the first step in the process of
project definition
Project Qualifications
• There is a gap between current and desired
performance.
• The cause of the problem is not clearly
understood.
• The solution is not predetermined.
Project Selection is Critical• High leverage projects lead to largest $$ Savings• Large returns justify the investment in time and
effort • Developing a Lean Six Sigma culture depends
upon successful projects having significant business impact
• Black Belt training depends on completion of a meaningful project within ~ 6 months
• Future Projects are frequently identified through initial projects
Lean Six Sigma Project Criteria
• Aligned with business objectives and plans
– Voice of Customer/ Critical to Satisfaction (CTS)
– Quality (CTQ) / Cost (CTC) / Delivery (CTD)
• Consistent with principles of Six Sigma
– Elimination of process defects
– Reduction of variation
• Concentrates on significant issues/opportunities
..... not “problem of the day”
• Justify the investment
Project Selection
“The best Six Sigma projects begin not inside the business but outside it, focused on the question — how can we make the customer more competitive? What is critical to the customer’s success? … One thing we have discovered is that anything we do to make the customer more successful inevitably results in a financial return to us.”
Jack Welch
Address to the General Electric annual meeting April 23, 1997
What is Customer Satisfaction?
• A comparison of expectation to experience
• A matter of degree• A result of a good match between
supply and demand• A predictor of repeat business
Y
• Projects are identified by the relationship between product, service, or deliverable requirements and processes.
• The process parameters that affect the requirements
are later identified (X1 , X2 , … Xn)
Customer needs are translated into product, service or deliverable requirements in terms of quality, delivery and cost. The “Y” of Y=f(X).
• Leverage processes are identified.
Breakdown ofthe processes
required toproduce the
product,service, ordeliverable.
Customer Needs Translated into “Critical To” (CT) Characteristics
Typical Critical to Characteristics
CTQ Critical to Quality
CTD Critical to Delivery
CTC Critical to Cost
S. No.
Criteria Weight
1 Aligned with core objectives 10
2 High probability of success 10
3 Data Availability 8
4 Pain area 8
5 Process Improvement 7
6 Higher returns 8
7 Repeatable 6
8 Faster Deployment 5
9 Stakeholder Satisfaction 7
10 Ease of implementation 6
Aligned with
core objectives
High probability of success
Data Availability
Pain area
Process
Improvement
Higher
returns
Repeatable
Stakeholder Satisfaction
Ease of
implementation
Faster
Deployment
Project Selection Criteria
S. No.
CriteriaProject 1 Project 2 Project 3 Project 4 Project 5
APC Reduction in stage I
Boiler (Stage II) Optimization
DM (Stage I) Make up Optimization
ESP (Stage I) Inlet Duct Replacement
Soot Blowing Sy.Optimization
1 Aligned with core objectives
2 High probability of success
3 Data Availability
4 Pain area
5 Process Improvement
6 Higher returns
7 Repeatable
8 Faster Deployment
9 Stakeholder Satisfaction
10 Ease of implementation
Strong Relationship Moderate Relationship Weak Relationship
Project Selection Matrix Diagram
Factors that Improve Project Success
• Dedicated Black Belt• Champion phase reviews• Black Belt has knowledge of
process/product to be improved• Historic data• Clearly defined deliverables • Committed process owners (skin in the
game) with the authority to modify the process
8
Project Metrics – Success CriteriaPrimary Metric • Used to measure project success• Consistent with the problem description and objective• Plotted on a time series graph and shows the goal and actual
performance lines
Secondary Metric(s)• Control unintended negative consequence (assures the Primary
Metric is not achieved artificially)• May be used to measure project progress when the Primary Metric
responds slowly • More than one may be required• Plotted on a time series graph and shows the goal and actual
performance lines
Project Charter
Traditionally created by LSS Champion
Specifies details of a project including:1. Scope
2. Responsibilities
3. Benefits
4. Schedule
5. Success criteria
A project charter template that may be adopted to fit your organization is: Project Charter Template.
SIPOC
Supplier, Input, Process, Output, Customer diagrams are used to:
1. Define the scope of the project
2. Identify key stakeholders
3. Gain a “30,000 foot” view of the process targeted by the project
Tips:
4. The SIPOC is the first of several ways the process will be documented. Therefore, it should be at a relatively high level of abstraction.
5. It is a good way to assure agreement on the scope of the project.
SIPOC Diagram – Questions to Answer
• Who are the customers of this process?• What are their requirements?• How are those requirements reflected in the
process parameters (output measures)?• What are the process outputs?• What are the process inputs that cause the
outputs?• What controls are in place for the inputs?• Who are the suppliers of the material for this
process?• What are their requirements?
Purpose of Various Diagrams / Maps
• SIPOC diagrams provide a “forest view” of the process – maintains focus on the customer’s requirements.
• Value stream “trees level” describes the time, effort, resources, and information used in the process – a frequent source of early wins.
• Lay-out diagram (spaghetti diagram) documents the distance an item travels during its production – illustrates unnecessary movement.
• Process map “ground level” documents the inputs and outputs of each step in the process – provides the raw material for building a model of the process.
The SIPOC Diagram – The Forest Level
• Start with the end in mind.• Who are the customers of this process?• What are their requirements?• How are those requirements reflected in the
process parameters (output measures)?• What are the process outputs?• What are the process inputs that cause the
outputs?• What controls are in place for the inputs?• Who are the suppliers of the material for this
process?• What are their requirements?
Sample SIPOC
Supplier(s) Inputs/Req'ts Process Output(s)/Req'ts Customer(s)
Grocery storeUtility CompanyAppliance store
Coffee machineMeasuring cupElectricityQualified operatorWaterFiltersCream/milkSweetenerGround coffee
1800
Specified number of cupsNo grounds< one hour oldDarkHotAromaticFreshStrong
HusbandWifeGuest
Install filterMeasure coffeeAdd coffeeAdd WaterTurn on machine
SIPOC Validation
Review the SIPOC with your: team,
Champion and process owner(s) to assure
agreement on the SIPOC content as well
as the project scope and success criteria
among all stakeholders.
IISS PP OO CCSuppliers Inputs Process Outputs Customers
Coal Field
Rihand Dam
Suppliers
Power
Effluent
Process Ash
Steam
CO2
InternalInternal
-Plant Mgmt
-Corp Mgmt
-Employee
ExternalExternal
-Cent.Gov.
-Ministry
-State Gov.
-Shareholders
-Contractors
-Suppliers
-PAPs
-Labour
EnvironmentEnvironment
CTQs
Plant Availability
UI Earned
Plant Load factor
Maintenance Cost
AUXILLIARY POWER-
CONSUMPTIONPreferred Employer
R&R
Man : MW Ratio
Lead Time
Heat Rate
Quality System
Social Responsibility
Manpower Utilization
Overhead Expenses
ENERGY EFFICIENCYDM Water Used
Safety aspect
Training of manpower
Cycle Time
In process idle stock
Air Emission quality
Noise level
COALCOAL
AIRAIR
WATERWATER
Boiler
STEAMSTEAM
TurbineGenerator
GRID
Coal
Water
Air
Power
Manpower
Lubricants
Maintenance
Services
Spares and
Consumables
Collecting VoC
• Who is a customer?
• What does the customer need?– Gathering the Voice of the Customer
– Define customer requirements
• How do the customers prioritize their needs?
• How are customer needs translated into CTQs?
Generally a less intense exercise for DMAIC projects than for DFSS projects
More likely to be based on information that is already available internally for DMAIC projects than for DFSS projects
Process
Voice of Customer
Step Step Step Product/Service
Customer
Who Is a Customer?
A customer sets/affects requirements for your product or service.• External• Buying customers• End-users • Regulatory agencies
A customer is one who receives your output.• Internal
Customer Segmentation
• Generally, external customer needs are more important than internal customer needs.
• Are all customers equally important?–External vs. internal–Customer segments
• Regions• Type of business• Volumes• Profitability• Strategic market• Future potential
Voice of the Customer
• The Voice of the Customer (VOC) is the
starting point of any project and data
collection plan.
• The Voice of the Customer includes:
– Expectations
– Requirements
– Opinions
Questions to Find Voice of the Customer
• What are the elements of your business that are
the most critical, from the perspective of your top
or best customers? What are their relevant
needs?
• What data has been collected to understand the
customer requirements?
• How do you operationally define the defect from
the perspective of the customer? Under what
conditions does it occur?
Voice of the Customer Concerns
• Real vs. stated needs
• Perceived needs
• Intended vs. actual usage
• Internal customers vs. external customers
• Effectiveness vs. efficiency needs
• Change over time
Determining Customer Requirements
• Use verbatim comments from customers to
help determine the key customer
requirements
– We often receive many verbal comments from
our customers.
– We need to look for ways to probe for deeper
meaning behind the comments in order to
translate these comments into what the
customer actually requires.
Tools for Gathering Voice of the Customer
Unsolicited data from customers – Complaints– Field reports– Trade journals– Benchmarking– Internal research
• Requirements documents• Contracts• Customer observation• Be a customer
Tools for Gathering VOC
Solicited data from customers
– Interviews
– Focus groups
– Surveys
– Informal customer discussions
– Market research
Determining Customer Requirements
• Review customer verbatim comments and
comparative data
• If possible, probe for deeper understanding
• Convert into terms of process performance
• Describe the actual customer requirement
– Write the requirement, not the solution
– Use measurable terms
– Identify performance targets
– Be concise
Define Phase Review
• The purpose of the define phase is to identify and
launch a project.
• VOC should be reflected in the project charter
especially in the project success criteria.
• The Black Belt and Champion should review and
agree on the details of the project charter and
SIPOC.
• A common cause of project failure is poorly
defined or projects with excessive scope. This
review is an opportunity to mitigate that risk.
D M A I CVOC ( Voice of Customer )
Customer NeedCustomer NeedsAux Power Consumption
Generation & Dispatch
Environmental Pollution
Conservation of CoalWH
AT
?
Ran
king
( 1
-5 )
Impr
ove
Proc
esse
s
Arre
st P
ro.D
evia
tion
Bette
r Sy
stem
s
Repl
ace
with
eff.
pro
Wor
se
Sam
e
Bet
ter
RATING
HOW ?Competitor
554
4
5 5 4 44 5 4 24 5 4 4
5 5 2 5
81 90 64 66
D M A I C
Project Charter
Big Y:
Reduction in APC of Stage-I units
Reduction in APC of Stage-I units
Project Review DatesChampion:
Process Owner:
Process Owner:
Quality Leader
Coach (BB):
Green Belt:
Resource Plan General InformationTollgate Date Signoff
(xx/xx/xx)
Green Belt Contact Information :
Define
Measure
Analyze
Improve
Control
Mohit YadavMr. S. Banerjee
Mr. P.K.MohapatraMr. N.N.Mishra
Iswar BMDIswar BMD
Ashish Jain EMDAshish Jain EMDS. Sinha TMDS. Sinha TMD
V. Agarwal EEMGV. Agarwal EEMG
Mohit Yadav 94258232991550
Mohit Yadav 94258232991550
YesYes
YesYes
YesYes
YesYes
YesYes
Project Team Rhythm and ReviewMeeting Frequency:
Mandatory Attendees:
Optional Attendees:
15 Days15 Days
Mohit YadavMohit Yadav V. Agarwal V. Agarwal Iswar Iswar
Mr. P.K.MohapatraMr. P.K.Mohapatra Mr. N.N.MishraMr. N.N.Mishra Mr. N.K.SinhaMr. N.K.Sinha Mr. S. BanerjeeMr. S. Banerjee
Rhythm and Review: On-Track
Off-TrackNeed Attention
05/02/0705/02/07
05/04/0705/04/07
15/04/0715/04/07
31/05/0731/05/07
31/08/0731/08/07
D M A I C
Mr. N.K.SinhaMr. S. Mathew
S. SinhaS. Sinha A. JainA. Jain
VOC ( Voice of Customer )
The Seven QC Tools
Check sheet Stratification Pareto diagram C &E Diagram Histogram Scatter diagram Graphs and Charts
Problem Solving
Continuous Improvement-- Kaizen
Dispersion Control-- Six Sigma
Waste Elimination--Lean
QMS, EMS, TS 16949, OHSAS-Process control, C&P
Supplier Development
Project Management--Team working
Area of Uses
What is their role ?
In problem solving
Tool
Data gathering
Check sheet
Stratification
Role they Play
Quantify current status
or magnitude of the
Problem
Facilitate data gathering
Identify and segregate different sources of the problem
Role
Tool
• Pareto diagram
• Brain storming
• Cause & effect diagram
Role they Play
• Prioritize the problem
• Generate many ideas for solving a specific problem
• Identify possible causes of a problem in a structured way
Role
Tool
• Histogram
• Scatter diagram
• Graph & chart
Role they Play
• Study pattern of variation in a set of data.
• Study relationship between 2 types of variable
• Visual display of data
Role
DATA GATHERING
Data Collection
What is Data ?
Data is a numerical expression of an activity
Conclusions based on facts and data are necessary for any improvement.
K. Ishikawa
If you are not able to express a phenomenon in numbers, you do not know about it adequately
Lord Kelvin
Types of Data
Quantitative Qualitative
• Measurable e.g. :Length, Temperature
• Countable e.g. :Number of
defects
• Subjective assessment e.g. :Score in a beauty
contest
Population Sample Data
Action
Action
X
Population, Sample and Data
Random
Sampling
Measurement
/ Observation
A Saying When you see the data, doubt it When you see the measuring instrument, doubt
it. When you see the chemical analysis, doubt it. Three Categories
1 False Data
2 Mistaken Data
3 No Data available
How to Collect Data?
Define the purpose (Follow 5W 1H approach). Define the period for data collection. Define the Stratification. Design the check sheet and assess Measurement
System Capability.Purpose
Be Clear on What, Where, When, Why, Who and How the data should be generated
STRATIFICATION
Stratification
Method of grouping data by Common points or characteristics
A Filtration Process for isolating the cause of a problem.
Prevent mix up and helps in easy & faster identification-
Basis for Stratification
Workers Material
Machines Time
Defect Environment
Product Folder
RegionFiles
Machine A
N = 450D = 12P% = 2.7
Machine B
N = 450D = 1118P% = 26.2
Machine A
N = 450D = 12
P% = 2.7
Machine B
N = 450D = 118
P% = 26.2
COMBINED
N = 900D = 130
P% = 14.4
Blister Defect
Pinhole Defect
All Defects
UCL
CL
UCL
CL
UCL
CL
CHECKSHEET
Check sheet
A convenient and compact format
for data collection
A Simple rule– Maximum
information with minimum writing
efforts and easy to fill
105
M/C No.
Comp.
DRG. No
Token No.
Op.
Qt. Prod.
Material Defect
1 2 3 4 5 6
No. Insp.
M/c Defects
A B C D………P Q R
Total
Remark
Check Sheet For Machining Operation
Location
Machining DefectMaterial Defect
Group Date Shift
1: Blow holes2: Cracks3: Hard Metal4: Eccentric5: Others6: Total
A: Dia.+ G: Length+ M: OblongB: Dia.- H: Length - N: TaperC: Ch+ I: Sp+ O: Hole ShiftedD: Ch- J: Sp- P: PCDVE: CDV+ K: D& T Size+ Q: Poor FinishF: CDV- L: D & T Size- R: Others
Graphs & Charts
Line chartBar chartMultiple bar ChartComponent bar
ChartRadar chart
Pie chart Gantt chart Pareto diagramScatter diagramControl chart
Graphs represent data pictorially. A picture can see what 1000 words can not tell.
Bar Chart
Bar graphs are parallel bars of identical width but differinglength to compare size of different quantities / things.
Line Chart
Line graphs manifest the overall trend in time series data by direction of their lines.
Pie charts makes it easy to grasp the breakdown of the components of a quantity over a certain period.
Pie Chart
Comparison of Machines A & B for weekly Rejection
11
5
10
21
23
10
43
13
20
14
11
68
13
20
15 15
11
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Week Number
% R
ejec
tion
263 285201
435
133
375 321 307 294 348
244336
221
257
275
422
281 317 299
358
0
100
200
300
400
500
600
700
800
900
1 2 3 4 5 6 7 8 9 10
Week Number
Uni
ts P
rodu
ced
Comparison of Machines A & B for Units Produced
Multiple bar chart
Component bar chart
Pie Chart for Customer returned watches
• A – Glass Broken
• B - Stop
• C - Mvt. Trouble
• D - Defective Dial
• E - Regulation
• F - Stem Loose
• G - Others
A43%
B27%
C12%
D6%
E4%
F3%
G5%
Control Chart
X- Bar and R Chart
252015105Subgroup 0
2854
2849
2844
Sa
mp
le M
ea
n
Mean=2849
UCL=2853
LCL=2844
15
10
5
0Sa
mp
le R
ang
e
R=7.76
UCL=16.41
LCL=0
Xbar/R Chart for C1
0
10
20
30
40
50
60
70
801
2
3
4
5
6
7
8
9
1011
12
13
14
15
16
17
18
19
20
Series1
Radar Chart on ISO 9001-1994 Implementation
Type of work 1 2 3 4 5 6 7 8 9 10 11 12
Foundation work
Frame work
Dry-walling
Exterior touch up
Sheetrock work
Plumbing
Electrical wiring
Fit Fixtures
Paint interior wall
Interior touch up
Inspection delivery
Gantt Chart for Construction ActivityWeeks
Gantt Charts makes it easy to understand the
details of a plan and progress in its
implementation schedule.
Pareto Diagram
Vital few from Trivial many
41.7
60.7
76.8
87.594.6 100
0
10
20
30
40
50
Fish notfresh
Vegetablewilted
BreadStale
CashierRude
Meat notFresh
Eggs rotten
No.
of
com
plai
nts
0
10
20
30
40
50
60
70
80
90
100
Cum
Per
cent
age
Pareto Analysis of Customer Complaints
Pareto Principle
80% of problems are caused by less than 20% of probable causes
Establishes proof of the need
Identifies vital few
PARETO ANALYSIS: Outstanding branch wise
BRANCH BRANCH Rs. DUE RATIO TO TOTAL
CUM. %
A= 5.0
B= 2.5
C=10.0
D=20.0
E=45.0
F=1.5
G=1.0
H=1.5
Oth.=0.5
E
D
C
A
B
F
H
G
OTHERS
45.0
20.0
10.0
5.0
2.5
1.5
1.5
1.0
0.5
51.7
23.0
11.5
5.7
2.9
1.7
1.7
1.2
0.6
51.7
74.7
86.2
91.9
94.8
96.5
98.2
99.4
100.0
87.0 TOTAL 87.0 100.0
Pareto Analysis on Outstanding
51.7
74.7
86.291.9
94.8 96.5 98.2 99.4 100
0
10
20
30
40
50
E D C A B F H G O
Out
stan
ding
Val
ue
0
10
20
30
40
50
60
70
80
90
100
Cum
Per
cent
age
Branches
Pareto Diagram for Production Stoppage
A. M/C quality change
B. Intermediate conveyor
C. Power failure
D. Hopper/duct line jamming
E. Dryer drum coupling pin
F. B P full press problem
G. Dryer preventive
H. Nip roller
I. Rotary comb tripped
J. Comber jamming
K. Al conveyor idle roller
L. Fire
M. Accumulation
N. Drum seal changing
O. Fan tripping
P. Chain problem
Q. Fiber jamming
R. Zone gear box
S. Zone conveyor
0
5
10
15
20
25
30
35
40
45
A B C D E F G H I J K L M N O P Q R S
No.
of s
topp
ages
0
10
20
30
40
50
60
70
80
90
100
Cum
ulat
ive
%
Pareto Analysis of Complaints at a Laundry
35
60
75
8593 98 100
0
20
40
60
80
100
120
140
160
180
200
Latedelivery
Missing orwrongitems
Fadingcolours
Stains Creased ButtonsMissing
Stretchedor torn
No.
of
com
plai
nts
0
10
20
30
40
50
60
70
80
90
100
Brain Storming
generating large number of ideas by a group of people
Basic Rules
Defer evaluation
Fantasize freely
Generate quantity
Build on ideas
Defer Evaluation
Put critical faculties in cold storage- even constructive criticism.
Ensure a proper climate for acceptance of all sorts of ideas.
No idea should be treated as stupid.
Fantasize Freely
Don’t operate with your brakes on.
Participants are encouraged to generate ideas, no matter how fanciful they are.
Generate Quantity
Generate as many ideas as possible.
A pearl diver will be more successful in finding pearls, when he brings up 200 oysters than when he surfaces only 15-20 oysters.
Build on ideas
Idea of one participant is more effectively built up by another participant.
Steps in Brainstorming
Select the topic
Each member, in rotation gives ideas
Member offers only one idea per turn, regardless of how many he or she has
Continue till all ideas are exhausted
Ideas are recorded and displayed
Benefits
Individual is limited in generating ideas and group produces more ideas
Ideas are improved upon by members
Presence of others increases creativity
Pooling of ideas and resources is made possible by coming together as a group
CAUSE AND EFFECTDIAGRAM
Graphic tool to represent relationship between an effect and influencing causes
There can not be an effect without a cause.
Reduce incidence of subjective decision making.
Identify main causes X’s influencing Y
C & E Diagram
Construction of C & E Diagram
Define problemGather members for discussionConduct BrainstormingGroup causes into 4M’sMan, Material, Machine, MethodFor each cause, ask, “What goes wrong
that produces the effect”.Identify major causes
Cause and Effect Diagram for high petrol consumption
High Petrol Consumption
Procedure Driver Vehicle
MaterialsMaintenanceRoad
Restrictions
No turnOne way
CircuitousRoad
Frequentstops
Crossings
Traffic
Speed Breakers
Steep
Poorcondition
Potholes Irregularservicing
Falseeconomy
Negligence
Cloggedfilters
Low pressureIgnorance
Faulty pressure
TyresPetrol
Oil
Not changed
Low level
Incorrect viscosity
ImpuritiesIncorrectOctane no.
Additives
SparesSpurious
Inferior
Impatience
Craze
Always late
Riding onclutch
Lack of awareness
Pooranticipation
Wrong gears
Poor skill
Wrongculture
Badattitude
Inexperience
Body
Heavy
Shape
Technicaldetails
Carburetor
Spark plugs
LifeContacts
Fuel mix
Engine
High H.P
Cylinders
Cause & Effect Diagram
PROCESS MATERIALS
COOKING QTY OF WOOD QLTY TIME COOKING WATER (OLD/FRESH) VARIATION TEMP. IN
PENTOSANS IN
FINAL PULP INSTRUMENT
TRAINED UNTRAINED ACCURACY
PERSONNEL EQUIPMENTS
Uses of C & E Diagram
Trace out real root cause
Help evolve countermeasures
Making C & E an education in itself Everyone participating, learn more about their work.Is a focus for discussion.Shows level of expertise available.Can be used for any problem
HISTOGRAM
3
9
12
19
24
17
11
6
2
0
5
10
15
20
25
30
1.776 1.868 1.96 2.052 2.144 2.236 2.328 2.42 2.512
Consumption(KWh)
Freq
uenc
y
Histogram
Method of analyzing data
Data is condensed in a table
Tabulation is known as frequency distribution.
Presented by a Graph displaying distribution of data
Histogram
Graph is Characterized by 3 constituents
• centre ( mean)•width (spread-variation)•over all shape
3
9
12
19
24
17
11
6
2
0
5
10
15
20
25
30
1.776 1.868 1.96 2.052 2.144 2.236 2.328 2.42 2.512
Consumption(KWh)
Freq
uenc
y
Histogram Construction
Select a sample of min. 50 Record the measurements. Determine the range. Decide the no. of classes. Divide range into no. of classes Determine boundary or class limits. Prepare frequency distribution. Construct histogram (GRAPH).
Data on Metal Block thickness (in mm)
3.56 3.46 3.48 3.50 3.42 3.43 3.52 3.49 3.44 3.503.48 3.56 3.50 3.52 3.47 3.48 3.46 3.50 3.56 3.383.41 3.37 3.47 3.49 3.45 3.44 3.50 3.49 3.46 3.463.55 3.52 3.44 3.50 3.45 3.44 3.48 3.46 3.52 3.463.48 3.48 3.32 3.40 3.52 3.34 3.46 3.43 3.30 3.463.59 3.63 3.59 3.47 3.38 3.52 3.45 3.48 3.31 3.463.40 3.54 3.46 3.51 3.48 3.50 3.68 3.60 3.46 3.523.48 3.50 3.56 3.50 3.52 3.46 3.48 3.46 3.52 3.563.52 3.48 3.46 3.45 3.46 3.54 3.54 3.48 3.49 3.413.41 3.45 3.34 3.44 3.47 3.47 3.41 3.38 3.54 3.47
Range= Max. – Min.=3.68-3.30=0.38
No. of classes= 9 Class width= 0.5N=100
Frequency TableClass no. Class Boundaries Mid-value Frequency
1
2
3
4
5
6
7
8
9
3.275 – 3.325
3.325 – 3.375
3.375 – 3.425
3.425 – 3.475
3.475 – 3.525
3.525 – 3.575
3.575 – 3.625
3.625 – 3.675
3.675 – 3.725
3.30
3.35
3.40
3.45
3.50
3.55
3.60
3.65
3.70
3
3
9
33
37
10
3
1
1
Histogram for Metal Block Thickness
3 3
9
33
37
10
31 1
0
5
10
15
20
25
30
35
40
45
3.3 3.35 3.4 3.45 3.5 3.55 3.6 3.65 3.7
Thickness (in mm)
Freq
uenc
y
Histogram for Bearing Thickness
5
12
18
29
41
31
22
17
9
3
0
5
10
15
20
25
30
35
40
45
5.24 5.28 5.32 5.36 5.4 5.44 5.48 5.52 5.56 5.6
Thickness (in mm)
Freq
uenc
y
Histogram for Energy Consumption
3
9
12
19
24
17
11
6
2
0
5
10
15
20
25
30
1.776 1.868 1.96 2.052 2.144 2.236 2.328 2.42 2.512
Consumption(KWh)
Freq
uenc
y
Types of Histograms
Bell shaped
Symmetrical shape with a peak in middle
representing a normal histogram
3
9
12
19
24
17
11
6
2
0
5
10
15
20
25
30
1.776 1.868 1.96 2.052 2.144 2.236 2.328 2.42 2.512
Consumption(KWh)
Frequ
ency
Skewed to Left & Right
Skewed to Left
Caused by centering the process toward high end of the tolerance
Skewed to Right
Caused by centering the process toward low end of the tolerance..
Bimodal & Truncated
Bimodal : Two combined populations-- two shifts, operators, inspectors, suppliers, machine settings, gages, tools, machines, measurement locations, etc.
Truncated: This can happen when a process is not capable of meeting the specifications, parts are sorted from both ends, or too few classes are chosen.
Missing Centre Spike's at Tail (s)
Missing Centre : Centre of the distribution has been sorted from the rest. Portion may have been delivered to a customer with tighter specifications.
Spike's) at the Tail (s) : Parts in outer ends of distribution are probably being reworked to bring characteristic just within specifications.
XTrans = 1/XRaw
The Need for Transformations--Prediction from a ND is possible … Skew distribution Transformation
Before
After
Histogram Uses
To know--whether variation in data is due to chance or assignable causes.
To tell about Process Behavior
--about its capability to produce defect free output
Sources Of Variation
Common Causes
---Chance Causes Of Variation
Special Causes
--- Assignable Cause Of Variation
Common Cause Consists of combined effect of several sources of
uncontrollable variation inherent to a process.
Collective influence of common cause variation
defines natural process fluctuation and is known
as Chance causes of variation.
Process output is predictable
Process is said to be in Statistical Control
Special Cause
Variation has a large impact on performance.
Determination of source of impact makes
cause "assignable." and is termed as
assignable cause of variation.
If they exist, process or key characteristic is
said to be "out-of-control".
Out-of-control process is not predictable
3
9
12
19
24
17
11
6
2
0
5
10
15
20
25
30
1.776 1.868 1.96 2.052 2.144 2.236 2.328 2.42 2.512
Consumption(KWh)
Frequ
ency
Process Behavior It tells whether process is under control? Is it producing defect free output?
----process under control or
process variability
LSL USL
Process out Of control
USLLSL
process variability
Good Process Behavior
Shape close to normal curve
Mean at target value
Spread within Specification limits
Cp is greater than 1.67 and Cpk is greater than 1.33
SCATTER DIAGRAM
What: To study the possible relationship between two variables.
Why: Diagram make it clear whether a relationship exists, and shows the strength of relationship.
When: To test a theory that the 2 variables are related.
Examples:
Cutting speed and tool life Breakdown and equipment age Temperature & lipstick hardness Temperature and percent foam
in soft drinks Hardness and tensile strength
Different Scatter diagram Patterns
Scatter Diagram on Conveyor Speed vs. Severed Length
1000
1005
1010
1015
1020
1025
1030
1035
1040
1045
1050
5 5.5 6 6.5 7 7.5 8 8.5 9
Conveyor Speed (cm/sec)
Sev
ered
Len
gth
(mm
)
Uses:
Control Purpose
Replacing a destructive test by a non-destructive test
Study of Cause & Effect relationship
Process Optimization
Process Mapping
About This Module…
Process Mapping is a tool used to:
Clearly define processes
Identify areas where data collection should take place
Visualize activities involved in a process at the early stages of project development
Six Sigma, A Quest for Process PerfectionAttack Variation and Meet Goals
\DataFile\ProcessT.ppt
What We Will Learn …
Extending Flow Charts to Process MappingExtending Flow Charts to Process Mapping
1. The importance of process maps and the character of the product and process parameters.
2. The when, why and where to use process maps.
3. The x’s & y’s and X’s & Y’s and Y=f(x,X).
4. What to measure and control.
5. The need for process maps prior to FMEA’s, Gage Studies, DOE’s and SPC.
6. When the process map is completed.
7. How to use the tool for your process.
Process Management
ProcessProcess
• People• Equipment• Material• Money• Time
Resources
A
D
PC
InputInput
OutputOutput
Feedback
System
Basic Process Model
Cycle Time
• Time it takes to complete a process from beginning to end
Question
“How does a reduction in cycle time benefit an organization?”
A process map will identify opportunities for quality improvements.
A process map will identify opportunities for quality improvements.
Fundamentals of Process Mapping
A process map should describe: Major activities/tasks Sub processes Process boundaries Inputs Outputs Process & Product Parameters Customers & Suppliers Process owners
A process map should describe: Major activities/tasks Sub processes Process boundaries Inputs Outputs Process & Product Parameters Customers & Suppliers Process owners
A process map should be reviewed frequently and is never done.
A process map should be reviewed frequently and is never done.
A process map should document how the process actually operates, not how it is supposed to operate. (“As is,” not “To Be”)
A process map should document how the process actually operates, not how it is supposed to operate. (“As is,” not “To Be”)
Principles of Process Management
• Establish ownership.• Verify and describe the purpose of the
process.• Define the process, boundaries, and
interfaces.• Organize and train the process
improvement team.
Principles of Process Management
• Define and document the process. • Define points of control.• Establish process measurements.• Improve process.
Process Mapping Steps 1. IDENTIFY INPUTS AND OUTPUTS
– Identify Inputs (raw material, equipment, energy, 6M’s, etc.)
– Identify Outputs (measurable/assessable end product parameters)
2. SHOW ALL STEPS
– Value adding steps have the following characteristics: Something the customer would be willing to pay for Transforms the product or service Done right the first time
– Non value-added steps in the process are presented graphically: Evaluation points Rework points Scrap points Inventory
Steps (cont.)
3. SHOW OUTPUTS OF EACH STEP
– Show after each process step the characteristics that can impact the following step(s).
4. SHOW ALL PROCESS PARAMETERS AT EACH STEP
– List under each step the parameters that can change a product characteristic at that step (i.e., parameters that can be controlled at that step).
More Steps
N = Noise Factors - Uncontrollable - May be controllable, but are not controlled by decision.
C = Controllable factors - Process factors that can be changed to see the effect on product characteristics.
S = Standard Operating Procedures - A procedure is used to define and run those factors. Tooling, Fixtures.
CR = Critical Factors - Determined through FMEA, DOE, etc.
5. CLASSIFY THE PARAMETERS
– Classify the process parameters identified (in #4 above) into the following categories:
INPUTS OUTPUTSPROCESS
X’s Y’s
High Level Process Map
Inputs & Outputs
Processes Come in Hierarchies
Process - Level #1
Step #1
Process - Level #2
Step #1 Step #2
Process - Level #3
Step #3
Step #1 Step #2 Step #3
Step #3
Select the appropriate process level.Select the appropriate process level.
Step #2
Product and Process Parameters
Inputs OutputsSTEP OF PROCESS
Product Parameters, y’s
y = f(x)Process Parameters, x’s
Remember the 6 M’s
Man (People)
Machine (Equipment)
Method (Procedures)
Material
Measurement
Mother Nature (Environment)
KEY for (x’s)Process Parameters
N Noise Parameters C Controllable Process ParametersS SOP ParametersCR Critical Parameters
Why List the Parameters?
The x’s and X’s are the sources of variation in your process.
Variation causes defects.
The x’s must be under control to prevent defects.
The root cause of a defect is variation of the x’s!
The y’s and Y’s are the measured results of the process and include the failure modes of the process.
Defects are also outputs of a process step.
TO REDUCE DEFECTS!Defects
What Are We Measuring?
Measure the x’s, not the Y’s !
X’s
x’s
y’s
Y’s
_________ ?
_________ ?
_________ ?
_________ ?
We cannot control what we don’t measure!We cannot control what we don’t measure!
Inputs
Process Parameters
Process Step Outputs
Process Outputs
Is Workmanship an x?
Product Parameters, y’s
DEFECT FREE OUTPUT
DEFECTS IN PROCESS OUTPUT
y = f(x)Process Parameters, x’s
WORKMANSHIP ??
OPERATOR ??
INPUTS OUTPUTSPROCESS
X’s Y’s
6 M’s reminders:
Man (People)
Machine (Equipment)
Method (Procedures)
Material
Measurement
Mother Nature (Environment)
What Are the x’s and y’s?
Inputs Outputs
6 M’s reminders:
Man (People)
Machine (Equipment)
Method (Procedures)
Material
Measurement
Mother Nature (Environment)
Process Parameters, x’s
N
N
N
N
C
C
C
C
S
S
Product Parameters, y’s
y = f(x)
KEY for (x’s)Process Parameters
N Noise Parameters C Controllable Process ParametersS SOP ParametersCR Critical Parameters
X’s Y’s
The following may be helpful to identify process parameters that have a potential effect on the product parameters and process output:
Brainstorming
Literature review
Operators manuals
Work Instructions
Operator experience
Customer / supplier input
Engineering knowledge
Scientific theory
Remember the 6 M’s
Man (People)
Machine (Equipment)
Method (Procedures)
Material
Measurement
Mother Nature (Environment)
Identifying Product & Process Parameters
Completeness Checks
Inputs Outputs
Process Parameters, x’s
Are there y’s for every x in this step?
Is there a “good” type of y for every x ?
Is there a “bad” type of y for every x ?
Are x’s here that impact downstream y’s?
Does the map have input of extended team?
Product Parameters , y’s Good Bad = Defects Good Rejected = Defect Bad Accepted = Defect Horror Stories: What has
happened in the past that caused disasters?
Success Stories: What outputs of this step thrilled the customer(s)?
Are there x’s for each y in this step?
Are upstream x’s changing y’s of this step? How?
Step of the Process
y = f(x)
Remember the 6 M’s
Man (People)
Machine (Equipment)
Method (Procedures)
Material
Measurement
Mother Nature (Environment)
KEY for (x’s)Process Parameters
N Noise Parameters C Controllable Process ParametersS SOP ParametersCR Critical Parameters
Wave Solder Process
Flux: Kester
2% Solid FACTORPre Heat #1 Temperature
Pre Heat #2 Temperature
Pre Heat #3 Temperature
Solder Temperature
Emmersion Depth
Conveyer Speed Angle
Hot Air Knife Angle Pressure
S.G.: NA RANGE - - - - - 2.75-4.25 - 45-65 12-20NOMINAL 400 445 470 490 1/4" 3.75 N/A 60 17PSI
Current Setup: Specifications
LOAD INFIXTURE
INPUT
Bd OrientationBd SpacingBd AlignmentBd to Rail PositionCritical areas masked
LOAD ONCONVEYOR
FLUXFLUXAIR KNIFE
Solder in all holesSolder BridgingSolder InsufficientsFire Qty of Excess Flux
Lead SolderabilityAmount on Bd.Flux through holes to top sideDistribution on Bd.Þ Excessive SolderÞ BridgingÞ IciclesÞ Partially filled HolesCleanliness of Board
Conveyor speed Rail position over pot Conveyor angle Time req’d in Solder 4-Corner Fixture support Conveyor drive smoothness Finger condition Rail Straightness
Pressure Flux Brand Flux Type Thinner Cleanliness of flux Tritration level Stone Type Cleanliness of Stone Height over Stone Temperature Humidity Ambient Temp
Pressure of air knife Orientation Distance to board Air Knife used Angle of air knife Temperature
Masking Operator Board thickness 4-Corner support Bd. Spacing in Fixture Bd quantity in fixture Bd. position within fixture Front or rear Side Fixtures/conveyor width Bd Orientation Frame size/Board size Fixture mass. Fixture dimensions Vert. location bd.in fix. Component Orientation Component Density
TO PREHEAT
X’s Boards with components Solder Flux Electricity Machine Setup
KEY for (x’s)Process Parameters
Noise Parameters Controllable Process Parameters SOP Parameters Critical Parameters
Immersion depthRaised Carrier Frame cornerPoor wettingÞ Partial filled holesÞ Skip SolderingÞ BridgingÞ Excessive solder speedÞ Insufficient solderÞ BridgingÞ Cycle Time
Wave Solder Process (cont.)
Excess PressureÞ Solder BridgingÞ Insufficient solder/OpensInsufficient PressureÞ Solder BridgingTemp Too LowÞ Solder BridgingTemp Too HighÞ Insufficient
Solder/OpensÞ Damage BoardAngle Too SteepÞ Insufficient
Solder/OpensAngle Too ShallowÞ Solder Bridging
PREHEAT# 1
Temp -Zone 1 Temp - Zone 2 Temp - Zone 3 Time in Preheat 1 Resp time of
heater Stability of temp Distance to board Temp distribution Fixture warp Rail warp
SOLDER POT
Solder DistributionCoverage on boardSolder AppearanceSolder joint Quality
Solder Temp Ht of Pot/Position Solder Pot Angle Exit Point Amount of dross Solder Pump Speed Solder Height Solder Pump
Pressure Choke bar setting/adj Solder contact Solder type Solder tin content Solder Contam Baffle qual, hole
wear, bent condition, clean Board Deflection
PREHEAT# 2
Temp - Zone 2 Temp - Zone 1 Temp -Zone 3 Time in Preheat 2 Resp time of
heater Stability of temp Dist to board Temp distribution Fixture warp Rail warp
.
HOT AIR KNIFE
Position Dist to
board Temp Angle Air
Pressure Temp Dist
.
EXITWAVE SOLDER
Solder AppearanceSolder Joint Quality/DefectsOpen Solder JointsGood BoardsDirty BoardsScrap BoardsHot BoardsDamaged ComponentsLifted Components
PREHEAT# 3
Temp - Zone 3 Temp - Zone 1 Temp - Zone 2 Time in Preheat 3 Response time of
heater Stability of temp Distance to board Temp. Distribution Fixture warp Rail warp
Board TempFlux ConditionFlux ActivatedFlux Solvent drive offThermal ShockÞ Board WarpingExcess HeatÞ Excess SolderÞ Poor FilletsÞ Excess flow thruInadequate HeatÞ Solder splatterÞ Trapped GasÞ Solder BridgesÞ Poor flow thru (plated thru holes)
Y’sBoards:• Accept
ed • Reject
ed• Scrap
Workmanship Stds Samples Lighting Magnification Prod/Dmnd/Sch Census/Inspection
Staffing Inspection Sample (%) Eyesight Inspector Variation
OUTPUT INSPECTION
SCRAP
REWORK
KEY for (x’s)Process Parameters
Noise Parameters Controllable
Process Parameters
SOP Parameters Critical Parameters
Board TempFlux ConditionFlux ActivatedFlux Solvent drive offThermal ShockÞ Board WarpingExcess HeatÞ Excess SolderÞ Poor FilletsÞ Excess flow thruInadequate HeatÞ Solder splatterÞ Trapped GasÞ Solder BridgesÞ Poor flow thru (plated thru holes)
Board TempFlux ConditionFlux ActivatedFlux Solvent drive offThermal ShockÞ Board WarpingExcess HeatÞ Excess SolderÞ Poor FilletsÞ Excess flow thruInadequate HeatÞ Solder splatterÞ Trapped GasÞ Solder BridgesÞ Poor flow thru (plated thru holes)
y’sProduct Paramenters
The Importance of QuestionsNoise Parameters:
What are they? Are they impossible or impractical to control? How robust is the system to the noise?
Controllable Parameters: How are they monitored? How often are they verified? Are optimum target values known? How much variation is there around the target values? How consistent are they?
Standard Operating Procedures: Do they exist? Are they understood? Are they being followed? Are they current? Is operator certification performed? Is there an audit schedule?
Process Parameter Questions
What causes variation of the process parameter? How is the process parameter controlled? How often is the parameter out of control? Is there data on the parameter? Which of your process parameters should have
control charts on them? When should you place a control chart on a process
parameter? Which of your process parameters have control charts
on them? How are the control charts used? How do you know which process parameters to monitor? Should we focus on parameters of non value-added
steps?
Process Parameters:
Product Parameters:
Product Parameter Questions
What is the goal of the improvement effort? Is the product parameter qualitative or quantitative?
– An attribute or a variable? For the product parameters:
– Is larger better?– Is nominal best? – Is smaller better?– Is it dynamic in nature?
Is the concern for... – Process centering?– Process variation?– Both?
What is the process baseline for the product parameter? – What is the mean and sigma?
Product Parameters: Is the product parameter currently in statistical control? Is the product parameter affected by time? How much of a change in the product parameter do you
need/wish to detect? Do you know the expected distribution of the product
parameter? Is the measurement system adequate? Are there multiple responses of concern? What are the
priorities for optimization? What measurements are taken on product parameters? How do you know which product parameters to monitor? Which product parameters need control charts on them? Which product parameters have control charts on them? How are the control charts used?
More Product Parameter Questions
Process Map-Flow Charting (Step-by-Step)
Document entire flow of the process selected
Identify/classify the scope of the process
Identify/classifyupstream in-process product parameters
Classify/characterizeprocess parametersinto 3 main factors
Identify all valueand Non value-added operations
Identify the inputsand outputs of the process
Identify/classifymeasurementstaken on product & process parameters
Noise factors Standard operating procedures Controllable process parameters
Continue toupdate & classifyprocess map!
Develop initial list of process parameters along with currentoperating conditions
7. What Supplier Requirements
8. Process Controls/Dependencies
4. Who are Customers
Process owner’s requirements on the supplier
Specifications Cost Schedule
All work is a process All processes have
owners All processes can be
described as a verb and noun
All processes can be analyzed and improved
Specifications– Function– Reliability– Format
Cost Schedule
Procedures/Policies Training/Education Equipment/Facilities Quality AttitudesAny written document that controls/impacts a process
Performance skills
Certifications
Space required Processing
equipment
Personal attitude which is less than the requirement
2. What Output
3. What Input
feedback
feedback
1. What Process5. What Customer Requirements
6. Who are Suppliers
Consider Every Process Step
Causes of Process Map Failure
CONCERN RESPONSERequires extra effort - “We know the process - lets just move forward”
The process appears straight forward - then becomes difficult as you realize you do not understand process as well as you thought
The process map just seems to grow and grow and grow
Initial payoff is team understands process -- team members are not working on different set of assumptions. Use experts to help you through the mapping process
If necessary, adjust process boundaries -- initiate another improvement team
Think about approaching the problem hierarchically
What is the tool? Graphical method to illustrate the
details of a process
What will the tool identify/show? All process steps, value-added &
non value-added Input parameters (Xi,in)
End product parameters (Yi) In-process parameters (x’s & y’s) Characterization of all
parameters Defect/data collection points Steps needing FMEA’s Sources of variation identified
What is the tool? Graphical method to illustrate the
details of a process
What will the tool identify/show? All process steps, value-added &
non value-added Input parameters (Xi,in)
End product parameters (Yi) In-process parameters (x’s & y’s) Characterization of all
parameters Defect/data collection points Steps needing FMEA’s Sources of variation identified
When do you apply this tool? Always: to fully understand
process & process flow Find where/when/how defects
are being created Define elements of cycle time
What results can you expect? Systems needing MSE’s List of Factors for DOE’s Find the hidden factory Opportunities for process step
elimination (i.e. flow improvement)
Ways to re-layout the process Sources of variation reduced
When do you apply this tool? Always: to fully understand
process & process flow Find where/when/how defects
are being created Define elements of cycle time
What results can you expect? Systems needing MSE’s List of Factors for DOE’s Find the hidden factory Opportunities for process step
elimination (i.e. flow improvement)
Ways to re-layout the process Sources of variation reduced
Process Mapping Summary
Map Your Process
For the next session:• Map and characterize a critical part of your process.• Identify:
– The Inputs (X’s)– The Outputs (Y’s)– The Process Parameters (x’s) – The Product Parameters (y’s)– The process owner, supplier, & customer– Classify the parameters at each step– The next step to reduce defects in your process
What We Have Learned …
Extending Flow Charts to Process MappingExtending Flow Charts to Process Mapping
1. The importance of process maps and the character of the product and process parameters.
2. The when, why and where to use process maps.
3. The x’s & y’s and X’s & Y’s and Y=f(x,X).
4. What to measure and control.
5. The need for process maps prior to FMEA’s, Gage Studies, DOE’s and SPC.
6. When the process map is completed.
7. How to use the tool for your process.
Failure Modes and Effects Analysis
FMEA
About This Module…Failure Modes and Effects Analysis
Six Sigma, A Quest for Process PerfectionMeet Goals and Attack Variation
An FMEA is a systematic method for identifying,
analyzing, prioritizing and documenting potential
failure modes, their effects on system, product,
process performance and the possible causes of
failure.
\DataFile\FMEAform.xls \DataFile\CopyFMEA.xls|Datafile|causeeffecte.igx\Datafile\catapultflow.igx\Datafile\catapultC&E.igx
What We Will Learn…Failure Modes and Effects Analysis
1. As a Team, how to construct an FMEA and associated Action Plan
2. How the FMEA process ties to process mapping
3. The relationship between Failure Mode, Cause and Effect
4. The different types of FMEAs
Sample FMEA
Datafile/CopyFMEA.xls
Failure Effects
SEV Causes
OCC Controls
DET
RPN Action Recommended
Resp. Person
Schedule Date Action Taken
Actual Compl.
DatepS
pO
pD
prpn
Risk
Risk X
prpn
Must redo copy 6 Paper Jam 7
Periodic Maint. 7 294 Periodic preventive maintence Key Opr 3/1
PM Schedule created and implemented 2/15 6 3 7 126 3 378
Must redo copy 6
User misset size 6
Existing notes on copier 5 180
Place sign over copier outlining standard size enlarge/reduce or reliable mach to clearly indicate
standard reduce/enlarge Key Opr 2/20Place sign over
mach 2/15 6 3 2 36 1 36Must redo copy 6
User misset control 5
Existing notes on copier 4 120
Place sign to encourage user to utilize auto settings Key Opr 2/20
Place sign over mach 2/15 6 2 2 24 1 24
Must redo copy 6
Used landscape instead of portrait or vice versa 7
Tray Selection 2 84
Place note on ruler re tray selection Key Opr 1/20 Placed Note 1/15 6 2 1 12 1 12
Must redo copy 6
align marking not clear 4
Use Auto Feeder / align ruler 3 72
Enlarge marks for 8.5 " paper on ruler Key Opr 1/15 Enlarged marks 1/14 6 2 1 12 1 12
Must redo copy 6
Doc moved
when lid closed 5
Use Auto Feeder / align ruler 2 60
Place sign over copier re "Ensure align prior to copying or
use auto Feeder" Key Opr 1/15 Displayed Sign 1/14 6 1 1 6 1 6
Must redo copy 6
User selected
wrong tray 3
Auto select
function 3 54
Place sign over copier to encourage user to use auto tray
select Key Opr 2/25Place sign over
mach 2/20 6 2 3 36 1 36Must redo copy 6 Dirty Glass 6
Periodic Cleaning
SOP 1 36Place cleaning material near
copier Maint. 1/15Placed Cleaning
Matl 1/15 6 1 1 6 1 6
Why Use FMEAs?What is an FMEA?
Identify critical product characteristics and process variables
Prioritize product and process deficiencies in support of downstream improvement actions Help focus on prevention of product and process problems
Benefits of FMEA’sWhat is an FMEA?
Improves the quality, reliability and safety of products.
Helps increase customer satisfaction.
Reduces product development timing and cost.
Reduces the amount of rework, repair and scrap.
Documents and tracks actions taken.
Prioritizes deficiencies to focus improvement efforts.
Process - Level #1
Step #1 Step #2
Process - Level #2
Step #1 Step #2
Process - Level #3
Step #3
Step #1 Step #2 Step #3
FMEA - Level #1
FMEA - Level #2
FMEA - Level #3
Step #3
Process and FMEA HierarchiesWhat is an FMEA?
Steps Completed Prior to FMEA:– Charter Team– Develop and Characterize Process Map
FMEA Steps:1. Identify “Heavy Hitter” Process Step
2. Identify Associated y’s (Product Parameters)
3. Identify Failure Mode
4. Identify Failure Effects/Rate Severity
5. Identify Causes/Rate Occurrence
6. Identify Controls (if any)/Rate Detection
7. Calculate RPN
8. Prioritize by RPN Order
9. Determine Actions/Plan
10. Recalculate RPN Based on Plan
11. Take Action
Process FMEA StepsWhat is an FMEA?
Header Accessible from View Header/Footer in Excel
Workbook in Excel
FMEA FormWhat is an FMEA?
\DataFile\FMEAForm.xls
Cause(x’s)
FailureMode
Effect (y’s)
What is an FMEA?
Cause -Failure Mode -Effect Continuum
What is an FMEA?
The Cause and Effect Diagram Example
Admin/Service Example First produced in 1950 by Professor Kaoru Ishikawa - Also called the: Ishikawa Diagram Fish Bone Diagram
Developed to represent the relationship between some “effect and all possible “causes” influencing it.
Create using Igrafx:FailureEffect
Failure Mode (Defect)
Measurements Materials Manpower
Mother Methods MachinesNature
The Cause and Effect Diagram Example
Measurement
Reproducibility Repeatability
Linearity
Stability
Calibration
Methods
Vague
Out of date
Complex
Machines
Not maintained
Inadequate capability
Material
Late
Wrong quantity
Defective
Manpower
Inadequatetraining
Lack ofexperience
Distractions
Mother nature
Too humid
Too hot
Too cold
Defects
Cause and Effects Diagram
Datafile/Causeeffecte.igx
Copy Machine ExampleWhat is an FMEA?
• Our process is copying documents on a Xerox model XC1045 copy machine.
• First we will construct a process map
• Then we will construct a cause and effect diagram
• Finally we will complete an FMEA
Process: Making A CopyWhat is an FMEA?
Ma
ke C
op
ies
Place Document in Copier
Set number of
copies
Enter size required
Set light/dark settings
Select paper source
Press button
Retrieve copies
N HingesN Glass clean
Legend C Controllable Cr Critical N Noise P Procedure x Input
C Copies requiredCr Number button
C Size desiredCr Size button
C Darkness desired
C Size desiredx Paper
Cr Button
Document set correctlyGlass clean
Number of copies selected correctly
Size selected correctly
Darkness set directly
Correct paper tray selected
Copies CopiesRight numberRight contrastRight orientationRight sizeRight paper
The FMEA Process
Step 1: Identify “Heavy Hitter” Process Step
From the Process Map, identify the process step with the most likelihood of having failure modes with significant effects
Use defect data and/or team knowledge about failure modes when selecting process steps
Significant impact to the business? (COPQ, cycle time, fill rate, ...)
Use a Cause and Effect Diagram to capture brainstorming results.
After completing FMEA Steps #2-7 for all failure modes associated with this process step, return to this step and select the next most likely “Heavy Hitter” process step
Not all process steps will need to be analyzed by the FMEA
Step 2: Identify Associated y’sThe FMEA Process
From the Process Map, identify the y’s that are associated with the process step being investigated
As the y’s are the indications of a successful completion of the process step, they are crucial as a basis for determining failure modes
Step 3: Identify Failure Mode
• Brainstorm failure modes for the selected process step :– Identify the ways in which the process could fail to
generate each of the expected “y’s”
• Eliminate “duplicates” from brainstorm list• Are the failure modes from the same level of the process?• Are the failure modes specific?• Are the failure modes the most likely?• Do the failure modes provide good coverage of the
process step?• Have all y’s been considered?
The FMEA Process
Step 4: Identify Failure Effect/Rate Severity
The FMEA Process
Pick the most likely failure mode and brainstorm the most important Effects:
– FAILURE EFFECTS are the outcome of the occurrence of the failure mode on the process. The impact on the customer --- What does the customer experience as a result of the Failure Mode?
Identify each effect as being “Attribute” or “Variable”
Severity doesn’t change unless the design changes.
Step 5: Identify Causes/Rate OccurrenceThe FMEA Process Identify the most likely causes for each failure mode
using a Cause and Effect Diagram:
– CAUSES are the conditions that bring about the Failure Mode
Transfer the resulting information to the FMEA form
Assign an occurrence value (1-10) to the likelihood that each particular cause will happen and result in the failure mode
The occurrence score for each cause should be related to the likelihood of that cause resulting in the failure mode and producing the specific associated effect
Organize Brainstorming IdeasThe FMEA Process
Copy Misaligned
Manpower
Selected wrongorientation
Materials
Wrong Paper Size
Measurement
Wrong Size Selected
Machine
Alignment MarkingUnclear
Method
Document MovedWhen Lid was
Closed
MotherNature
Too Humid
What would you add?
Step 6: Identify Controls/Rate DetectionThe FMEA Process
Identify the current mechanisms in place which prevent the cause from occurring, or detect it before the product reaches the customer. Some examples of controls are SPC, training, maintenance, inspection, SOP etc.
Assign a detection value (1-10) based on an assessment of the likelihood that the current control mechanisms will detect the cause of the failure mode before it reaches the customer.
Don’t agonize over detectability.
The product of the estimates of severity
occurrence and
detection.
The RPN provides a relative priority for taking action
the bigger the RPN, the more important to address.
RPN = SEVERITY x OCCURRENCE x DETECTION
Step 7: Calculate Risk Priority Number The FMEA Process
8: Prioritize by RPN Order
Use the “Sort” command in Excel to order the spreadsheet in descending order of Risk Priority Number (RPN).
9: Determine Actions/Plan
Based on the causes found, determine actions that will minimize the effect of each cause, in priority order.
Steps 8 and 9The FMEA Process
10: Recalculate RPN Based on Plan Assuming the actions are carried out successfully, reassign
severity, occurrence and detectability.
Place these new ratings in the “predicted” columns (ps, po & pd).
Assign a rating from 1 to 5 for each action that will show the “risk” associated with each action (5 being the greatest risk). Place the rating in the “risk” column.
11: Take Action Based on the risk mitigation column (Risk * prpn), take the actions
indicated or reassign actions. Then….
Complete the actions indicated by the times stated!
Steps 10 and 11The FMEA Process
Failure Effects
SEV Causes
OCC Controls
DET
RPN Action Recommended
Resp. Person
Schedule Date Action Taken
Actual Compl.
DatepS
pO
pD
prpn
Risk
Risk X
prpn
Must redo copy 6 Paper Jam 7
Periodic Maint. 7 294 Periodic preventive maintence Key Opr 3/1
PM Schedule created and implemented 2/15 6 3 7 126 3 378
Must redo copy 6
User misset size 6
Existing notes on copier 5 180
Place sign over copier outlining standard size enlarge/reduce or reliable mach to clearly indicate
standard reduce/enlarge Key Opr 2/20Place sign over
mach 2/15 6 3 2 36 1 36Must redo copy 6
User misset control 5
Existing notes on copier 4 120
Place sign to encourage user to utilize auto settings Key Opr 2/20
Place sign over mach 2/15 6 2 2 24 1 24
Must redo copy 6
Used landscape instead of portrait or vice versa 7
Tray Selection 2 84
Place note on ruler re tray selection Key Opr 1/20 Placed Note 1/15 6 2 1 12 1 12
Must redo copy 6
align marking not clear 4
Use Auto Feeder / align ruler 3 72
Enlarge marks for 8.5 " paper on ruler Key Opr 1/15 Enlarged marks 1/14 6 2 1 12 1 12
Must redo copy 6
Doc moved
when lid closed 5
Use Auto Feeder / align ruler 2 60
Place sign over copier re "Ensure align prior to copying or
use auto Feeder" Key Opr 1/15 Displayed Sign 1/14 6 1 1 6 1 6
Steps 1-11:
The FMEA Process
\DataFile\CopyFMEA.xls
FMEA
Step 5Step 10
Step 7 & 8
Step 2 ID y’s
Step 11Step 4
Step 9Step 6Step 1 ID Process Steps
Step 3 ID Failure Modes
Process FMEA
Types of FMEA
• Helps analyze manufacturing and assembly processes to reduce the occurrence and improve detection of defects.
• Assists in the development of process control plans.
• Establishes a priority for improvement activities.• Documents the rationale behind process
changes and helps guide future process improvement plans.
• IS PROACTIVE! Should be started when new processes are designed or when old processes are changed.
Note: When completing a Process FMEA, first assume the material is good and the process is bad. Then assume that the process is good and the material is bad. Lastly, review the process for safety considerations.
Process FMEA Scoring Definition
Types of FMEA
Score DETECTION
10 1 in 2 Very High Absolute Uncertainty
9 1 in 3 Very High Very Remote
8 1 in 8 High Remote
7 1 in 20 High Very Low
6 1 in 80 Moderate Low
5 1 in 400 Moderate Moderate
41 in 2,000 Moderate Moderately High
31 in 15,000 Low High
21 in 150,000 Low Very High
1£1 in 1,500,00 Remote Almost Certain
SEVERITY CRITERIA OCCURRENCE
Hazardous Without Warning
Hazardous With Warning
Very High
High
Moderate
Low
Very Low
Minor
Very Minor
None
Design/Product FMEATypes of FMEA
• Helps to identify potential product failure modes early in the product development cycle.
• Increases the likelihood that all potential failure modes and their effects on assemblies will be considered.
• Assists in evaluating product design requirements and test methods.
• Establishes a priority for design improvement.• Documents the rationale behind design
changes and helps guide future development projects.
• IS PROACTIVE! Should be done when new products are designed or existing products are changed.
Defect FMEA
• Helps identify the root causes of defects.• Establishes a priority for improvement activities.• Documents plan of action.• Provides methodology to battle initial ground swell
of defects.• Focuses effort on defects with highest $ impact.• IS NOT PROACTIVE!
Types of FMEA
Scoring CriteriaTypes of FMEA
Score DETECTION10 Very High Absolute Uncertainty9 Very High Very Remote8 High Remote7 High Very Low6 Moderate Low
5 Moderate Moderate
4 Moderate Moderately High3 Low High2 Low Very High1 Remote Almost Certain
RISK: Optional field used to reflect the probability of completing actions.
SEVERITY CRITERIA OCCURRENCEHazardous Without WarningHazardous With WarningVery HighHighModerate
Low
Very LowMinorVery MinorNone
Note: To change header information, click on "View" then "Header".
Use actual defect quantities
The CatapultFMEA Exercise
Analyze the Catapult process using the FMEA tool. (Remember we want to get the “most bang for the buck”.)
25 minutes!
• Break into the Catapult teams• We have already constructed a process map• First, we will construct a cause and effect
diagram• Then we will complete at least two failure
modes for the most critical step(s) of our process
• Appoint a spokesman for your team to debrief the class on your progress, questions, etc.
• Complete the FMEA (FMEAform.xls) for the Catapult process before the third session (We will use this information for our DOE competition)
Catapult Process MapFMEA Exercise
Datafile/Catapultflow.igx
Assemble Catapult
Secure to tableSelect Catapult
SettingsSet Catapult
Pins
ShootMeasure distance
Record distance
Pins (2)ArmRubber BandBall
ClampTape MeasureTape
Aligned with tape ± 3 inches
Pull Arm to Proper Angle
Arm moves smoothly
Plan or Prediction equationComputer
Feasible settings
Correct settings
Positions Designated
OperatorConsistencyNo Parallax
OperatorLateral movement
Tape MeasureObservers positioned properly
Ball flys straight
Accurate measurement ± 2 inches
RecorderComputer
Correct angle
Stop
Correct distance recorded
Start
Complete the Diagram BelowFMEA Exercise
Datafile/CatapultC&E.IGX
Distance
MenMaterialMethod
MeasureMachine
Mother nature
Calculation procedureRubber Band
Ball
Release consistency
Angle measurement
Repeatability
Reproducibility
Arm moves freelyAir Conditioner
When To Update an FMEA?FMEA Summary
An FMEA should be updated whenever a change is being considered to a product’s:
design
application
environment
material
product’s manufacturing or assembly process
What is the tool?– Spreadsheet
What will the tool identify/show?– All product/process failure
modes, related effects, causes, & methods of controlling them
– Risk Priority Number (RPN) for action based on failure severity, probability of occurrence and detection capability
– Actions/plans to reduce elements of RPN
When do you apply this tool?– When evaluating product for
robustness (functionality, produceability, reliability)
– During early stages of defect reduction efforts to identify causes
– When identifying key process/product parameters and evaluating methods for controlling them
What results can you expect?– Learn to identify critical product/
process parameters– Achieve consensus on solutions and
methods of implementation– Detailed product/process
understanding
Summary of Product/Process FMEA’sFMEA Summary
Keys to Success
Identify purpose...BE SPECIFIC!
Understand effects...INVOLVE CUSTOMERS & SUPPLIERS!
Link to the process map.
Use to prioritize efforts, allocate resources.
Use as a risk assessment/prioritization tool based on predicted impact.
Use to build consensus on prioritization.
Encourage creativity...TEAMWORK!
PLAN!
ASK QUESTIONS!
FMEA Summary
Steps Completed Prior to FMEA:– Charter Team– Develop and Characterize Process Map
FMEA Steps:1. Identify “Heavy Hitter” Process Step
2. Identify Associated y’s (Product Parameters)
3. Identify Failure Mode
4. Identify Failure Effects/Rate Severity
5. Identify Causes/Rate Occurrence
6. Identify Controls (if any)/Rate Detection
7. Calculate RPN
8. Prioritize by RPN Order
9. Determine Actions/Plan
10. Recalculate RPN Based on Plan
11. Take Action
Process FMEA StepsWhat is an FMEA?
FMEA Appendix
Severity is an assessment of how serious the effect of the potential failure mode is on the customer. The customer in this case could be the next operation, subsequent operations, or the end user.
Occurrence is an assessment of the likelihood that a particular cause will happen and result in thefailure mode.
Detection is an assessment of the likelihood that the current controls (design and process) will detectthe cause of the failure mode, should it occur, thus preventing it from reaching your customer. The customer in this case could be the next operation, subsequent operations, or the end user.
Current Controls (for both design and process) are the mechanisms which prevent the cause of the failure mode from occurring, or detect the failure mode, should it occur, before the product reaches your “customer.” For example, current controls include SPC, inspections, written
procedures, training, preventive maintenance and all other activities that ensure a smooth running process.
Critical Characteristics are those items which affect customer safety and/or could result in non-compliance to regulations and thus require controls to ensure 100% compliance. These areusually process“settings” such as temperature, time, speed, etc.
Significant Characteristics are those items which require SPC and quality planning to ensure acceptable levels of capability.
Key Definitions for FMEA
TerminologyA. Process or Product Name – Description of Process or Product being analyzed.B.C.D.E.F.
G.
H.I.J.K.L.
M.
N.
O.P.Q.R.S.T.
Responsible – Name of Process Owner.Prepared By - Name of Agent coordinating FMEA study.FMEA Date – Dates of Initial and subsequent FMEA Revisions.Process Step/Part Number – Description of individual item being analyzed.Potential Failure Mode – Description of how the process could potentially fail to meet the process requirements and/or design intent, i.e. a description of a non-conformance at that Potential Failure Effects – Description of the effects of the Failure Mode upon the customer, i.e. what the next user of the process or product would experience or notice.SEV (Severity) – An assessment of the seriousness of the effect of the potential failure mode
RPN (Risk Priority Number) – The product of the Severity, Occurrence, and Detection Rankings i.e., RPN = SEV * OCC * DET.
DET (Detection) – An assessment of the probability that the current controls will detect the potential cause, or the subsequent failure mode.
Current Controls – Description of process controls that either prevent, to the extent possible, OCC (Occurrence) – Description of how frequently the specific failure cause is expected to Potential Causes – Description of how the failure could occur, described in terms of something
Resulting new RPN after corrective action.New DETECTION Rating after corrective action.New OCCURENCE Rating after corrective action.New SEVERITY Rating after corrective action.Actions Taken – Brief description of actual action and effective date.Responsibility – Person or group responsible for the Recommended Action.
Actions Recommended – Actions to reduce any or all of the Occurrence, Severity or Detection rankings.
FMEA Appendix
Introduction to Process Capability
About this Module
• Process capability enables the prediction of the
ability of any process to produce products and
services that meet their desired specifications.
• This module focuses on typical manufacturing
processes. Transactional and other
manufacturing processes are not discussed here.
• The principles of process capability will be
introduced and Minitab will be used to calculate
process capabilities.
Learning Objectives
At the conclusion of this module participants
will be able to:
1. Recognize the value of and uses for process
capability.
2. Calculate and explain the capability of
processes whose output is normally
distributed.
3. Predict the probability that the output of a
process will be within its specification limits.
We Live in a Statistical World
• Statistics have a pervasive influence on our lives– Every day there is another poll– Sampling is being used to perform many
aspects of the census– All major economic indicators are based on
samples– TV ratings are based on samples – Statistics determine insurance rates
• Quantum physics has demonstrated that probability determines the structure and operation of everything
• Statistics are a major enabler of Six Sigma
Basic Statistics
Types of StatisticsDescriptive statistics
is the process of describing the information we have. We summarize information from a sample or population give a clear understanding, or description, of the data.
Inferential statisticsis the process of using information from a smaller set of data (sample) to reach conclusions or inferences about a larger group (population). Usually, we have only sample information, not the entire population, and must infer understanding of the population based on our sample. We want these conclusions to be mathematically correct.
Definitions
Data TypesAttribute
Yes - noGood - badAccept - reject
DiscreteMultiples of whole unitsCan not be meaningfully dividedCount or classification
ContinuousCan be meaningfully divided into finer and finer increments of precision weight, length, voltage, time
Definitions
Mode - the most frequently occurring or most likely value
Median - the fiftieth percentile
(half the values are above and half below the
median)
m= = åPopulation mean X X X X
N
j
j11 2 3, , ...
X Sample mean=
Definitions
Mean - the sum of all members divided by the population size (average)
Measures of Central Tendency - Location
Population Versus SampleDefinitions
Statistics infer information about the parameters of the population.
Population SamplesSize N nLocation Average (Mean) m x
Dispersion: Variation Variance s2 s2
Std dev s s Range R = XHi-XLo
Quantifying Dispersion - SpreadDefinitions
X
x1
x2
xn
We could add the differences between each value x and the average of the values x however that would always yield zero. Therefore we square the difference between each x and x, to eliminate the negatives and emphasize the outliers, then take the average of the results. This is defined as the variance or 2. Obviously,
2s
1n
)XX(ˆs
n
1i
2
Frequency
Values of X
0
2
4
6
8
10
12
14
50 60 70 80 90 100 110
75 80 75 65 7085 70 70 85 7060 80 80 80 6580 75 75 70 8570 75 75 75 8580 55 70 70 8565 70 80 75 6575 85 90 80 6570 75 75 80 8075 95 90 60 65
Variable X measurements:
Number of Cases = 50Mean & Median = 75Standard Deviation = 8.3299Range = 40Variance = 69.388Minimum = 55Maximum = 95
i
nˆX
n
1iiX
Attributes of the Histogram - Location & SpreadDefinitions
Measures of Variability - Variance = Sigma Squared
Sigma Squared is a measure of dispersion of the population about the mean
Variances are not in the units of interest; standard deviations are in the units of interest
Variances are additive; standard deviations are not
additive... …so s1
2 + s22 + s3
2 is OK, but, s1 + s2 + s3 is NOT OK
Definitions
Measures of Variability – S. D. = Sigma Definitions
= the units of interest and is population standard
deviationm = population meanN = total populations = estimate of standard deviationn = sample size( )
( ) ( ) ( ) ( )N
XXXXX
N
22
3
2
2
2
1 ... --+-+-=s
m m m m
( ) ( ) ( ) ( )n - 1
XXXXXXXX n
22
3
2
2
2
1 ... --+-+-= s =̂
Standard Deviation is a measure of dispersion of the population about the mean
Normal Distribution
Each curve shown here has: An area of one A mean of zero A standard deviation of
Therefore, the same % of the population is under each of the curves for n about the mean.
Quantifying the Normal Distribution
-3 -2 -1 +1 +2 m s m s m s m m s m s+3m s 68.26%
95.46%
99.73%
Definitions
Area under the curve = 1s = 1m = 0
Any normal distribution can be converted to a standard normal distribution
f z ez
( ) 1
2
2
2
The formula for the probability density function is
Probability Density Function – Standard Normal DistributionDefinitions
The Standard Normal Transform
Permits conversion of any data point (X) into a Z value. This value allows us to look up the percentage of the population that is above and below the data point.
XZ
Definitions
Sample Questions………
Q. A new iron ore mine is discovered. 10 Kg ore is collected from each of 20 spots.
a. This procedure is called as __________ . b. Average is calculated from iron content of each of 20
spots. This value is called as ________________c. If we calculate average, range and standard deviation
from the iron content values of each lot, this data is called as ________________ .
d. Predictions are made regarding average iron content of the mine, total iron that can be extracted, impurities present etc. the analysis is called as ___________ .
e. The above calculations will give answers which will be 100% correct. True / False
Answers
a. The procedure is called as SAMPLING.
b. The value is called as STATISTIC.
c. The values are called as STATISTICS.
d. The analysis is called as STATISTICAL ANALYSIS.
e. The Statement is FALSE.
Basic Principle• All measures of process capability are based
on the concept of calculating the number of standard deviations between the process center and the specification limits.
• A Six Sigma process has six units of standard deviation between the process center and both specification limits.
USLLSL
Visualizing Process Capability
Process width
Specification width
Quantifying Process Capability
Process Sigma Yield1 0.68268952 0.95449973 0.99730024 0.99993675 0.99999946 1
If we assume the process is centered on the target and does not shift or drift the yields would be.
Yield of a one sigma process 0.683
LSL
USL
The Standard Deviation
m
1s
T USL
p(d)
Upper Specification Limit (USL)Target Specification (T)Lower Specification Limit (LSL)Mean of the distribution (m)Standard Deviation of the distribution (s) 3s
1 Sigma - 68%2 Sigma - 95%3 Sigma - 99.73 %
S (X – X)2
ns =
Calculating Yield
We know that Z is the number of units of standard deviation on a standard normal curve which has a mean of zero and a standard deviation of one. We also know any normal distribution can be converted to the standard normal using the Z equation.
xZ
If the specification limits are substituted for x we can determine the number of units of standard deviation between the process center and the specification limits on the standard normal curve. Then we can use the tables to look up the probability a value will be less than that number.
ˆ
X XZ
In most cases we do not know m or s so we substitute the sample statistics for the population parameters as shown.
Calculating Yield
The mean time taken for completing an operation is 500 hrs.
and this is normally distributed with a standard deviation of
100 hrs.
1. What is the probability that an operator taken at random
will take between 500 to 650 hrs to complete the
operation?
2. What is the probability that he will take > 700 hrs?
Express in graphical form also.
Calculating Yield – Example
1. What is the probability that an operator taken at random
will take between 500 to 650 hrs to complete the
operation?
= (650 – 500) / 100 = 1.5
Looking up z table, the corresponding value under the
Standard Normal Distribution is 0.4332. i.e. 43%.
xZ
Calculating Yield – Example
2. What is the probability that he will take > 700 hrs?
= (700 – 500) / 100 = 2
Looking up z table, the corresponding value under the
Standard Normal Distribution is 0.4772.
Thus the probability of an operator taking more than 700 hrs
is (0.5 – 0.4772) = 0.0228, i.e. slightly over 2%.
xZ
Calculating Yield Example
Consider a process that has the following specification limits: Lower Specification Limit (LSL) of -1 and a Upper Specification Limit of 1. Data indicates the process is centered on 0 with a standard deviation of 1. What is the yield?
USL
USL
USL-XZ =
σ̂1-0
Z = 11
Using tables or software to look up the area under the curve when Z=1 we find .8413. This means that 84.13% of the product has a value less than the upper specification limit.
LSL
LSL
LSL-XZ =
σ̂-1-0
Z = 11
Again using tables or software to look up the area under the curve when Z=-1 we find .1586. This means that 15.86% of the product has a value less than the lower specification limit.
What if the Process Shifts?
Generally speaking, processes have been observed to shift and/or drift 1.5 standard deviations over time. How would that effect the yield of a one sigma process?
10-1-2-3-4
LSL USL
Calculating Shifted Process Yield
USL
USL
LSL
LSL
USL-XZ =
σ̂1-0-1.5
Z = .51
LSL-XZ =
σ̂-1-0-1.5
Z = 2.51
Using tables or software to look up the area under the curve when Z=-.5 we find .3085
Again using tables or software to look up the area under the curve when Z=-2.5 we find .0062.
Subtracting the two we obtain .3023
Using These Principles
• Process capability and process capability
indices are unambiguous and will be
addressed first.
• Process sigma is somewhat ambiguous
and will be addressed second.
Process Capability Terms
See formulae on next page.
Measures of the ability of a process to produce compliant products/services:Cp - Short-term process capability For a limited period of time (not including shifts and drifts) Does not consider process centering Also known as process entitlement
Cpk - Short-term process capability index For a limited period of time (not including shifts and drifts) Does consider process centering
Pp - Long-term process capability For an extended period of time (including shifts and drifts) Does not consider process centering
Ppk - Long-term process capability index For an extended period of time (including shifts and drifts) Does consider process centering
Specification Width (s)Short-Term Process Width
=
Specification Width (s)Long-Term Process Width
=
Lesser of: or
Lesser of: or
Capability Formulae
Cp =
Pp =
Cpk=
Ppk=
ST
USL-LSL
6σ
LT
USL-LSL
6σ
ST
USL-X
3σ
LT
USL-X
3σ
ST
X-LSL
3σ
LT
X-LSL
3σ
Using MinitabThe data is continuous so test for normalityStat>Basic Statistics>Normality Test
The Normality Test
1.0081.0061.0041.0021.0000.9980.9960.9940.992
99.99
99
95
80
50
20
5
1
0.01
Caps
Perc
ent
Mean 1.000StDev 0.001986N 750AD 0.619P-Value 0.107
Probability Plot of Caps
Worksheet: Bottle Caps.MTW
Normal
The P value is > .05 therefore do not reject the assumption of normality.
Using Minitab to Calculate Process Capability
Minitab Results
LSL Target USL
LSL 0.995Target 1USL 1.005Sample Mean 1.00006Sample N 750StDev(Within) 0.00198431StDev(Overall) 0.00198636
Process Data
Z.Bench 2.26Z.LSL 2.55Z.USL 2.49Cpk 0.83
Z.Bench 2.26Z.LSL 2.55Z.USL 2.48Ppk 0.83Cpm 0.84
Overall Capability
Potential (Within) Capability
% < LSL 0.40% > USL 0.67% Total 1.07
Observed Performance% < LSL 0.54% > USL 0.64% Total 1.18
Exp. Within Performance% < LSL 0.54% > USL 0.65% Total 1.19
Exp. Overall Performance
WithinOverall
Process Capability of Caps
Worksheet: Bottle Caps.MTW
Let’s examine this in detail
Process Data
1.005
0
1.003
5
1.002
0
1.000
5
0.999
0
0.997
5
0.996
0
0.994
5
LSL Target USL
LSL 0.995Target 1USL 1.005Sample Mean 1.00006Sample N 750StDev(Within) 0.00198431StDev(Overall) 0.00198636
Process Data
Z.Bench 2.26Z.LSL 2.55Z.USL 2.49Cpk 0.83
Z.Bench 2.26Z.LSL 2.55Z.USL 2.48Ppk 0.83Cpm 0.84
Overall Capability
Potential (Within) Capability
% < LSL 0.40% > USL 0.67% Total 1.07
Observed Performance% < LSL 0.54% > USL 0.64% Total 1.18
Exp. Within Performance% < LSL 0.54% > USL 0.65% Total 1.19
Exp. Overall Performance
WithinOverall
Process Capability of Caps
Worksheet: Bottle Caps.MTW
Calculated directly from the data. The within standard deviation is the pooled standard deviation of the subgroups.
Observed Performance
1.005
0
1.003
5
1.002
0
1.000
5
0.999
0
0.997
5
0.996
0
0.994
5
LSL Target USL
LSL 0.995Target 1USL 1.005Sample Mean 1.00006Sample N 750StDev(Within) 0.00198431StDev(Overall) 0.00198636
Process Data
Z.Bench 2.26Z.LSL 2.55Z.USL 2.49Cpk 0.83
Z.Bench 2.26Z.LSL 2.55Z.USL 2.48Ppk 0.83Cpm 0.84
Overall Capability
Potential (Within) Capability
% < LSL 0.40% > USL 0.67% Total 1.07
Observed Performance% < LSL 0.54% > USL 0.64% Total 1.18
Exp. Within Performance% < LSL 0.54% > USL 0.65% Total 1.19
Exp. Overall Performance
WithinOverall
Process Capability of Caps
Worksheet: Bottle Caps.MTW
The percent of product that was outside of the upper and lower specification limits in this data set.
Expected Within Performance
1.005
0
1.003
5
1.002
0
1.000
5
0.999
0
0.997
5
0.996
0
0.994
5
LSL Target USL
LSL 0.995Target 1USL 1.005Sample Mean 1.00006Sample N 750StDev(Within) 0.00198431StDev(Overall) 0.00198636
Process Data
Z.Bench 2.26Z.LSL 2.55Z.USL 2.49Cpk 0.83
Z.Bench 2.26Z.LSL 2.55Z.USL 2.48Ppk 0.83Cpm 0.84
Overall Capability
Potential (Within) Capability
% < LSL 0.40% > USL 0.67% Total 1.07
Observed Performance% < LSL 0.54% > USL 0.64% Total 1.18
Exp. Within Performance% < LSL 0.54% > USL 0.65% Total 1.19
Exp. Overall Performance
WithinOverall
Process Capability of Caps
Worksheet: Bottle Caps.MTW
The percent of product that is expected to be outside of the upper and lower specification limits on an short term basis. This projection is based on the within standard deviation and the process mean.
Expected Overall Performance
1.005
0
1.003
5
1.002
0
1.000
5
0.999
0
0.997
5
0.996
0
0.994
5
LSL Target USL
LSL 0.995Target 1USL 1.005Sample Mean 1.00006Sample N 750StDev(Within) 0.00198431StDev(Overall) 0.00198636
Process Data
Z.Bench 2.26Z.LSL 2.55Z.USL 2.49Cpk 0.83
Z.Bench 2.26Z.LSL 2.55Z.USL 2.48Ppk 0.83Cpm 0.84
Overall Capability
Potential (Within) Capability
% < LSL 0.40% > USL 0.67% Total 1.07
Observed Performance% < LSL 0.54% > USL 0.64% Total 1.18
Exp. Within Performance% < LSL 0.54% > USL 0.65% Total 1.19
Exp. Overall Performance
WithinOverall
Process Capability of Caps
Worksheet: Bottle Caps.MTW
The percent of product that is expected to be outside of the upper and lower specification limits on an long term basis. This projection is based on the overall standard deviation and the process mean.
Potential Within Capability
1.005
0
1.003
5
1.002
0
1.000
5
0.999
0
0.997
5
0.996
0
0.994
5
LSL Target USL
LSL 0.995Target 1USL 1.005Sample Mean 1.00006Sample N 750StDev(Within) 0.00198431StDev(Overall) 0.00198636
Process Data
Z.Bench 2.26Z.LSL 2.55Z.USL 2.49Cpk 0.83
Z.Bench 2.26Z.LSL 2.55Z.USL 2.48Ppk 0.83Cpm 0.84
Overall Capability
Potential (Within) Capability
% < LSL 0.40% > USL 0.67% Total 1.07
Observed Performance% < LSL 0.54% > USL 0.64% Total 1.18
Exp. Within Performance% < LSL 0.54% > USL 0.65% Total 1.19
Exp. Overall Performance
WithinOverall
Process Capability of Caps
Worksheet: Bottle Caps.MTW
Z USL and Z LSL are calculated using the process mean, the respective specification limits and the within standard deviation.Z bench is calculated by putting the projected within yield (.982) left hand tail of a standard normal then looking up the respective Z score.Cpk is calculated 1/3 of the lesser of Z USL or Z
LSL.
Note: Minitab uses within to describe short term variation and overall to describe long term variation.
Overall Capability
1.005
0
1.003
5
1.002
0
1.000
5
0.999
0
0.997
5
0.996
0
0.994
5
LSL Target USL
LSL 0.995Target 1USL 1.005Sample Mean 1.00006Sample N 750StDev(Within) 0.00198431StDev(Overall) 0.00198636
Process Data
Z.Bench 2.26Z.LSL 2.55Z.USL 2.49Cpk 0.83
Z.Bench 2.26Z.LSL 2.55Z.USL 2.48Ppk 0.83Cpm 0.84
Overall Capability
Potential (Within) Capability
% < LSL 0.40% > USL 0.67% Total 1.07
Observed Performance% < LSL 0.54% > USL 0.64% Total 1.18
Exp. Within Performance% < LSL 0.54% > USL 0.65% Total 1.19
Exp. Overall Performance
WithinOverall
Process Capability of Caps
Worksheet: Bottle Caps.MTW
Z USL and Z LSL are calculated using the process mean, the respective specification limits and the overall standard deviation.Z bench is calculated by putting the projected within yield (.981) left hand tail of a standard normal then looking up the respective Z score.Ppk is calculated as 1/3 of the lesser of Z USL or Z LSL.
Within - Between
1.005
0
1.003
5
1.002
0
1.000
5
0.999
0
0.997
5
0.996
0
0.994
5
LSL Target USL
LSL 0.995Target 1USL 1.005Sample Mean 1.00006Sample N 750StDev(Within) 0.00198431StDev(Overall) 0.00198636
Process Data
Z.Bench 2.26Z.LSL 2.55Z.USL 2.49Cpk 0.83
Z.Bench 2.26Z.LSL 2.55Z.USL 2.48Ppk 0.83Cpm 0.84
Overall Capability
Potential (Within) Capability
% < LSL 0.40% > USL 0.67% Total 1.07
Observed Performance% < LSL 0.54% > USL 0.64% Total 1.18
Exp. Within Performance% < LSL 0.54% > USL 0.65% Total 1.19
Exp. Overall Performance
WithinOverall
Process Capability of Caps
Worksheet: Bottle Caps.MTW
This process is very stable as indicated by the Within and Between lines being very close together.
Calculating Cpk and Ppk
Calculating Cpk and Ppk
1.005
0
1.003
5
1.002
0
1.000
5
0.999
0
0.997
5
0.996
0
0.994
5
LSL Target USL
LSL 0.995Target 1USL 1.005Sample Mean 1.00006Sample N 750StDev(Within) 0.00198431StDev(Overall) 0.00198636
Process Data
Cp 0.84CPL 0.85CPU 0.83Cpk 0.83
Pp 0.84PPL 0.85PPU 0.83Ppk 0.83Cpm 0.84
Overall Capability
Potential (Within) Capability
PPM < LSL 4000.00PPM > USL 6666.67PPM Total 10666.67
Observed PerformancePPM < LSL 5355.08PPM > USL 6432.04PPM Total 11787.12
Exp. Within PerformancePPM < LSL 5395.59PPM > USL 6478.48PPM Total 11874.07
Exp. Overall Performance
WithinOverall
Process Capability of Caps
Worksheet: Bottle Caps.MTW
CPL and CPU are calculated using the process mean, the respective specification limits and the within standard deviation.Cp is calculated by putting the projected within yield (.982) left hand tail of a standard normal then looking up the respective Z score.Then dividing by 3. Cpk is the lesser of CPL or CPU.
Calculating Cpk and Ppk
1.005
0
1.003
5
1.002
0
1.000
5
0.999
0
0.997
5
0.996
0
0.994
5
LSL Target USL
LSL 0.995Target 1USL 1.005Sample Mean 1.00006Sample N 750StDev(Within) 0.00198431StDev(Overall) 0.00198636
Process Data
Cp 0.84CPL 0.85CPU 0.83Cpk 0.83
Pp 0.84PPL 0.85PPU 0.83Ppk 0.83Cpm 0.84
Overall Capability
Potential (Within) Capability
PPM < LSL 4000.00PPM > USL 6666.67PPM Total 10666.67
Observed PerformancePPM < LSL 5355.08PPM > USL 6432.04PPM Total 11787.12
Exp. Within PerformancePPM < LSL 5395.59PPM > USL 6478.48PPM Total 11874.07
Exp. Overall Performance
WithinOverall
Process Capability of Caps
Worksheet: Bottle Caps.MTW
PPL and PPU are calculated using the process mean, the respective specification limits and the overall standard deviation.Pp is calculated by putting the projected within yield (.9813) left hand tail of a standard normal then looking up the respective Z score.Then dividing by 3. Ppk is the lesser of PPL or PPU.
A Process that Drifts
Consider a similar process that does change over time. The data is in Caps Drift.MTW.First test for normality
Normality Test
1.00501.00251.00000.99750.9950
99.99
99
95
80
50
20
5
1
0.01
Caps Drift
Perc
ent
Mean 1.000StDev 0.001291N 720AD 0.326P-Value 0.520
Probability Plot of Caps Drift
Worksheet: Caps Drift.MTW
Normal
Do not reject the assumption of normality.
Capability Analysis
Capability Analysis
1.00501.00351.00201.00050.99900.99750.9960
LSL Target USL
LSL 0.995Target 1USL 1.005Sample Mean 0.999998Sample N 720StDev(Within) 0.00102066StDev(Overall) 0.00129055
Process Data
Z.Bench 4.76Z.LSL 4.90Z.USL 4.90Cpk 1.63
Z.Bench 3.70Z.LSL 3.87Z.USL 3.88Ppk 1.29Cpm 1.29
Overall Capability
Potential (Within) Capability
% < LSL 0.00% > USL 0.00% Total 0.00
Observed Performance% < LSL 0.00% > USL 0.00% Total 0.00
Exp. Within Performance% < LSL 0.01% > USL 0.01% Total 0.01
Exp. Overall Performance
WithinOverall
Process Capability of Caps Drift
Worksheet: Caps Drift.MTW
This process is changing over time as indicated by the difference between the Within and Between lines.Plot this data using a control chart.
Process Capability Exercise 1
Data indicate the process is centered with a standard deviation of .02. Calculate the yield.
1 ± .06 Inches
Exercise 1 Visualizing the Answer
Design width(.12 Inches)
Process average
+.02 +.04 +.06-.06 -.04 -.02
There are 3 units of standard deviation between the process average and the specification limits therefore this is a 3 sigma process (short term).
Exercise 1 Calculating the Yield
USL
USL
LSL
LSL
USL-XZ =
σ̂1.06-1
Z = 3.02
LSL-XZ =
σ̂.94-1
Z = 3.02
Using tables or software to look up the area under the curve when Z=3 we find .9986
Again using tables or software to look up the area under the curve when Z=-3 we find .00135.
Subtracting the two we find a yield of .9973
Exercise 2
Assume a process owner has asked you to analyze the data in Process Capability Exercise 1.MTW. Parts A and B are made on different machines in lots (subgroups) of 5. The customer has established specification limits of 10 ± .1 and requires a Ppk of 1.33.
Prepare a brief presentation to describe your analysis and recommendations? Remember to present data practically, graphically and analytically.
Exercise 2 Normality Tests
10.210.110.09.99.8
99.99
99
95
80
50
20
5
1
0.01
Part A
Perc
ent
Mean 10.00StDev 0.05049N 750AD 0.420P-Value 0.324
Probability Plot of Part A
Worksheet: Process Capability Exercise 1.MTW
Normal
10.210.110.09.99.8
99.99
99
95
80
50
20
5
1
0.01
Part B
Perc
ent
Mean 10.00StDev 0.05647N 750AD 0.248P-Value 0.752
Probability Plot of Part B
Worksheet: Process Capability Exercise 1.MTW
Normal
No reason to reject the assumption of normality for either part.
Exercise 2 Process Capabilities
Exercise 2 Part A Process Capability
10.1210.0810.0410.009.969.929.88
LSL Target USL
LSL 9.9Target 10USL 10.1Sample Mean 10.0009Sample N 750StDev(Within) 0.0496334StDev(Overall) 0.0504922
Process Data
Cp 0.67CPL 0.68CPU 0.67Cpk 0.67
Pp 0.66PPL 0.67PPU 0.65Ppk 0.65Cpm 0.66
Overall Capability
Potential (Within) Capability
% < LSL 1.87% > USL 2.80% Total 4.67
Observed Performance% < LSL 2.10% > USL 2.30% Total 4.40
Exp. Within Performance% < LSL 2.28% > USL 2.49% Total 4.77
Exp. Overall Performance
WithinOverall
Process Capability of Part A
Worksheet: Process Capability Exercise 1.MTW
Exercise 2 Prepare the Control Charts
Control Chart Shows Process Stability
1361211069176614631161
10.05
10.00
9.95
Sample
Sam
ple
Mean
__X=10.0009
UCL=10.0675
LCL=9.9343
1361211069176614631161
0.2
0.1
0.0
Sample
Sam
ple
Range
_R=0.1154
UCL=0.2441
LCL=0
444
4
Xbar-R Chart of Part A
Worksheet: Process Capability Exercise 1.MTW
Process Capability Part B
10.1410.0810.029.969.909.84
LSL Target USL
LSL 9.9Target 10USL 10.1Sample Mean 9.99961Sample N 750StDev(Within) 0.0496334StDev(Overall) 0.0564727
Process Data
Z.Bench 1.71Z.LSL 2.01Z.USL 2.02Cpk 0.67
Z.Bench 1.43Z.LSL 1.76Z.USL 1.78Ppk 0.59Cpm 0.59
Overall Capability
Potential (Within) Capability
% < LSL 4.13% > USL 4.00% Total 8.13
Observed Performance% < LSL 2.24% > USL 2.16% Total 4.39
Exp. Within Performance% < LSL 3.89% > USL 3.77% Total 7.66
Exp. Overall Performance
WithinOverall
Process Capability of Part B
Worksheet: Process Capability Exercise 1.MTW
Control Chart Shows Time Based Variation
1361211069176614631161
10.05
10.00
9.95
9.90
Sample
Sam
ple
Mean
__X=9.9996
UCL=10.0662
LCL=9.9330
1361211069176614631161
0.2
0.1
0.0
Sample
Sam
ple
Range
_R=0.1154
UCL=0.2441
LCL=0
51
1
1
51
111
1
11
51
1
444
4
Xbar-R Chart of Part B
Worksheet: Process Capability Exercise 1.MTW
Confidence Intervals
About This Module…
\DataFile\PurchOrd.mtw\DataFile\PwrSuply.mtw\DataFile\Conf-Int.mtw\DataFile\OEack.mtw
Six Sigma, A Quest for Process PerfectionMeet Goals and Attack Variation
Confidence Intervals (CI) permit us to state that we
are X% confident that the population parameter of
interest is at most a specified interval from the
sample statistic.
1. Significance of confidence intervals
2. How to calculate confidence intervals for:
– Means
– Standard deviations or Variation
What We Will Learn...
Mean and Standard Deviation statistics are:– estimates of the population Mu’s (m) and
Sigma’s (s) – based on one sample
Variability exists from sample to sample
By using statistically based confidence intervals, uncertainty can be quantified
Usually, 95% confidence intervals are calculated
Confidence in the Midst of Uncertainty?
The chances are approximately 95 out of 100 that the calculated confidence interval contains the population parameter, or…
With 95% certainty, the population parameter is inside the confidence interval.
Nin
ety-
five
Per
cent
Cer
tain
Population vs. Sample
Population
Sample
How representative is this sample?
Population is the entire area of interest.
Sample is a subset of the population.
What is the relationship between the population and the sample?
Confidence Interval Symbols and Definitions
Measure PopulationParameter
SampleStatistic
Use
Mean
Z ÷øöç
èæ ³30n
t ÷øöç
èæ <30n
X
Variance s2 2cs2
StandardDeviation s 2cs
ProcessCapability
Cp 2c
Proportion pF or Z (approx)
Alpha Risk a Typically.05
m
Cp^
^p
s is known
Confidence Intervals (CI)
CI take the general form :
C.I.=Statistic +/- K * (Standard Deviation)
Statistic= Mean, Variance, CP, etc.
K = Constant based on a statistical distribution
CI reflect the sample to sample variation of our point estimates
We will look at CI for: m , sX , and C P
The Student t distribution is a family of bell shaped (Normal like) distributions that vary by degrees of freedom (sample size) - the fewer degrees of freedom, the wider and flatter the distribution.
What is the Student t-distribution?
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
-4-3
.5 -3-2
.5 -2-1
.5 -1-0
.5 00.
5 11.
5 22.
5 33.
5 4
DF2 DF10 DF30
t-Distributions, Normal Approximation, Risk
STATISTICS FOREXPERIMENTERS-- BHH
To give an idea of the values of t compared to Z for 95% ( a = 0.05), look at the table below:
Sample t-value Z-value 5 2.78 1.96 10 2.26 1.96 20 2.09 1.96 30 2.05 1.96 100 1.98 1.96 1000 1.96 1.96
ta/2=0.025 a/2= 0.025
a = risk
We can use Z to estimate t if
and s is known30n ³
Hypothesis Testing
About This Module…
Six Sigma, A Quest for Process PerfectionMeet Goals and Attack Variation
Hypothesis Testing helps: Determine if there is a statistically significant
difference between two relatively small samples Quantify the risks of making an incorrect decision
1. How to test variable dataa. Use a t-test to compare two means b. Alpha (a) and Beta (b) Risksc. Use a paired t-test to compare paired
treatmentsd. Use test for equal variances
2. How to test discrete dataa. Compare proportionsb. Compare discrete data
What We Will Learn
Design:Determine if two alternate design changes are significantly different.
Manufacturing:Determine if two different types of material wear differently.
Administrative/Transactional / Service:Determine if the change to a process affected the cycle time.
Real World Scenario
Purposes of Hypothesis Testing
Determine if there is a real difference between ? and ? .
Use relatively small samples to answer questions about the population.
Quantify the associated risks.
ExampleOld Design New Design
89.7 84.781.4 86.1
84.8 91.987.3 86.379.7 79.385.1 86.2
81.7 89.1
83.7 83.784.5 88.5
To answer this, we need some fundamentals of significance testing first!
Hard disk transfer speed (megabytes per second) is marginal. A new design is proposed.
An Engineering Change Notice (ECN) is incorporated
Is the new design better?
Steps in Hypothesis Testing
1. Define the problem
2. Determine the objectives
3. Establish the Hypothesis– Write the Null Hypothesis
(H0)– Write the Alternative
Hypothesis (Ha)
4. Determine the appropriate statistical test (assume distribution Z, t, F)
5. State the alpha risk (usually 5 %)
6. State the beta risk (usually 10-20 %)
7. Establish the effect size (delta)
8. Compute the sample size
9. Develop a sampling plan
10.Select the samples
11. Conduct the test and collect data
12.Calculate the test statistic (Z, t, or F) from the data
13.Determine the probability that the calculated test statistic has occurred by chance
14. If that probability is less than alpha, reject H0
15. If that probability is greater than alpha, do not reject H0
16.Translate the statistical conclusion into a practical solution
Used to assess evidence provided by sample data to reject, or fail to reject a claim about a population parameter.
Null hypothesis (Ho) is the statement we assess.
Ho is usually stated as, “there is no difference”.
Alternate hypothesis (Ha) is usually stated as “there is a difference”.
We fail to reject Ho unless there is convincing evidence to reject it.
Ho
Ha
Ho
Ha
Ho p p
Ha p p
a b
a b
a b
a b
a b
a b
:
:
:
:
:
:
m mm ms ss s
=
¹
=
¹
=
¹
Typical Examples
Significance Tests
What does 5% Level of Significance Mean?
This means that we will reject the null hypothesis if
the difference between the sample statistic and the
hypothesized population parameter is so large that
it would occur, on an average, only 5 or fewer
times in every 100 samples when the
hypothesized population parameter is correct.
This risk is typically set at 5%.
Type I and II Errors: Associated Risks
Type I errors are made when we reject the null hypothesis when in fact it is true.
Type II errors are made when we fail to reject the null hypothesis when in fact it is false.
Alpha (a) risk is the probability of making a type I error.
Risks are set before the test or experiment is conducted
This risk is typically set at 10%
Beta (b) risk is the probability of making a type II error.
Ho not rejected Ho rejected
Ho should not be rejected (Ho is true)
CorrectDecision
Type II orconsumer’s risk = b P(Type II)
Ho should be rejected (Ho is false)
Type I orproducer’s risk a = P(Type I)
CorrectDecision
a is the risk of finding a difference when there really isn’t one.b is the risk of not finding a difference when there really is one.
Action
State of Nature
The Risk Truth Table
Remember:
a is the risk of finding a difference when there really isn’t one.
b is the risk of not finding a difference when there really is one.
b a
Ho Ha
Now we can determine if the ECN improved performance
Another Look at Risks
Normal Distribution and t Distribution
When Population SD is Known
When Population SD is Not Known
Sample size n is > 30
Normal distribution, z table
Normal distribution, z table
Sample size < 30, and we can assume population is approx normal
Normal distribution, z table
t distribution, t table
P Value
P value is the smallest level of significance that
would lead to rejection of the null hypothesis Ho.
eg. supposing Ho were true, what is the
probability of getting a value of x-bar this far from
the population mean? This probability is called a
prob value or p-value.
Manual Test Null Hypothesis m1 † m2
2 21 2
1 2 ,1 2
Difference Upperbound *
Difference Upperbound -1.99 1.7459*1.57
Difference Upperbound .756
df
s sX X t
n n
The upper bound for the difference in the means indicates the difference between the means of these populations could be as great as .756 (at the 95% confidence level). Therefore, the evidence is not statistically significant to conclude that the difference between the new design and the old design is less than 0. Fail to reject Ho.
Manual Test Null Hypothesis m1 † m2
1 2( , ) 2 2
1 2
1 2
-1.26
.112
df
X Xt
s sn n
P
P> .05 therefore fail to reject Ho.
Hypothesis Testing Decision Tree
Ho: M1=M2=M3…Ha: At least 2 are differentMinitab: Stat-Nonparametric-Mann-Whitney (or) Stat-Nonparametric-Kruskal-Wallis (or) Stat-Nonparametric-FreidmansM1=Median sample 1, etc.
Ho: M1 = Target Ha: M1 TargetMinitab: Stat-Nonparametric-1 Sample - sign (or) Stat-Nonparametric-1 Sample Wilcoxon(Also used for paired comparisons Ho: M1-M2=0)M1=Median or sample 1M target = Target Median
HypothesisTesting
Continuous Data(One factor only)
Attribute Data
Contingency Table
Proportions Testing (2 factors only)
Ho: 2 factors are independentHa: 2 factors are dependentMinitab: Stat-tables-Chi square test
Ho: P1=P2 Ha: P1 P2Minitab: Stat-Basic Stat-1or 2 proportions
Normality test
Ho:s1=s2=s3…Ha: At least 1 is differentMinitab: Stat-ANOVA-Test for Equal VariancesFor only 2 s, this is similar to an F-test: F=(S1)2/(S2)2If Fcalc>Fcrit, reject null(Use Chi-Squared for 1 sample)
Normal
2 or more samples
Levene’s Test
2 or More Samples
1 Sample
Ho: Data is NormalHa: Data is NOT NormalMinitab: Stat-Basic Stat-Normality TestUse Anderson-Darling
Chi-Square Bartlett’s Test/F-Test
Non-normal
1 Sample 2 or More Samples
1 Sample T Test
Paired T Test (Variance =)
One Way ANOVA
2 Sample T Test
Ho: s1=sTarget Ha: s1 s TargetMinitab: Stat-Basic Stat-Graphical SummaryIf s target falls within C1: then fail to reject Ho
Ho: m1=mTarget Ha: m1 m TargetMinitab: Stat-Basic Stat-1 Sample-T(Also used for paired comparisons:Ho: m1=m2=0)
Ho:s1=s2=s3… Ha: s1 At least 2 are differentMinitab: Stat-ANOVA-Test for Equal VariancesFor only 2 ss, this is same as F-test: Stat>BasicStat>2 VariancesF=(S1)2/(S2)2If Fcalc>Fcrit, reject Ho
Ho: m1=m2=m3=… Ha: m1 at least 2 are differentMinitab: Stat-ANOVA-One Way(Caution Bartlett’s p<0.05; assumes=variances)
Ho: m1=m2 Ha: m1 m2Minitab: Stat-Basic Stat-2 Sample-T(Compares Means using pooled Std Dev)Check box to assume equal variances orCheck box to assume unequal variances
2 SamplesHo: m1-m2=0 Ha: m1-m2 0Minitab: Stat-Basic Stat-Paired T(Compares Means when observations are paired or dependent in a pairwise manner)
1 Sample Z TestHo: m1=mTarget Ha: m1 m TargetMinitab: Stat-Basic Stat-1 Sample-Z(Also used for paired comparisons: Ho:m1=m2=0)Sample Size >=30 s is known
Regression and Correlation
About This Module…
\DataFile\Correlat.mtw\DataFile\Yarn.mtw\DataFile\Cases.mtw\DataFile\Water.mtw \DataFile\RMystery.mtw\DataFile\R-Exampl.mtw\DataFile\Callque.mtw\DataFile\Pizza.mtw\DataFile\Cases.xls\DataFile\CEO-COMPENSATION.xls\DataFile\Realestate.xls\DataFile\Oilcons.mtw
Six Sigma, A Quest for Process PerfectionMeet Goals and Attack Variation
Correlation Analysis is used to quantify:the degree of linear association between variables
Regression Analysis is used to quantify:the functional relationship between variables
What We Will Learn1. Correlation
– How to measure the linear relationship between two variables
– The correlation coefficient
– Implication of the correlation coefficient “r”
2. Regression
– Definition of the regression line and how it is developed
– How to calculate and analyze a regression equation
– How to analyze relationships between an independent variable
– and one or more dependent variables using regression
– How to interpret r2
– Understanding and analyzing residuals
– How to use the regression ANOVA table
ADMINISTRATIVE
A software company wants to know the relationship between calls in queue and service time.
MANUFACTURING
A customer and supplier disagree on the quantity received by customer versus several months’ quantity ordered for a given lead time.
DESIGN
A chemical engineer, designing a new process, wants to investigate the relationship between key input variables and stack loss of ammonia.
Real World Examples
Regression and Correlation
Regression and Correlation analyses show us
how to determine both the nature and the
strength of a relationship between two variables.
In regression analysis we develop an estimating
equation relating the dependent and independent
variables. i.e. how much percent of variation can
be explained by the regression equation.
In correlation analysis we determine the degree
to which the variables are related.
Regression Analysis
Used to fit lines and curves to data
The fitted lines
– Quantify the relationship between the process variables (X’s) and process performance (Y)
– Help identify the vital few X’s
– Enable predictions to be made
– Identify the impact of controlling the process variables (X’s)
Produces an equation to match the line
Terms
Correlation – A measure of linear association – Used when both X and Y are continuous
r values range from:– Perfect positive relationship = 1– No relationship = 0– Perfect negative relationship = -1
Regression – Provides the basis for predicting the values of a variable
from the values of one or more other variables– Used with a continuous Y and continuous Xs, or
continuous Y and categorical Xs
r2 - proportion of variation of Y explained by the prediction equation
A Word of Caution
• It is important that we consider the relationships
found by regression to be relationships of
association but not necessarily of cause & effect.
• That is unless we have specific reasons for
believing that the values of the dependent
variable are caused by the values of the
independent variable(s), do not infer causality
from the relationships we find by regression.
Correlation Illustrated
0
5
10
15
20
0 2 4 6 8 10 -30
-25
-20
-15
-10
-5
0
0 2 4 6 8 10
0
2
4
6
8
10
12
0 2 4 6 8 10
Correlation = 1 Correlation = - 1
Correlation = 0
Correlation Example
Is this reasonable? Are you comfortable with .959? What does it mean to you? How does the data actually look? How would you find out?
Correlation of Station 1 and Station 2 = 0.959, P-Value = 0.000
Two test stations are used to measure power supply voltage. Is there a correlation?
\DataFile\Correlat.mtw
Minitab: Stat>basic stat>correlation
The two are highly correlated (.959)
?
Plot the DataGraph>ScatterPlots
The Data
Station 2
Sta
tion 1
9.69.49.29.08.88.6
9.4
9.3
9.2
9.1
9.0
8.9
8.8
8.7
8.6
8.5
Scatterplot of Station 1 vs Station 2
Worksheet: Correlat.MTW
If all of the data points were on the diagonal line, would we have perfect correlation?
Let’s try regression
Regression
Fitted line plot is used when there is only one predictor.
Example 1 (cont.)
In what ways is this graph different from the preceding one?
What are the implications?
What action would you take?
Station 2
Sta
tion 1
9.69.49.29.08.88.6
9.5
9.4
9.3
9.2
9.1
9.0
8.9
8.8
8.7
8.6
S 0.0557288R-Sq 92.0%R-Sq(adj) 91.5%
Fitted Line PlotStation 1 = 1.020 + 0.8729 Station 2
Worksheet: Correlat.MTW
Slide 225 was actual line – this is a fitted line. Can be used for prediction.
ii bXa Y
By minimizing the residual sum of squares, we get a best fit line of the form:
a = coefficient of the constant term or intercept b = coefficient of the predictor, X
Best Fit Line
Test Piece
Case
s
100908070605040
100
90
80
70
60
50
40
S 11.5131R-Sq 49.4%R-Sq(adj) 47.7%
Fitted Line PlotCases = 22.47 + 0.7546 Test Piece
Worksheet: cases.MTW
Statistical Process Control
About This Module…
Six Sigma, A Quest for Process PerfectionMeet Goals and Attack Variation
Control charts portray process performance andseparate causes of variation:
• Random• Assignable
Control Chart Systems are:• A proven technique for improving productivity• Effective in defect prevention• Prevent unnecessary process adjustments• Provide diagnostic information• Provide information about process capability
\DataFile\Attribut mtw\DataFile\Variable.mtw
1. Control charts are a powerful tool to hold the gains.
2. How control charts discriminate between common cause and assignable cause variation.
3. Why control charts must be designed to fit the data type and the control purpose.
What We Will Learn.
Process Variation
Process variation is theresult of:• Common causes.• Special (assignable)
causes.
Common Causes
• Result in normal process variation.
• Are specific to each process.• Can be reduced by changing
the process.
Special (Assignable) Causes
• Are attributed to something outside of the process.
• Result in abnormal process variation.• Do not result in process improvement
if eliminated.
Uses of Control Charts
1) Attain a state of statistical control: • All subgroup averages and ranges within control limits - no
assignable causes of variation present
2) Monitor a process
3) Determine process capability
What happens after an out-of-control situation occurs at the core of a successful SPC program?
Juran’s Quality Control Handbook, 4th edition, page 24.7
General Concepts
w = some characteristic of interest
= mean of each sample
Sw = standard deviation of w
Upper Control Limit
Centerline =
Lower Control Limit
Therefore 99.73% of points will be within the control limits unless there is an assignable cause
WX
3 wUCL X S
3 wLCL X S X
Control Chart Selection Tree
Type of data
Count or Classification
Discrete
Fixed or variable
opportunity?
Count
C Chart
Fixed
U Chart
Variable Fixed or variable
opportunity?
Attribute
NP Chart
Fixed
P Chart
Variable
Subgroup >1?
Variable
IMR Chart
No
X Bar and Ror
X Bar and S
Yes
Supplement with EWMA if
CTQ is sensitive to
small process shifts
X and R Control Chart Formulae & Constants
2
4
3
X Control Limits =X ± A R
R Upper Control Limit = D R
R Lower Control Limit = D RSample
SizeA2 D3 D4 d2
2 1.880 - 3.267 1.1283 1.023 - 2.574 1.6934 .729 - 2.282 2.0595 .577 - 2.114 2.3266 .483 - 2.004 2.5347 .419 .076 1.924 2.7048 .373 .136 1.864 2.8479 .337 .184 1.816 2.970
10 .308 .223 1.777 3.078
Creating Control Charts for Variables
\DataFile\Variable.mtw
Creating an X-bar and R Chart
An X-Bar and R Chart
Sample
Sam
ple
Mean
45403530252015105
41
40
39
38
__X=40.000
UCL=41.294
LCL=38.706
Sample
Sam
ple
Range
45403530252015105
4.5
3.0
1.5
0.0
_R=2.243
UCL=4.743
LCL=0
5
1
66
1
11
1
1
1
Xbar-R Chart of measure1, ..., measure5
Worksheet: Variable.MTW
The numbers show violations of the assumption of control. The nature of the violation is given in the session window.
X-Bar and R Chart Session WindowTest Results for Xbar Chart of measure1, ..., measure5
TEST 1. One point more than 3.00 standard deviations from center line.
Test Failed at points: 7, 10, 13, 16, 17, 29, 46
TEST 5. 2 out of 3 points more than 2 standard deviations from center line (on
one side of CL).
Test Failed at points: 10, 17, 47
TEST 6. 4 out of 5 points more than 1 standard deviation from center line (on
one side of CL).
Test Failed at points: 7, 32, 34
* WARNING * If graph is updated with new data, the results above may no
* longer be correct.
StatGuide Interprets the Tests
Comparing the Suppliers
Sample
Sam
ple
Mean
24222018161412108642
41
40
39
__X=39.894
UCL=41.207
LCL=38.580
Sample
Sam
ple
Range
24222018161412108642
4
2
0
_R=2.278
UCL=4.816
LCL=0
Sample
Sam
ple
Mean
24222018161412108642
42
40
38
__X=40.106
UCL=41.384
LCL=38.829
Sample
Sam
ple
Range
24222018161412108642
4
2
0
_R=2.214
UCL=4.683
LCL=0
1
5
1
5
56
5
1
11
1
1
Xbar-R Chart of measure1, ..., measure5
Worksheet: Variable.MTW(Supplier = 1)
Xbar-R Chart of measure1, ..., measure5
Worksheet: Variable.MTW(Supplier = 2)
Supplier 2’s process is less stable than Supplier 1’s process.
Add Dates to Control Charts
Adding dates to the control charts may help identify potential sources of shifts.
Adding Dates Indicates When the
Shift Occurred
9/19/20069/13/20069/7/20069/1/20068/28/20068/22/20068/16/20068/10/20068/4/20067/31/2006
12
11
10
9
Date
Sam
ple
Mean
__X=10.568
UCL=11.850
LCL=9.286
9/19/20069/13/20069/7/20069/1/20068/28/20068/22/20068/16/20068/10/20068/4/20067/31/2006
4.5
3.0
1.5
0.0
Date
Sam
ple
Range
_R=2.222
UCL=4.699
LCL=0
2
222
22
6
5
666
Xbar-R Chart of Stacked Data 1s
Worksheet: Variable data.MTW
Detecting Gradual Process Drift
Sample
Sam
ple
Mean
403632282420161284
12
11
10
9
__X=10.568
UCL=11.850
LCL=9.286
Sample
Sam
ple
Range
403632282420161284
4.5
3.0
1.5
0.0
_R=2.222
UCL=4.699
LCL=0
2
22
22
2
6
5
6
66
Xbar-R Chart of Stacked Data 1s
Worksheet: Variable.MTW
The tests detect the process shift but it would have been detected earlier if the control limits had been based on the first 20 data points.
Detecting Gradual Process DriftMinitab calculates control limits based on the entire data set be default. Freezing control limits detects shifts earlier than using the entire data set to calculate limits.
Sample
Sam
ple
Mean
403632282420161284
12
11
10
9
__X=10.112
UCL=11.360
LCL=8.864
Sample
Sam
ple
Range
403632282420161284
4.5
3.0
1.5
0.0
_R=2.164
UCL=4.575
LCL=0
2
22
22
2
222
2
1
2
1
6
66
5
Xbar-R Chart of Stacked Data 1s
Worksheet: Variable.MTW
Rational Subgrouping• Usually consecutive units• Must come from a single distinct population• Within subgroup, variation should be white noise only• Between subgroups should capture variation due to black noise
1) Subgroup needs to represent the distinct population
2) Establish minimum subgroup size to reflect the within variation
3) Establish sample frequency to capture the between variation
4) Collect data maintaining the sequential information
Donald J. Wheeler has six guiding principles for subgrouping in a rational manner.
• Never knowingly subgroup unlike things together• Minimize variation within each subgroup• Maximize opportunity for variation between subgroups• Average across noise not across signals• Treat charts in accordance with the use of the data• Establish standard sampling procedures
When to Increase Sample Size
If the sample size is too small, assignable causes may produce real effects that are relatively small and unimportant. In this case, it may not be economical to take action.
To minimize the number of these “nuisance” causes, the sample size should be increased using the following techniques:
• Identify characteristics• Determine logical nature of subgroups• Identify sampling sequence• Measurement methods proven to be accurate
1. Control charts are a powerful tool to hold the gains
2. How control charts discriminate between common cause and assignable cause variation
3. Why control charts must be designed to fit the data type and the control purpose
What We Have Learned.
Lean EnterpriseA Formula for Organizational Success
Agenda
1. Introduction to Lean, Wastes
2. 5S WPO & Visual Management
3. Standard Work
4. Value Stream Mapping
5. Quick changeover
6. Poka-yoke
7. Continuous Improvement
8. Kaizen Blitz
9. Starting Lean
Introduction to Lean and 7 Wastes
• Identify and Eliminate
the 7 Wastes
Brief History of Lean
• Craftsman to mass production
• Mass production to lean production
• Lean production: Ford to Toyota
– Frederick Taylor
– Taiichi Ohno
– Shigeo Shingo
– James Womack
• From shop floor to office and support functions
then to service industry
Craft Manufacturing
Late 1800’s
Car built on blocks as workers walked around Built by craftsmen with pride Components hand-crafted, hand-fitted Excellent quality Very expensive Few produced
Mass Manufacturing
• Assembly line - Henry Ford 1920s
Low skilled labor, simplistic jobs, no pride in work Interchangeable parts Lower quality Affordably priced for the average family Billions produced – identical
Model ‘T’
Lean History – Japan
• Sakichi Toyoda at his textile mills (20’s–30’s) • Toyota Motor Company’s Kiichiro Toyoda and
Taiichi Ohno made innovations (40’s) in assembly lines that provided efficient, customer-focused, streamlined processes with flow, variety, and short lead time—Toyota Production System (TPS); to face competition of GM and Ford after WWII when key need was flexibility.
• Taiichi Ohno and Shigeo Shingo developed Lean based on TPS
Lean Manufacturing
Cells or flexible assembly lines Broader jobs, highly skilled workers, proud of
product Interchangeable parts, even more variety Excellent quality mandatory Costs being decreased through process
improvement Global markets and competition.
What is Lean?
“A business system for organizing and managing product development, operations, suppliers, and customer relations that requires less human effort, less space, less capital and less time to make products with fewer defects to precise customer desires compared with the previous system of mass production.”
Lean Lexicon, Lean Enterprise Institute, 2003
Lean manufactuirng is aimed at the elimination of waste in
every area of production including customer relations,
product design, supplier networks and factory management.
The goal of Lean Manufacturing is to incorporate less
human effort, less inventory, less time to develop products,
and less space to become highly responsive to customer
demand, while at the same time producing top quality
products in the most efficient and economical manner.
Definition
• The term “lean” is used because leanuses “less”…
Labor SpaceCapital investmentMaterialsTime between the customer order and the
product shipment
Why Call it “Lean”?
Definition of Lean
Lean has been defined in many different ways –
“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 of perfection.”
Definition by the MEP Lean Network
Give the customers what they want, when they want it, and do not waste anything.
Definition of Value Added
Waste is any activity that does not add value to the final product for the customer.
• Value-added is an activity that transforms or shapes raw material or information to meet customer requirements.
• Non-value added is an activity that takes time, resources or space, but does not add to the value of the product or service itself.
• Non-value-adding, but necessary – does not add value to the product or service but is required (e.g., accounting, governmental regulations, etc.).
Waste
“Anything that adds Cost
to the product
without adding Value”
“Anything that adds Cost
to the product
without adding Value”
Toyota Way – the 14 Principles by Jeffrey K. Liker
1. Base management decisions on long-term philosophy, even at expense of short-term financial goals.
2. Create continuous process flow to bring problems to surface.
3. Use pull systems to avoid overproduction.
4. Level out workload (heijunka); work like a tortoise, not a hare.
5. Build culture of stopping to fix problems, to get quality right first time.
6. Standardized tasks are the foundation for continuous improvement and employee empowerment.
7. Use visual controls so no problems are hidden.
8. Use only reliable, thoroughly tested technology that serves people and processes.
372
Toyota Way - 14 Principles (cont.)
9. Grow leaders who thoroughly understand work, live
philosophy, and teach others.
10.Develop exceptional people and teams that follow company’s
philosophy.
11.Respect extended network of partners and suppliers by
challenging them and helping them improve.
12.Go and see to thoroughly understand situation (genchi
genbutsu).
13.Make decisions slowly by consensus, thoroughly considering
all options; implement decisions rapidly.
14.Become a learning organization through relentless reflection
(hansei) and continuous improvement (kaizen).
373
Liker Model
Philosophy
Problem Solving
Process
People and Partners
Challenge
GenchiGenbutsu
Respect and Teamwork
Kaizen
Toyota Terms
374
Liker Model - 4 Ps1. Philosophy
• Long-term thinking even at expense of short-term financial goals
2. Process • Eliminate waste by focusing on flow, pull, workload
balance, error reduction, standardization, visual controls, and jidoka or use of reliable, tested technology/automation with mistake proofing and human touch
3. People and Partners• Respect, develop, and challenge people
4. Problem Solving • Fix and prevent problems by continual learning, going to
place where problem occurs, getting hands dirty, and making good decisions based on fact
What Is Lean?
Lean is a methodology
• that allows organizations to drastically improve
bottom line
• by improving processes and monitoring everyday
business activities to reduce errors
• in ways that increase value and minimize work, non-
value-add tasks, and waste while increasing
customer satisfaction
- Based on idea that faster processes yield less waste,
less cost, less work in process, less complexity,
higher quality, and happier customers
Womack and Jones Model
1. Define value from customers’ perspective
2. Document value stream
3. Improve flow of value stream
4. Drive for pull versus push
5. Continuously improve
Lean Principles
• Create value for customer
• Understand:
– Who is customer – person or entity who is
recipient of product or service; one who places
value on output; catalyst/trigger in value chain• Another business
• Someone inside own business
• Specific individual, group, or team
• Consumers—ultimate customer
– What customer considers valuable
• Make value flow based on customer’s needs
Lean Principles (cont.)• Consider life cycle of information, materials,
processes, products, and services• Look for process problems that prevent people
from performing best work• Eliminate waste
– Non-value-add steps– WIP– Cost
• Standardize work• Do not become distracted by other stakeholders
Value-Add Quiz In which category should the following be
placed?Activity Value Add Type 1 Type 2
Attending weekly team coordination meeting
Filtering through daily e-mail list
Reporting status to upper management
Gaining multiple approvals on documents
Gaining management approval for routine actions
Expediting document through approval list
Writing formal policies and procedures
Writing brief work-method instructions
Gaining regulatory or agency approvals
Creating ISO 9000 documentationHunting for needed information to do your job
Building “best practices” database
Holding lessons learned meeting
Spending time on process improvements
Lean vs. Traditional
Lean• Simple and visual signals• Demand driven• Inventory as needed• Reduce non-value added• Small lot size• Minimal lead time• Quality built• Value stream managers
Traditional• Complex• Forecast driven• Excessive inventory• Speed up value-added work• Batch production• Long lead time• Inspected-in• Functional departments
Benefits of Lean Manufacturing
Helps in – • Cost reduction• Cycle time reduction• “Waste”
minimization• Elimination of non-
value-added activities
• Resulting in a more “lean,” competitive, agile, and market-responsive company
Real Results
0 50 100
Lead TimeReduction
ProductivityIncrease
WIPReduction
QualityImprovement
SpaceUtilization
Why the Emphasis on Lean Now?• Global economy
• Pressure from customers for price reduction
• Fast-paced technological changes (e.g. Internet auctions)
• Continued focus on quality, cost, delivery
• Higher and higher expectations of customers
• Quality standards, such as QS-9000 (or TS 16949), the new ISO 9000:2000
• Holding on to “Core Competencies,”outsourcing the rest
• Market-driven pricing: Customers expect better performance at lower prices year after year
Evolution of Lean Across Markets
• Proven global concept since 1980s• Transformed business processes across
many industries:– Automotive– Aerospace
• Other industries beginning to embrace Lean concepts with excellent results:
– Construction– Hospitals – Pharmaceutical Manufacturing – Service Organizations
Pricing Model
Old Way
Cost + Profit = Price
New Way
Price - Cost = Profit
CustomersDemandLowerPrices
If CostsStay theSame
ProfitsDecrease
CostsIncrease
IncreasePrice
MaintainProfits
Whatcan we
do?
Pricing Model
Old Way
Cost + Profit = Price
New Way
Price - Cost = Profit
CustomersDemandLowerPrices
CostsIncrease
IncreasePrice
MaintainProfits
ImplementLean
IncreasedProfits
Core Concepts of Lean
• Creativity before Capital• A solution that is not-so-perfect implemented
today, is better than a perfect solution that is late. “Just do it.”
• Inventory is not an asset, but a waste/cost.• Typically, 95% of lead-time is not value added.• Lean implementation using the Plan-Do-Check-
Act methodology• Continuous Improvement environment: both
incremental and breakthrough.• Lean is a never-ending philosophy.
Aluminum Can Example
Bauxite Cryolite Aluminum Cast Product
Rolled PlateSheetCans
• From aluminum ore to usable cans, it typically takes about 300 days
Guess what the total value-added time is?
3 hours
Video
• Introduction to Lean
7 Wastes of Lean
“OMIT What U DO”• Overproduction• Motion• Inventory• Transportation (Movement)• Waiting• Defects (Correction)• Over-processing• Underutilized People
COMMWIP
Overproduction
Making more-earlier-faster than the next process needs it
• Just in case logic• Unbalanced workload• Unleveled scheduling• False sense of efficiency
• Printing 20 copies of a report that only 3 people look at
• All-staff e-mails when it pertains to only a few
• Waiting to “batch” work
Motion
Any movement of people that does not add any value to the product or service
• Poor layout• Inefficient Workplace
Organization• Lack of Standardization,
inconsistent work methods
• People, Material and Machine Ineffectiveness
• Where is are copier, printer, files and coffee-maker located?
• How far does the paperwork travel?
Inventory
Any supply in excess of one-piece flow
• Just in case logic• Unbalanced
workload• Unleveled scheduling• Unreliable suppliers• Reward system• “Pack rat” mentality
• Printed forms or tags that become obsolete
• 8 weeks of paper located by the copier
• How many pens do you have in your desk drawer?
Transportation
Moving people, materials and information around the organization
• Poor layout• Inefficient “flow”• Carrying large
quantities
• Moving “banker’s boxes to a storage area
• Mail carts• Messenger services
Waiting
Waiting for… man, machine, materials, information etc.• Just in case logic• Unbalanced workload• Unleveled scheduling• Unplanned downtime• Needs not
understood
• Waiting for files or information
• Need a signature• Customer reply to a
voice-mail or e-mail• Someone is printing
50 copies of a 70 page report
• Starting a meeting
Defects
Information, products and service that need correction• Not using Jidoka or
Poka-yoke• Lack of Standardization,
inconsistent work methods
• Ineffective communication
• Little investment in training
• Have to fix paperwork that is not completely filled in or track down the right person to get the information
• An entry error causes the wrong actions like shipping too many, or too few to the wrong address, etc.
Over-processing
Effort that adds no value to the product orservice from the customer’s standpoint
• Just in case logic• Inconsistent work
methods• Ineffective
communication• Redundant approvals• Excessive information,
extra copies
• Multiple sign-offs or checks
Underutilized People
Not utilizing people’s experience, skills, knowledge, creativity
• Not utilizing Teams• Organization
structure• Poor hiring practices• Little investment in
training
• Lack of suggestions• “That’s not my job”
attitude• Waiting for lead from
management
Mura and Muri
• Mura (unevenness) – variation in operation,
wasted resources when quality, cost, or delivery
cannot be predicted
– Testing/inspection, Containment, Rework,
Returns, Overtime, Unscheduled travel
• Muri (overdoing) – unnecessary or unreasonable
overburdening of people, equipment, or systems
when demand exceeds capacity or tasks are not
designed properly including harmful, wasteful, or
unnecessary tasks
Building Blocks of Lean
Change Management
5SVisualLayout Standard Work
Batch Size ReductionPOUS
Autonomation
JIT
Quick Changeover
Pull System & KanbanCellular & FlowTPM
VSM
Continuous Improvement & Kaizen Blitz
Self InspectionPoka-yoke
Teams
Building Blocks of Lean
Change Management
5SVisualLayout Standard Work
Batch Size ReductionPOUS
Autonomation
JIT
Quick Changeover
Pull System & KanbanCellular & FlowTPM
VSM
Continuous Improvement & Kaizen Blitz
Self InspectionPoka-yoke
Teams
5 Words that begin with “S”
Japanese Translation Conversion *Other
Seiri Organization Sort Sorting
Seiton Neatness Set in order Simplifying access
Seison Cleaning Shine Sweeping
Seiketsu Standardization Standardize Standardize
Shitsuke Discipline Sustain Self-discipline
* There are several other conversions
1
Clear/Sort
By red tagging
2
Organize/Straighten
A place for
everything
3
Clean/Sweep
Housekeeping /
Inspection
4
Maintain/Standardize
Establish standards
5
Continuous Improvement
Sustain
Discipline
Waste
5 Steps to Workplace Organization
Workplace Scan
“Understand your Current State”
• Start with a workplace Scan
• Team Based
• Define the boundaries
• Complete a Diagnostic Checklist
• Draw a Spaghetti Diagram
• Take “Before” Photos
• Starts the 5S Program
Workplace Scan Display
ChecklistScore
AreaDetails
Spaghetti Diagram
AfterPhotos
BeforePhotos
Sort
“When in doubt, move it out”
• Move unneeded items out of the area
• Use the Red Tag Technique
• Use a Temporary Red Tag Holding Area
• Criteria for unneeded items
– “30-day Rule”
• Keep only what you need in the area
Name____ Date___
Item _____________
Reason _________
Set in Order
“A place for everything and
everything in its place.”
• Make it easy for anyone to find
– “30-second Rule”
• Make it obvious if an item is out of place
• Decide where to keep items, how many items to
keep, how and when to replenish items
• Make it Visual
Shine
“Clean and Inspect”
• Get items to a like-new condition
– “10 Second Rule”
• Must plan Shine – assignments & supplies
• Perform as a Team
• Prevent dirt, grime, or contamination
• Repair as needed
Standardize
“Create the rules and follow them”
• Determine how the first 3S conditions are
met
• Use “One-Point Lessons”
• Maintain and monitor the conditions
• Use Visual techniques
Sustain
“Make 5S a habit”
• 5S is not something additional, it is part of
everyone’s daily job
• Supports discipline
• Train
• Communicate
• Support from Management
• Reward and recognition
5S is Fundamental to Lean
• 5S is directly related to other Building
Blocks
– Teams
– Visual
– POUS
– Standard Work
– TPM
Point-Of-Use Storage
• Raw material and WIP are stored at
workstation where used, which reduces the
inventory that can be carried.
• Works best if vendor relationship permits
frequent, on-time, small shipments (JIT).
• Simplifies physical inventory tracking,
storage, and handling.
Carpenter Story
• Does the carpenter walk back to the toolbox every time a tool is needed?
• Which waste is this?
• What does the carpenter do?
Proximity
• Typically, up to 60% of time is spent on
finding/collecting items needed.
• Minimize non-value activities
• Store as close as possible and within reach
• Layout and workstation design should
accommodate required materials
• Try to use the packaging from the supplier
or have the supplier change packaging
POUS Components
• Have the:
– Information
– Parts & materials
– Tools & equipment
that you need to perform you tasks within reach
POUS Workplace Zones
• Items used most often (i.e., daily) should be kept within reach
• Items used less often (i.e., weekly) should be kept close-by
• Items used rarely (i.e., monthly) should be kept in the vicinity
Daily
Weekly
Monthly
Location of items
• Use horizontal
transfers and
gravity feeds when
possible
• Support heavy
objects
• Set items
ergonomically
• Must be
comfortable for a
day’s work
Benefits
• Supports 5S & Visual and other Building
Blocks
• Simplifies inventory tracking and accuracy
• Reduces waiting, inventory, motion and
transportation waste
Benefits of 5S
• Improved equipment reliability• Superior quality• Increased productivity• Better workflow• Enhanced Safety• Reduced inventory• More pleasant place to work• Impress customers
Video
• Introduction to 5S
Building Blocks of Lean
Change Management
5SVisualLayout Standard Work
Batch Size ReductionPOUS
Autonomation
JIT
Quick Changeover
Pull System & KanbanCellular & FlowTPM
VSM
Continuous Improvement & Kaizen Blitz
Self InspectionPoka-yoke
Teams
Visual
Signs, lines, labels and color coding
Why Visual?
• What you need to know
• Cockpit view
• Information sharing
How do you know where to park when you
drive to a shopping mall?
Does someone have to tell you where to
park?
How to Apply Visual
• Use Signs, Lines, Labels and Color-coding
• Charts, pictures, lights, scoreboards
• Kanban, Andon lights
• Inventory Levels
Examples
• Productivity Goals
• Quality Goals
• Delivery schedules
• Set-up specification
• Safety Initiatives
• Attendance Goals
• Team Objectives
More Examples of Visual
• Signs
• Charts
• Goals
• Pictures
• Color coding
• Lights
• Scoreboards
• VSM Current & Future
State
• Standard Work
instructions
• Tags• Forms• Training hours• Employees’ suggestions• Cross trained skills• Employee awards• Absenteeism• Critical maintenance points• Customer satisfaction goals• Performance targets
Visual Controls as Communication Tools• Visual controls expose waste so we can
reduce or eliminate it• Visual controls help in:
– Improving motivation & morale– Focus on safety– Pride of workplace & workmanship
• Visuals and performance metrics– What gets measured, gets done– Policies drive behaviors
World Class Visual Controls
• Anyone knows what’s going on by looking
around
• You do not have to wait for information to
do your job
• Everyone passes the 30 second test
Visual Examples
Andon Lights
Shadow Boards
Display Panels
Range MarkingsOn Gauges
Standard Work
Reduce task variability
Standard Work
Best sequence of operations, using the most
productive combination of resources:
• Man, machine, materials, changeovers,
etc.
• Details any special skill/knack needed
• Safety, ergonomics are integrated
• Tool for perfect quality and efficiency
Standard Work Properties
• Specific
• Measurable
• Repeatable
• Documented
Standard Work
Identifies value added versus non-value added activities
• Reduce or eliminate non-value added activities• Convert Internal Time to External Time,
wherever possible• Continuous Improvement: once Standard Work
is established as a base and displayed at workstations, operators monitor and implement improvements
• Use as a training tool for new employees• Created by input from the people who actually
work in the process
Philosophy of Standard Work
Be specific about:
• Content• Sequence• Timing• Outcome
Example: Installing a Car Seat
• Bolts are installed and tightened in the same exact order
• The time required to tighten bolts is stated and followed
• Specified torque is applied and checked
Used as the basis from where the next level of improvement is made.
Types of Standardized Work Forms
• Process Capacity Table
• Work Combination Sheet
• Standard Work Sheet
• Others forms may be used based on your
organization’s needs
Process Capacity TableTimes for:• Elapsed time• Element time• Internal Time• External Time• Manual Time
Step Identification• Transportation• Process• Inspection• Storage
Use to identify bottlenecks Use to calculate the capacity of machines, and identify bottlenecks
Process:Seq No. Element Symbol
Elapsed Time
Element Time
Internal Time
External Time
1 Review work order f or die number and material 600 600 300
2 Locate the die 1800 1200 300
3 Locate material 3000 1200 300
4 Get tools 3600 600 300
5 Tagout machine 4500 900 60
6 Loosen bolts 4980 480 60
7 Disconnect hoses 5280 300 60
8 Remove die f rom press 5580 300 120
9 Return die to Tool Room 6180 600 300
10 Load die into press 6480 300 90
11 Align die 6960 480 0 X
12 Tighten bolts 7440 480 60
13 Connect hoses 7740 300 60
14 Position material 8340 600 300
15 Clear tagout 8940 600 60
16 Make sample piece 9000 60 60
17 Take fi rst piece sample to QC 9600 600 120
18 Adjust die and press 10800 1200 0 X
19 Make sample piece 10860 60 0 X
20 Return tools 11460 600 600
750 2400
Changeover Analisys Chart
Date: Name: Shift:
NV
A =
X
Comments
Convert to External
Convert to External
Convert to External
Convert to External
Prepare Tags before
Use quick connects
Use quick connects
Position die cart
Convert to External
Use positive stops
Eliminate
Use quick connects
Use quick connects
Convert to External
Have QC Tech ready
Pre-adjust die
Transport Process Inspection Storage Total Time Page ____ of _____11460
Eliminate
Convert to External
Work Combination Sheet
Sequence of:• Manual work time• Machine
operations time• Walking
Shows the interactions between machines and operators
Allows to recalculate operator work content as takt time changes
B - Generators 24,600 Date:
Assembly Cell #23 200 Name:
Final Assembly 123 VS Mgr:
IDManual
OperationMachine
Operation Walking Start Manual OperationMachine OperationWalking1 12 32 0 44 0 0 12 32 02 3 0 2 5 44 49 3 0 23 1 16 2 19 49 68 1 16 24 45 120 0 165 68 233 45 120 05 2 15 3 20 233 253 2 15 36 23 41 2 66 253 319 23 41 27 42 0 0 42 319 361 42 0 08 35 0 0 35 361 396 35 0 09 5 0 4 9 396 405 5 0 4
10 0 0 0 0 405 405 0 0 011 0 0 0 0 405 405 0 0 012 0 0 0 0 405 405 0 0 013 0 0 0 0 405 405 0 0 014 0 0 0 0 405 405 0 0 015 0 0 0 0 405 405 0 0 016 0 0 0 0 405 405 0 0 017 0 0 0 0 405 405 0 0 018 0 0 0 0 405 405 0 0 019 0 0 0 0 405 405 0 0 020 0 0 0 0 405 405 0 0 021 0 0 0 0 405 405 0 0 022 0 0 0 0 405 405 0 0 023 0 0 0 0 405 405 0 0 024 0 0 0 0 405 405 0 0 025 0 0 0 0 405 405 0 0 026 0 0 0 0 405 405 0 0 027 0 0 0 0 405 405 0 0 028 0 0 0 0 405 405 0 0 029 0 0 0 0 405 405 0 0 030 0 0 0 0 405 405 0 0 0
168 224 13
41% 55% 3%
405
405Time PCS Rate
1 Work Flow Diagram2345
Throughput per shift = Available Time / Total Operating Time: Total Time (Cyclical + Non-cyclical):
seconds
pieces
seconds per piece I.C. Flow
Total Non-cyclic Time:
Time Available:
Demand:
Takt Time:
Non-cyclical Work Elements Seconds
Total Time:
Percent Operator Time:
Total Cyclic Time:
Load on cart
Start WC-1, go to WC-2Unload part, Load Part, Start Machine, go to WC-3Unload part, f ile corner, inspect to printLoad next part, start machine, go to WC-1Fasten parts A-1, and B-1 together, go to AS-2Fasten Housing and BasePackage generator
Description of Work ElementManually load WC-1
Product Family:
Process:
Description:
Cyclical Work Element Element Time Graph Data
January 31, 200X
Eileen N. Terprise
0 100 200 300 400 500
123456789
101112131415161718192021222324252627282930
Operation Times
WC-1 WC-2 WC-3
AS-1AS-1AS-1
Standard Work Sheet
Sequence of processing steps• Worker• Machine• Tools• Layout• Material location(Standard stock)
Displayed at Workstations
Continuously reviewed and updated
Standard Work Sheet
Product Family
B - Generators
Process
Assembly Cell #23
Description
Final Assembly
Supplier
Fab, Assm #17, SM-29
Customer
SM-FG48, Shipping
WC-1 WC-2
WC
-3
AS-1
FS-1
AS-2
3 2
1
2
12
3
1
Uses
• The Process Capacity Table can be used
to reduce changeover times
• The Work Combination Sheet can be
used for line balancing when creating a cell
• The Standard Work Sheet can be used for
training and team development
Standard Work Examples
Adobe Acrobat Document
Adobe Acrobat Document
Adobe Acrobat Document
Standard Work and Training
Questions to ask Operators about Standard Work• How do you do this work?• How do you know you are doing this work
correctly?• How do you know there are no defects?• What do you do if you have a problem?
If these questions cannot be answered satisfactorily, then either the Operator needs additional training or the Standard Work is unclear
Uses of Standard Work
• Consistent performance of tasks = better quality
• Track performance = actual versus standard for continuous improvement
• Easy to Train = reduced learning cycle time
Old Learning Curve
Time
Pro
duct
ivity
New Learning Curve
TimeP
rodu
ctiv
ity
Benefits of Standard Work
• Standard documentation for all shifts
• Reductions in injuries and strain
• Employee ownership of process
• More pleasant working conditions; higher
morale
• Better than traditional time and motion
studies
• Reduced variability
Poka-yoke
• Error proof (mistake proof) takes away the possibility of human error
• The term Poka-yoke was made popular by Shigeo Shingo
• Fail-safe devices• Low cost, highly reliable mechanisms • Detects abnormal situations before they occur,
or• Once they occur, will stop the equipment from
further production. The machine stoppage makes the problem visible.
Other Poka-yoke Examples
• USB ports on computers
• Re-typing passwords to verify
• Computer prompts before deleting file
• Bar codes & scanning
• ATM swipe card or beep
Benefits of Poka-yoke
• Gives immediate feedback for root cause
analysis & correction (and prevention for the
future).
• Failure Mode and Effect Analysis (FMEA) solution
can be Poka-yoke
• Some examples of Poka-yoke devices are:
sensors, counters, feelers, limit switches, electric
eyes, probes, automatic stops.
Building Blocks of Lean
Change Management
5SVisualLayout Standard Work
Batch Size ReductionPOUS
Autonomation
JIT
Quick Changeover
Pull System & KanbanCellular & FlowTPM
VSM
Continuous Improvement & Kaizen Blitz
Self InspectionPoka-yoke
Teams
Value Stream Mapping
See the Flow
Value Stream AnalysisValue stream analysis encompasses all activities company must do to design, order, produce, and deliver its products and services to customers – Flow of tasks, from request for service (trigger event)
to service complete, from receipt of materials or information from suppliers to delivery of finished product or service to customers
– From viewpoint of customer, service, or transaction– Flow of information that supports and directs both flow
of materials and transformation of raw materials or information into finished goods or services
FinanceHumanResources
OperationsPurchasing Sales
Value Stream
Value Stream
Purpose of Value Stream Map
• Has customers’ perspective and focuses on meeting customers’ wants and needs
• Starts with immediate customer and maps back to receiving inputs from suppliers and shows how fits into overall value stream
• Provides single view that is a complete, fact-based, and time-based representation of stream of activities
• Provides common language and view for analysis• Shows how information triggers and supports
activities• Shows time for activities and whether they add value
Elements of Value Stream Map• Process steps• Value-add classification for each step• Information flow such as orders, requirements, schedules,
messages, approvals, specifications, kanban signals, shipping information, standard procedures
• Box score of key operational metrics including cycle time, waiting time, working time, conveyance time, distance traveled, items per shift, items processed per hour,setup time, backlog/work-in-process, amount of inventory between last step and consumer, defects, cost information, resource availability and active time, process variations
• Lead time is amount of time for one item to flow completely through process, noted along bottom of flow
• Takt time showing customer demand rate, in upper right corner of flow
Value Stream Analysis Steps• Identify deliverable, value stream, and sponsor who has authority and
responsibility to allocate resources and make changes across organization
• Identify customer and value from customer’s perspective as well as regulatory, legal, and compliance requirements
• Draw visual representation of process current state, generally draw steps starting at consumer’s view working back through steps to sources of material and labor; flows from left to right with time, with steps in order of occurrence
• Add metrics and observations like Takt time/throughput, cycle times, defect rates, and inventory/work-in-process and information flows to identify magnitude and frequency of waste
• Use lean principles to reduce or eliminate waste and reduce cycle time
• Develop future state map, document steps of process that need to happen, and prioritize and implement action plans to achieve future state
Value Analysis Matrix Steps• Structure value analysis matrix• Number process steps on sub process map• Have column for each process step• Estimate time for each process step• Place check in category for each process step,
either value-add or one of non-value-add categories
• Total number of hours or number of checks for each row
• Report percentages of value-add and non-customer required
1Process Step
Time (Hours)
Value - Added
Non Customer Required
Internal Failure
External Failure
Control/Inspection
Delay
Prep/Set -Up
Move
Total
2 3 4 5 6 7 8 9 10 Total % Total
30%
100
52%52
6%6
100 100%10620101012 10 201 1
2 2%
30
100%
Ö Ö
Ö 10 10%
Ö
Ö ÖÖ
Ö Ö Ö
1Process Step
Time (Hours)
Value - Add
Non Customer Required
Internal Failure
External Failure
Control/Inspection
Delay
Prep/Set-Up
Move
Total
2 3 4 5 6 7 8 9 10 Total % Total
30%
100
52%52
6%6
100 100%10620101012 10 201 1
2 2%
30
100%
Ö Ö
Ö 10 10%
Ö
Ö ÖÖ
Ö Ö Ö
Value Analysis Matrix Example
RFQ Creation Value Stream Map
Gather
RequirementsAssign Buyer
C/T = 3 days
W/T = 4 hours
VA/T = ~ 0
Verify Customer
Requirements
C/T = 14 days
W/T = 2 days
VA/T = 1 days
Consult with Manu-facturing Engineer
C/T = 5 days
W/T = 2 days
VA/T = 4 hours
C/T = 14 days
W/T = 2 days
VA/T = 1 day
Customer Meetings
C/T = 14 days
W/T = 2 days
VA/T = 1 day
Create Preliminary
RFQ
C/T = 5 days
W/T = 2 days
VA/T = 1 day
Review and
Approval Cycle
C/T = 5 days
W/T = 1 day
VA/T = ~ 0
Create Final
RFQ
C/T = 5 days
W/T = 2 days
VA/T = 1 day
Review and
Approval Cycle
C/T = 5 days
W/T = 1 day
VA/T = ~0
Iterate
Revise
Triggering
Event
Release RFQ
C/T = 2 days
W/T = 1 day
VA/T = 2 hours
Continue
Revise
Continue
Measurable
Deliverable
As-Is Process Cycle Time*:
C/T = 58 daysW/T = ~14 daysVA/T = 5 days
C/T = Calendar Time
W/T = Work Time
VA/T = Value-Add Time
Assumes no revisions!
Wait for AvailableSales Person
Initial PhoneContact
C/T = 0W/T = 0VA/T = 0
C/T = 5 minutesW/T = 0VA/T = 0
Sales Pitch
C/T = 10 minutesW/T = 10 minutesVA/T = 10 minutes
Configure System
C/T = 30 minutesW/T = 30 minutesVA/T = 5 minutes
Fill Out Order Form
C/T = 10 minutesW/T = 10 minutesVA/T = 5 minutes
Promise to Ship
C/T = 5 minutesW/T = 5 minutesVA/T = 0
Pending Order “FIFO” Queue
C/T = 7 DaysW/T = 0VA/T = 0
Batch TogetherSimilar Systems
C/T = 6 DaysW/T = 1 DayVA/T = 0
Check Availabilityof Materials
C/T = 3 DaysW/T = 1 hourVA/T = 0
Issue Work Orderto Factory Floor
C/T = 1 DayW/T = 1 hourVA/T = 0
Mtl.Available
?
Yes
No
Change Ship Date
Time Customer is On Telephone
TriggeringEvent
MeasurableDeliverable
While customer is on telephone:
C/T = 60 min.W/T = 55 min.VA/T = 20 min.
From Contact to Order Launch:
C/T = 17 daysW/T = ~ 1 dayVA/T = 0
Sales Order Processing Value Stream Map C/T = Calendar Time
W/T = Work TimeVA/T = Value-Add Time
Customer buys salad with salmon
Grocer offers premade salads
Salad company makes salad and delivers to grocer
Salad company buys supplies
Processed salmon is shipped to fish
markets
Salmon is processed at
fishery
Fishers catch salmon
Mother nature makes salmon
Restaurant supply company distributes food
Farmers grow and harvest produce
Produce is package and shipped
Meat companies process animals
Farmers raise meat animals
Container company sells
containers
Manufacturers make
containers
Chemical producers make plastics from
petroleum
Oil refined for petroleum products
Buying a Salad Process Flow
Cycle Time Definition“One of the most noteworthy accomplishments in keeping the price of products low is the gradual shortening of the cycle time. The longer an article is in the process and the more it is moved about, the greater is its ultimate cost.”
Henry Ford, 1926
• Time that elapses from beginning to end of process• Ultimate objective or goal of Lean processes is to reduce cycle
time by eliminating waste
Work Errors, waiting, transportation, movement etc…..
Total Cycle Time
Benefits of VSM
• Helps you visualize more than the single
process level
• Links the material and information flows
• Provides a common language
• Provides a blueprint for implementation
• More useful than quantitative tools
• Ties together lean concepts and techniques
4 Steps for VSM
1. Determine the Product Family
2. Draw your Current State Map
3. Create the Future State Map
4. Develop your plan to get there
Current State Map
• Understanding how the floor currently operates– Material and Information flows– Draw using symbols– Start with the “door to door” flow– Have to walk the flow and get actuals
• No standard times• Draw by hand, with pencil and eraser
– Foundation for the future state
Current State Icons
Customers
Suppliers
Mon., Wed., Fri.
Shipment-Truck
Process Box
Painting
Data
BoxC/T=1 sec Cycle TimeC/O= 1 hr ChangeoverRel.= 98% ReliabilityFPY = 95% Quality
I Inventory
Push System
Operator
Go See
More Current State Icons
Train
Boat
Cell
Hardcopy
Electronic
Person
Plane
Fun Current State Icons
???
o
&@#$%!
Fax
Current State Map Setup
Tips• Use 11” x 17” paper, landscape• Use pencil and eraser• Draw by hand• Don’t waste time putting it on a computer just to
make it look nice (non-value added time)• Practice, practice, practiceSteps• Customer• Supplier• Process• Information flow• Calculate process time and lead-time
Current State Map Setup
Title Block
Process Time and Lead-time Area
Process Flow Area
Information Flow AreaCustomer
informationSupplier
information
Current State Map
Dewey, Cheatem & Howe
Daily
Phlye-Biknight
Weekly
Stamping Spot Weld Deburr Assemble
C/T=1 sec
C/O= 4 hrs
Rel.= 98%
C/T=39 sec
C/O= 11 min
Rel.= 99%
FPY = 90%
C/T=17 sec
C/O= 0 min
Rel.= 80%
FPY = 100%
C/T=48 sec
C/O= 5 min
Rel.= 100%
FPY = 98%
I I I I
=1 =1 =1 =2
Shared
2 Weeks 5,425 1,400 1,225
5,300 pcs/mo.265 pcs/day
Order Entry
MRPMonthly
Weekly
FPY = 95%
L/T= 2 days
P/T = 20 min
Prod Ctrl
MRP
WeeklySchedule
Daily
30/60/90Forecast
Weekly
1 sec 39 sec 17 sec 48 sec20.5 days 5 days 4.5 days10 days
20 min2 days
105 sec40 days
Future State Questions
1. What is the Takt Time?
2. Will we build to shipping or to a supermarket?
3. Where can we use continuous flow?
4. Where do we have to use supermarket pull system?
5. At what single point in the production chain do we trigger production?
6. How do we level the production mix at the pacemaker process?
7. What increment of work will we release and take away at the pacemaker process? (Leveling the volume)
8. What process improvements will be necessary? (e.g. uptime, changeover, training)
1. What is the Takt Time?
• Takt means drumbeat
• Ability to meet customers’ demand
• Formula
Takt Time = Time Available
Demand
Takt Time Calculation
Time available
Shift (8 hours) = 480 mins
Breaks (2 x10) - 20 mins
Lunch - 30 mins
Meetings - 5 mins
C/O - 5 mins
Total Time = 420 mins = 25,200 sec
Demand = 265 parts
Takt Time = 95 sec/part
Takt Time Calculation
• Takt Time = Demand Rate– Goal: Produce to demand with no excess
capacity• Takt Time = work time available number of
units sold• Assume 5 people work, sell 500
units/week:– Takt Time = (5 x 40 x 60) / 500 = 24 min/unit– Set cycle time to match personnel/operation– For three-step process, perfect is 8 min/step
Exercise
• Takt time calculation
Microsoft Office Word Document
Takt Time Calculation
• Old requirements: 847/day * 240 workdays/yr = 203,000/yr
• 10% growth = 223,600/yr• New requirements: 223,60/yr/240 workdays/yr =
931/day• Time available: 8.5 hrs/day - .5 hrs (lunch) - .33 hrs
(breaks) = 7.67 hrs/day• 3,600 secs/hr * 7.67 hrs/day = 27,612 seconds/day• 27,612 seconds/day divided by 931 units/day = 29.3
secs per unit • Cycle time (actually 116 secs/unit) divided by Takt
time (29.3 secs/unit) = 3.95 = 4 operators required
Quick Changeover
Changeovers in less than 10 minutes
Quick Changeover
• Factory definition – the time from the last
good piece of previous run to the next good
piece of new run
• Office definition – the time it takes to switch
from one task to a new task
– Typically, in the office the time savings is not as
significant as in manufacturing
2 Hour C/O – Large Batch Size
0
123
456
78
Mon Tue Wed Thu Fri
A B C D E
1 Hour C/O – Half Batch Size
0
123
456
78
Mon Tue Wed Thu Fri
A
B
C
D
E
A
B
C
D
E
10 Minute C/O – Small Batch Size
0
123
456
78
Mon Tue Wed Thu Fri
A
B
C
D
E
A
B
C
D
E
A
B
C
D
E
A
B
C
D
E
A
B
C
D
E
10 Minute C/O – Many Different Small Batches
0
123
456
78
Mon Tue Wed Thu Fri
A
B
C
D
E
F
B
CD
G
A
F
B
A
H
C
B
E
I
G
H
D
B
Changeover Summary
C/0 Time Number of Changeovers
Number of Production
Runs
Production Time
Available
2 Hour 5 5 30 hours
1 Hour 10 10 30 hours
30 Minute 15 15 32.5 hours
10 Minute 25 25 35.8 hours
Based on 40 hours per week
SMED
• Single Minute Exchange of Dies (SMED)
• Shigeo Shingo (1970)
1. Separate internal steps and external
steps
2. Convert internal steps to external where
ever possible
3. Streamline all steps
4 Categories of SMED time
1. Preparation, after-process adjustments, checking of material and tools (30%)
2. Mounting, removing tools and parts (5%)
3. Measurements, settings and calibrations (15%)
4. Trial runs and adjustments (50%)
30% 5%
15%
50%
Typical proportions
Step 1. Separate Internal and External Times
• Checklists
• Functional checks
• Transportation of parts and tools
Step 2. Convert Internal Time to External Time
• Preparation conditions– Pre-heat, correct air pressure, stage materials
• Standardize– Centering, gripping, securing, replace fewest
parts, standardize heights, standardize bolts or
fasteners
• Intermediary jigs– Mounting plates
Step 3. Streamline
• Parallel operations
– More than one person working at the same
time
• Eliminate adjustments
– Markings
– Scales
• Functional clamps
• Mechanization
Changeover Cart Example
Before• Waste of time to find
correct tools• Tools can become
damaged• Waste of money for extra
tools
After• Saves time• Do not have to replace
tools as often• Have what you need
where its needed
QCO and Other Building Blocks
• 5S, Visual, POUS, Teams and Standard
Work
• VSM can discover opportunities for QCO
• As Batch Size Reduction continues, QCO
becomes more important
• Kaizen Blitz is a great method to implement
QCO
• Must sustain the gains
Benefits of Quick Changeover
• Shorter lead time
• Less material waste
• Fewer defects
• Less inventory
• Lower space requirements
• Higher productivity
• Greater flexibility
• Better Teamwork
Building Blocks of Lean
Change Management
5SVisualLayout Standard Work
Batch Size ReductionPOUS
Autonomation
JIT
Quick Changeover
Pull System & KanbanCellular & FlowTPM
VSM
Continuous Improvement & Kaizen Blitz
Self InspectionPoka-yoke
Teams
Continuous Improvement
Kaizen vs. Kaizen Blitz, or Incremental vs. Breakthrough Improvements
Kaizen Incremental Improvements:• Are continuous, since there is always room for
improvement in any process• It is never-ending• Many small improvements throughout the enterprise• Done by individuals or small teams• Could be functional, departmental, or task-oriented• Part of the “useful many”• A little time spent on an ongoing basis• Standardization of processes
(i.e., process improvement oriented)• Plan-Do-Check-Act methodology
Continuous Improvement
Ideas for continuous improvement could come from:– Employee suggestions– Corrective & Preventive actions– Non-conformities, defects– Customer complaints, returns– Benchmarks– The Lean “wastes”– Variations from the standard– Assessments, audits & competitive analyses– Research & Development activities
Continuous Improvement & Continuous Learning
• Continuous Learning goes hand in hand with continuous improvement
• Management should have training given to employees in Lean and Quality tools, problem solving and root cause analysis, the process model, concepts of Theory of Constraints, basic statistical techniques, graphical tools, etc.
• Understanding of Plan-Do-Check-Act and Standardize-Do-Check-Act (SDCA) will be beneficial
Continuous Improvement & Continuous Learning
• Continuous improvement and learning:– Becomes part of daily work life– Is practiced at both personal, functional and
organizational levels– Is result oriented– Is shared within the enterprise– Becomes part of institutional memory and
knowledge, even after employees retire, move up/laterally or leave
Why C. I.?• Standing still is not an option:
– Competitors will overtake us– Globalized economy– Higher customer expectations– Technical and breakthrough changes– Tapping into human potential and creativity
• Improvements based on:– Cost and cycle time reduction– “Waste” minimization– Defect prevention– Enhancing customer satisfaction/delight– Attaining competitive advantage
Kaizen Blitz
• Breakthrough strategies for lasting results
Building Blocks of Lean
Change Management
5SVisualLayout Standard Work
Batch Size ReductionPOUS
Autonomation
JIT
Quick Changeover
Pull System & KanbanCellular & FlowTPM
VSM
Continuous Improvement & Kaizen Blitz
Self InspectionPoka-yoke
Teams
Kaizen Blitz
• Kaizen Blitz is a combination of the Japanese word Kaizen for “continuous improvement” and the German word Blitz for “lightning.” It is a focused, week-long workshop where a cross-functional team reviews a process, identifies and eliminates waste, thereby achieving dramatic and tangible breakthrough (rather than incremental) improvement results.
• Kaizen Blitz now stands to mean the improvement activity itself.
• It is treated more as a “Project” (rather than a “Process”).
Why Kaizen Blitz?• Major benefits in a flash.• Can use benchmarking for setting goals.• Innovation has become indispensable in today’s
competitive world economy.• Cycle Time Reduction translates directly to cost
savings.• Kaizen Blitzes typically attack wasted time.• Positive impact on organizational culture through
“breakthrough” type improvements.
Who Will be Involved?
• Kaizen Blitz teams that come together for one week to implement improvements in a pre-selected bottleneck project or process.
• Cross-functional teams (seven to ten persons)• Hourly and salaried personnel• Operators, engineers, supervisors, maintenance persons,
managers, technical experts, material handlers, quality personnel, business support personnel, participants from the outside
• Typically, the Team Leader is person with clout and is the highest stakeholder in the process who possess leadership skills, open minds, strong desire to succeed and some prior Lean experience.
Kaizen and Cycle Time Reduction
• Focus on Process.
• Focus on Elimination of Waste.
• Focus on Speed.
• Time improvement translates directly to cost savings and customer satisfaction.
Kaizen Blitz Steps
1. Select specific area for improvement.
2. Define current situation in measurable terms
3. Set aggressive goals (stretch goals).
4. Identify team members.
5. Conduct training on the first day of the project.
6. Do it (in three to five days).
Step 1 – Select Project
• Value Stream Map• Bottlenecks• Customer or quality related issues• Interdepartmental• Long lead-times or setup times• Competitive advantage• Cost reduction or avoidance
Step 2 – Define Current State
• Video tape• Time study• Flowchart• Historical information• Observations and interviews
Step 3 – Identify Team Members• Cross-functional teams (seven to ten persons)• Hourly and salaried personnel• Operators, engineers, supervisors, maintenance persons,
managers, technical experts, material handlers, quality personnel, business support personnel, participants from the outside
• Typically, Team Leader is person with clout and is the highest stakeholder in the process. Ideally, the team leader must possess leadership skills, open minds, strong desire to succeed and some prior “Lean” experience.
Step 4 – Set Aggressive Goals• Define the purpose or objective and set stretch
goals.• Goals should be clearly defined and quantifiable
(e.g., reduce machine set up time by 75%, increase throughput by 40%, reduce floor space by 30%).
• Emphasis should be on identifying and eliminating waste, and then standardizing at the improved level.
• Benchmark when possible
Step 5 – Conduct Training
• Select hands-on training that is compatible with the project
• Do training on the first morning• Provided by an internal or external expert
Step 6 – Do it!
• Perform in 3 to 5 days
Example 1 – Universal Joint QCO
Category Changeover Tool Change
Target savings 4.9 hours (75%) 14.8 hours (75%)
Actual savings 4.5 hours (69%) 13.8 hours (70%)
Target savings per day $291 $879
Actual savings per day $268 $820
Total savings $272,041 per year
Example 2 – Tube Mill SMED
• Changeover savings per year: $510,000• Reduced changeover time from 4 hours, 40
minutes to 2 hours, 11 minutes• Employees happier – bonuses based on
changeovers• Management happier – more changeovers,
more production, more cash in the door
How to Start and Sustain your Lean Journey
• A journey of one thousand miles, starts with a single step
8 Ways to Get Started
1. Baseline Assessment or Gap Analysis
2. Value Stream Map
3. Training in Lean
4. Basic Building Blocks
5. Kaizen Blitz
6. Pilot Projects
7. Change Management
8. OEE
1. Baseline Assessment
Baseline Assessment or Gap Analysis performed by experienced Lean experts
• Use – Interviews– Observations– Process mapping– Analysis of reliable data
• Create a “Gap Analysis” with focus on eliminating the Eight Wastes
• Generate an Action Plan for implementing Lean improvements
2. Value Stream Mapping
Value Stream Mapping• Assemble the cross functional team• Have a Value Stream Manager• Determine a Product Family• Create the Current State Map• Create the Future Stats Map• Develop the Plan to get there, tie-in with business
objectives• Review the Plan, stay on course• Your Future State then becomes your Current State• Expand to Multiple Value Streams
3. Training in Lean
Training in Lean
• “Massive” training in Lean
• Need to build a critical mass of trained
employees
• Perform the training just before
implementation
• Lean Champions should have advanced
skills in Lean
4. Basic Building Blocks
• Start with one of the Basic Building Blocks of Lean
Change Management
5SVisualLayout Standard Work
Batch Size ReductionPOUS
Autonomation
JIT
Quick Changeover
Pull System & KanbanCellular & FlowTPM
VSM
Continuous Improvement & Kaizen Blitz
Self InspectionPoka-yoke
Teams
Basic Building Blocks
Basic Building Blocks• Start with the implementation of the Basic
Building Blocks• Build up layer by layer until TPM, Cellular
Manufacturing and Pull/Kanban are established
• Then continuously improve using Kaizens, suggestion systems and periodic Value Stream Maps.
Example – Implementing 5S
• Plan– Identify 5S Champions
& Teams– Decide how to roll-out
to entire organization– Resources required
• Train– Train just before
Kaizen– Train-the-trainer
• Do• Improve & Repeat
1
7
1
5
5 6
8 98 88 8
44
9999
23
10
10
13
141411
12
5S Implementation Map
5. Kaizen Blitz
Select a Kaizen Blitz project• Perform in 3-5 days• Focus on speed and elimination of waste• Can perform on “low hanging fruit”• Generates quick victories and
improvements• Do not continue in an Ad-hoc approach,
use your Value Stream Map
6. Pilot Projects
Pilot Projects• Implement Lean Pilot Projects where bottlenecks
have been identified• Use cross-functional teams• PDCA methodology is best• Can use benchmarks and best practices for goal
setting• Communicate results• Migrate lessons learned to other areas
7. Change Management
Change Management
• Begin with cultural Change Management before
rolling out Lean
• Address the human side of Lean in your three to
five year Master Plan
• Use internal/external change agents
• Communicate the need for change: ultimately,
Lean has to become integrated into daily work life
• Open up channels for sharing ideas
8. OEE
Overall Equipment Effectiveness (OEE) analysis can identify where to start your Lean journey
• Pareto the time spent on: – Breakdowns– Setups– Tool changes– Idling time– Slower speed– Minor stoppages– Producing defects, rework– Start-up issues
• This exercise will self-identify the “biggest bang for the buck” and where to start
Plan
• You must have a plan
• Utilize a Steering Committee, Design
Teams and Lean Champions
• Tie the Lean Objectives with the Business
Objectives
• Commit resources (time, people, budgets)
Stages of Lean Implementation
Generally, organizations can use this model
for the stages of implementing Lean
• Takt– Establish takt time and meet it
• Flow– After meeting takt time, then create Flow
• Pull– Where you can’t Flow, Pull
How to Sustain Lean?
• Lean will not be sustainable without proper
training in Lean and satisfied employees
• Internalize into daily work
• Understand that it is a never-ending process or
philosophy: no turning back
• Create discipline/motivation/incentives
• Standardize so as not to slip back
How to Sustain Lean?
• Continued, visible management commitment
• Open communication channels
• Emphasize accountability
• Use Lean performance metrics
• Role of Lean champions
• Job rotation
How to Setup the Lean Team
• Steering Committee• Design Teams• Champions
ChampionsChampions
Champions
Lean SteeringCommittee
5S, Visual, POUSDesign Team Cellular
Design Team
Pull/KanbanDesign Team
HPTDesign Team
Design Team
Lean Team Roles & Responsibilities
Steering Committee
Roles & Responsibilities• Set the Lean policy• Provide resources – time, people,
budgets & remove barriers• Develop and share the Lean Vision• Develop the Communication Plan
and then deploy it• “Walk the talk” everyday and fully
support the Lean initiatives• Determine the Design Team make-
up and members• Review the work of the Design
Teams
Lean SteeringCommittee
• Members usually from top management, but can include “Value Adders”
Design Teams
Roles & Responsibilities• Deploy the Lean policy• Determine the resources
required
– Time, people, budgets, etc
• Determine the best way to implement the Lean Building Blocks in your organization
• Report to the Steering Committee on progress
• Support your Lean Champions
• Members usually from management or “Value Adders”
• Group like Building Blocks together
Design Team
Design Team Agenda
• Design Teams decide how Lean will be implemented at their facility
• Take into account:
– Organizational Culture
– Change management
– Resources– Current skills &
needed skills– Size and timing of
projects– Metrics & Goals
• Design Teams may change over time
– At first they oversee the implementation plan
– Then they support the sustaining efforts
– They may disband, be absorbed into another Design Team or morph into a new design Team
– Allows members to try different aspects of Lean
Champions
Lean Champions
Roles & Responsibilities• Deploy the Lean policy via
training, implementation and Kaizen Blitz
• Feedback information to the Design Team on progress
• Be given the time to support the Lean efforts
• Make presentations and communicate the results of the Lean projects
• Members usually from management or “Value Adders”
• Motivated to learn, lead and improve their organization
Champion’s Agenda
• Be ready to commit time to Lean projects
• Be willing to learn and continually improve
• Become a Lean content expert
• Have skills in training, public speaking,
project management and be a team player
WIIFM
• Gain new skills
• Valued by the organization
• Exciting, new assignments
• Learn other aspects of Lean
Multi-facility Deployment Example
OrganizationLean Steering
CommitteeSmall FacilityLean Steering
Committee
Large FacilityLean Steering
Committee
Design Team/Champions
DesignTeam
DesignTeam Design
Team
DesignTeam
Champions
Momentum
• Have to build a “critical mass” of employees trained in Lean and apply principles
• Build “buy-in” and get people onboard
• “Bandwagon” affect
Organizational Alignment
Dealing with Objections to Lean
• Put yourself in their shoes
• Help answer “WIIFM”
• Communicate, communicate, communicate
and then communicate some more!
• Create an “Elevator Speech”
Getting People on Board
Lean Paradise
Status QuoLand
! ?
Lean Enterprise vs.Lean Manufacturing
• Taking Lean beyond the shop floor
Lean Enterprise• Move from the shop floor to Enterprise-wide Lean
implementation• Many of the Building Blocks are essential for
efficient office functions – 5S, Visual, POUS, Standard Work, Layout, Self Inspection, Poka-yoke
• The goal is to reduce or eliminate the wastes to reduce lead times and to enhance responsiveness, competitiveness and customer satisfaction
Thank you!
www.asq.org