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Innovation And Out Of Box Thinking in Lean Six Sigma Essay

Learning Objectives
• Review of MEASURE phase
• ANALYZE Phase
• Data and Process analysis
• Control Charts
• Causal analysis
– 5 Why’s
– Relations Diagram
– Cause & Effect Diagram
– Cause & Effect Matrix
– Failure Modes & Effects Analysis
• Process Capability
• Process Map, C&E Matrix, and
FMEA in Concert
• Value Stream Analysis
– Takt Time
– Supermarket Pull System
– Continuous Flow
– Level the Production
– Level the Production Volume
• HOSHIN PLANNING
Review of Measure Phase
MEASURE Phase – Objective: To determine what to measure, manage measurement data
collection, develop and validate measurement systems and determine the current process and value
stream performance.
• Types of data
• Attribute/discrete >> qualitative
• Variable/continuous >> quantitative




Properties of Normal Distribution
Cost Of Poor Quality (COPQ)
Determine & Quantify Current Metrics
Measurement Systems Evaluation
• Sources of Observed Process Variation

Process Mapping
• High Level Process Map – Process Flow Symbols
• Detailed Process Step Map (P-Map)
• Physical Flow (Spaghetti) Diagram
• Identify value stream and eliminate waste
• The Seven Types of Waste (COMMWIP)
• Workplace Organization (5S’s)
• ACME Value Stream Map
‘Current’ State – Value Stream Map
6 week
Forecast
PRODUCTION
CONTROL
90/60/30 day
Forecasts
MRP
Michigan
Steel Co
Daily
Order
Weekly
Fax
18,400 pcs/mo
12,000 “L”
6,400 “R”
Tray = 20 pcs
Weekly Schedule
500 ft Coil
Daily Ship
Schedule
Tues &
Thurs.
Value Added Time
184 secs
= 2,039,040 secs
Total Lead Time
STAMPING
1
Coils 5
days
5 days
200 T
C/T = 1 sec
C/O = 1 hr
Uptime = 85%
2 shifts
26,640 sec avail.
1 second
4600 L
2400 R
7.5 days
S. WELD #1
S. WELD #2
1
1
C/T = 38 secs
C/O = 10 mins
Uptime = 100%
2 shifts
26,640 sec avail.
38 seconds
1100 L
600 R
1.8 days
C/T = 45 secs
C/O = 10 mins
Uptime = 80%
2 shifts
26,640 sec avail.
45 seconds
2.7 days
61 seconds
1X Daily.
ASSEMBLY #2
1
C/T = 61 secs
C/O = 0
Uptime = 100%
2 shifts
26,640 sec avail.
2 shifts
= 0.01%
ASSEMBLY #1
1600 L
850 R
State
Street
Assembly
SHIPPING
Staging
1
1200 L
640 R
2 days
C/T = 39 secs
C/O = 0
Uptime = 100%
2 shifts
26,640 sec avail.
39 seconds
2700 L
1440 R
4.5days
Lead Time =
23.6 days
V/A Time =
184 secs
Learning to See: Value-Stream Mapping to Create Value and Eliminate Muda : Version 1.3 June 2003 by James Womack, Mike Rother and John Shook (2003, Hardcover, Spiral)
ANALYZE
Phase
Objective: To understand the sources for variation and waste, identify potential
root causes, and stratify and analyze the opportunities for improvement.
ANALYZE Phase
NARROW IT DOWN
▪ Determine Inputs that could effect Output
▪ Separate the “Vital Few” from the “Trivial Many”.
▪ Reduce the number of Inputs impacting Output.
WHAT ARE THE MAJOR ROOT CAUSES OF
VARIATION & WASTE?
ANALYZE Phase
ANALYSIS
DATA
PROCESS
Using data to find patterns, trends, and
differences that suggest, support, or reject
theories about the causes of defects
Examine process and value stream maps for
Non-Value Added Elements and Constraints
The Evolution of Analytics
High
What can happen, given the
behavior of a community?
Complexity
Analytics -BIG DATA
What is likely to happen?
PREDICTIVE ANALYSIS
What’s happening now?
DASHBOARDS
Why Did it happen?
DETECTIVE ANALYSIS
What happened?
Low
REPORTING
Low
Business Value
High
The Evolution of Analytics
• Small data – The era of “business intelligence”
– Historical data generated purely by a firm’s internal transaction
systems
– Gained an objective, deep understanding of important business
phenomena
– Gave managers the fact-based comprehension to go beyond
intuition when making decisions
Activity addressed only what had happened in the past;
they offered no explanations or predictions
The Evolution of Analytics
• The era of “Big Data”
– Internet-based and social network firms – Google, eBay, and so on began to amass and analyze new kinds of information
– Big data was externally sourced as well, coming from the internet,
sensors of various types, public data initiatives
– The need for powerful new tools – and the opportunity to profit
by providing them
The data scientists helped shape the business by analyzing the
Digital Trace
The Evolution of Analytics
• The era of “actionable offerings”
– Silicon Valley began investing in analytics to support customer-facing
products, services, and features.
– Attracting viewers to their websites through better search algorithms,
recommendations from friends and colleagues, suggestions for products
to buy, and highly targeted ads, all driven by analytics.
– Banks, industrial manufacturers, health care providers, retailers can
develop valuable products and services from their aggregated data.
Google, LinkedIn, Facebook, Amazon …
Giving customers shortcuts to decisions and actions
What type of chart?
Our decision is based on:
• The types of data we have
• What is counted
Types of data
• Attribute/discrete data is qualitative, consists of
categories and cannot be subdivided
– Yes/No, Pass/Fail, number of defects
• Variable/continuous data is quantitative showing
absolute distance between numbers, and can be
subdivided.
– Time, Length, Width, etc.
What is counted
• Defects: individual non-conformances
• Defectives: units failing to meet at least one conformance
standard
• Individual: n=1
• Subgroups: Subgroups or samples should be selected so
that if assignable causes are present, the chance for
differences between subgroups will be maximized, while
the chance for differences due to these assignable causes
within a subgroup will be minimized.
Control charts for Attribute Data
Attribute Data
Defective
Defect
CONSTANT
Sample size
VARIABLE
Sample size
CONSTANT
n > 50
VARIABLE
n > 50
c
chart
u
chart
p or np
chart
p
chart
Control charts for Variable Data
Variable Data
Individuals
Individuals
& Moving
Range
(I&MR)
chart
Rational Subgroups
Subgroup
size or = 6
X-bar & R
chart
X-bar &
S chart
c Chart – Example
Counts number of defects per lot.
All subgroups are the same size.
Parts can have more than one defect.
u Chart – Example
Counts number of defects per unit of production.
Can handle subgroups of differing sizes.
Parts can have more than one defect.
np Chart – Example
Counts number of defective units per lot.
All subgroups are the same size.
p Chart – Example
Counts the proportion of defective units per lot.
Can handle subgroups of differing sizes.
I & MR Chart – Example
The individual (X)
chart displays
individual
measurements.
The moving range
(MR) chart shows
variability between
one data point and
the next.
For processes with a subgroup size of one.
Xbar & R Chart – Example
The X-bar chart shows
how the mean or
average changes over
time
The R chart shows
how the range of
the subgroups
changes over time.
For processes that have a subgroup size of two or more
X-bar & s Chart – Example
The X-bar chart
shows how the
mean or average
changes over
time
The s chart shows
how the Standard
Deviation of the
subgroups changes
over time.
The sample size is constant
Pareto Chart
Bars sorted in
descending order
To sort out the “vital few” from the “trivial many”
GENERATING THEORIES – Causal Analysis
• 5 Why’s
• Relations Diagram
• Cause & Effect Diagram
• Cause & Effect Matrix
• Failure Modes & Effects Analysis
The “Why” Graph
Lack of Knowledge
Impractical
1st
2nd
7th
6th
3rd
4th
5th
Identification
Domain
The 5 Whys is a question-asking technique used to
explore the root cause of a defect or problem.
The “5 Why’s” Approach
Issue
Cause
Cause
Cause
Cause
Cause
Why
Why
Why
Why
Why
?
?
?
?
?
Avoid the Perceived Immediacy by
using the 5 Why’s
A “5 Why’s” Example
Invoices
take too
long
Why?
Because I
don’t have
all
the info
Why?
Because the
customer
did
not provide
Why?
Why?
Project
Level
Why?
Because of
insufficient
training
Because the
Work order
isn’t
used correctly
A “5 Why’s” Example
• WHY is there a bottleneck?
The equipment cannot keep up due to downtime.
• WHY so much downtime?
The equipment is in disrepair.
• WHY is the equipment in disrepair?
Didn’t do any preventive maintenance.
• WHY no preventive maintenance?
The procedures are not being followed.
• WHY are procedures not followed?
Maintenance Department is short-handed
Relations Diagram
• A visual tool that reveals a network of cause-and-effect relations
• Takes complex, multi-variable problems and reveals the interrelated factors
• For each pair of root causes, compare the relationship between the two drawing an
arrow to indicate direction of force
• Ask of each pair: “Does this drive this next category or vice versa?” Draw oneway arrows only
The project was
inadequately scoped
Management Decisions did
not align with project needs
and goals
4/0
The processor
schedule was
unrealistic
Out (Impacts Others) /
In (Impacted by others)
The project was
insufficiently staffed:
not enough people and
not the right skill sets
Too many builds
occurred without
design maturity
Insufficient tools and process
to qualify new technology or
processors
Relations Diagram – Steps
3/1
The project was
inadequately scoped
1/1
Out (Impacts Others) /
In (Impacted by others)
The processor
schedule was
unrealistic
0/5
Management Decisions did
not align with project needs
and goals
Too many builds
occurred without
design maturity
4/0
The project was
insufficiently staffed:
not enough people and
2/2 not the right skill sets
Insufficient tools and process
to qualify new technology or
processors
1/2
• Repeat until all pairs have been considered
• Count the number of arrows going out and going into each root cause
• In most cases we would start with the main driver(s)
Improving the Photocopy Process
TOP LEVEL PROCESS MAP & SIPOC
Cause & Effect (C&E) Diagram
• Dr. Kaoru Ishikawa, a Japanese quality control statistician, invented
the fishbone diagram (Ishikawa diagram)
• The design of the diagram looks much like the skeleton of a fish
(Fishbone diagram)
• The fishbone diagram is an analysis tool that provides a systematic
way of looking at effects and the causes that create or contribute to
those effects. Therefore, it may be referred to as a Cause-and-Effect
diagram
The value of the C&E diagram is to assist teams in categorizing
the many potential causes of problems or issues in an orderly
way and in identifying root causes
Fishbone (Cause & Effect Diagram)
Copy Machine
Measurement
Machine
Wear of parts
Mother Nature
Too Humid
Dirty Feed Rollers
Preventive
Maintenance
Too much paper
in feed tray
Inadequate
Wrong paper in
feed tray
Not frequent
Stockcard
Mylar
Paper
Jam
Inferior Paper
Quality
Finish
Grain
Texture
Poor paper condition
Paper jam not
completely
removed by
previous user
Method
Man (People)
Materials
Redo
copy
Cause & Effect Matrix
• A tool used to emphasize importance of
Customer Requirements.
• Numerically Ranks Output Importance
• Numerically Ranks Input Relationships
• Pareto Input Impact On Outputs
• Pareto Output Impacted By All Inputs
• Provides information for a Failure Modes & Effects Analysis
and Process Capability Assessment
Modified Portion of the Quality Function Deployment Tool
C&E Matrix Method
1. List Output Variables (Y’s) (CTS’s) along the top section of the matrix.
2. Rank each output numerically, highest number represents most important.
(1) = low importance, no effect
(3) = somewhat important, remote effect
(6) = very important, moderate effect (9) = most important, strong effect
3. List all inputs/causes impacting output along the left hand side
4. Numerically rate effect of each input on each output within the body of the matrix
(1, 3, 6, 9)
5. Totals column prioritizes where to focus team effort to create the FMEA.
2
1
3
4
5
Refer to “Improving the Photocopy Process” – Excel file
QuikSigma Cause and Effect Matrix
~ 6 mins
http://www.youtube.com/watch?f
eature=player_detailpage&v=g90
7YnSfcRw
How to separate out the stronger
input variables collected in the
Process Map
Failure Modes &
Effects Analysis
Cause-Failure Mode-Effect Continuum
◼ Every product or process has modes of failure
◼ The effects represent the impact of the failures
Variation source
causing Failure Mode
Specific way
input fails
Impact on Customer
requirements
Where Does Risk Come From?
Unclear Customer
Expectations
Assignment
Variation
Vague
Workmanship
Standards
Machine Reliability
Potential Safety
Hazards
Cumulative
Risk
Measurement Variation
(Online and QC)
Poor control plans &
SOP’s
Poor Process
Capability
Raw Material
Variation
Poorly developed
Specification Limits
Failure Mode and Effects Analysis
An FMEA is a tool to:
• Identify the relative risks designed into a product or process.
• Initiate action to reduce those risks with the highest potential
impact.
• Track the results of the action plan in terms of risk reduction.
• Assists in the development of process control plans
• Documents the rationale behind process changes and helps guide
future process improvement plans
The FMEA IS PROACTIVE! Should be started when new products or a new
processes are designed or when old processes are changed
FMEA Inputs & Outputs
INPUTS:
• Process Map
• Cause & Effect Diagram (Fishbone) and Cause & Effects
Matrix
• Process History
• Process Technical Procedures
OUTPUTS:
• List of Actions to Prevent Causes or to Detect Failure
Modes
• History of Actions Taken
FMEA Terminology
• Failure Mode – In what ways does the process step or
input go wrong?
• Failure Effect – What is the impact on the Key Output
Variables (Customer Requirements, Big Y) or internal
requirements?
• Severity – How Severe is the effect to the customer?
• Cause – What causes the process step to go wrong?
• Occurrence – How often does cause or failure mode occur?
• Current Controls – What are the existing controls and
procedures that prevent either the cause or the failure
mode?
• Detection – How well can you detect cause or failure
mode?
Assessment Guidelines
Rating
9
6
Severity of Effect
Hazardous defect noticed
by all customers
Major defect noticed by
most customers
3
Minor defect noticed by
some customers
1
No effect
Likelihood of
Occurrence
Ability to Detect
Failure is inevitable
Can not detect
Frequent failures
Moderate chance of
detection
Relatively few failures High chance of detection
Failure is unlikely
Certain detection
The Risk Priority Number
• A systematic methodology is used to rate the risks relative to each other.
• An RPN or Risk Priority Number is calculated for each failure mode and its
resulting effect(s).
RISK PRIORITY NUMBER
Severity
X
Occurrence
X
Detection
Dynamics of the RPN
Sev Occ Det RPN
1
1
9
1
9
9
1
9
1
9
1
1
9
1
9
9
1
1
1
9
1
9
9
9
1
9
9
9
81
81
81
729
Result
Ideal Situation
Freq. fails, detectacle, costly
Failure does not reach customer
Assured Mastery
Freq. fails with major impact
Failure reaches customer
Freq. fails, reaches customer
Big Trouble!
The RPN can range from a low of 1 to a high of 729
Process of Conducting an FMEA
• Identify “Heavy Hitter” Inputs or Process Steps
• Identify Associated Y’s (Outputs – Critical To Satisfaction)
• Determine ways inputs can go wrong
• Determine Effects for each Failure Mode
• Identify Causes for each Failure Mode
• List current Controls for each Cause
• Assign ratings: Severity, Occurrence and Detection
• Calculate Risk Priority Number (RPN)
• Once the RPN’s are calculated, sort them in descending
order
Refer to “Improving the Photocopy Process” – Excel file
Hints for a successful FMEA
F
M
E
A
• Take your time in defining functions
• Ask a lot of questions:
– Can this happen…..
– What would happen if the user….
• Do not plan to REDUCE RPN with detection actions
4:21
FMEA Overview

Data Analysis – VERIFYING CAUSES
• Scatter Plot or Correlation Diagram
• Stratified Charts
• Advanced Statistical Tools & Methods
– Hypothesis Testing
– Correlation
– Simple Regression
– Chi-square
– Proportions Test
– Discriminant Analysis
– Analysis of Variance
– T-Tests
– Design of Experiment
Scatter Diagram or Plot
• Used to study the relationship between two variables.
• Used to measure the strength and direction of this relationship.
• Allows study of two distinct variables and graphically shows if a
relationship exists between these variables.
WEAK POSITIVE CORRELATION
STRONG NEGATIVE CORRELATION
Stratified Charts
Stratify: to separate
or become separated
into layers or
categories
QuikSigma Process Map, C&E Matrix,
and FMEA in Concert
~ 4 mins
http://www.youtube.com/watch?feature=play
er_detailpage&v=u6GHwnRAEZI
Linkage between the various tools
Process
Maps
&
Supplier
Input
Process
Output
Customer
C&E
Diagram or
Fishbone
Cause and
Effects
(C&E) Matrix
Y = f (X)
Narrowing Input Variables
Failure
Modes &
Effects
Analysis
(FMEA)
Design of
Experiment
(DOE)
Optimized Process
ANALYZE Phase
ANALYSIS
DATA
PROCESS
Using data to find patterns, trends, and
differences that suggest, support, or reject
theories about the causes of defects
Examine process and value stream maps for
Non-Value Added Elements and Constraints
Process Capability – The Strategy
• Two main problems: poor centering of the process around
a target, and too much total process variation.
CENTERING
Put The Process On Target!
SPREAD
Reduce The Variation!
• Key process metrics which report directly on capability
include; PPM defects, DPMO, RTY, FTY, and COPQ.
Process Control: Process Outputs
Upper control limit
Lower control limit
In statistical control and CAPABLE
of producing within control limits:
A process with only natural causes of
variation and capable of producing
within the specified control limits.
In statistical control, but NOT CAPABLE of
producing within control limits: A process in
control (only natural causes of variation are
present) but not capable of producing within the
specified control limits
OUT OF CONTROL: A process out of control
having assignable causes of variation.
Analyze Checklist
Value Stream Analysis – Guidelines
1. Produce to your Takt Time.
2. Use Supermarket Pull System to control production where
continuous flow does not extend upstream.
3. Develop Continuous Flow whenever possible.
4. Try to send the customer Schedule to only one production process
5. Distribute the production of different products evenly over time at
pacemaker process (Level the Production Mix)
6. Create an “initial pull” by releasing and withdrawing small,
consistent increments of work at the pacemaker process (Level the
Production Volume)
Learning to See: Value-Stream Mapping to Create Value and Eliminate Muda : Version 1.3 June 2003 by James Womack, Mike Rother and John Shook (2003, Hardcover, Spiral)
Takt Time is the heartbeat of Lean
TAKT Time =
Available Time
Customer Demand
Balanced Line
Unbalanced Line
20
20
15
15
10
10
5
5
0
0
A
B
C
D
Operation
E
A
B
C
D
E
Operation
The Takt Time Enables Us to Balance the Process
The ACME Stamping Takt time
• Takt time links production to the customer by matching the pace of production (pacemaker
processes) to the pace of actual final sales
ACME STAMPING COMPANY Work Time:
▪ 20 days in a month
▪ Two (2) shift operation, Eight (8) hours every shift
▪ Two (2) 18-min breaks during each shift
▪ Manual processes stop during breaks, Unpaid lunch
TAKT Time = Available Time
Customer Demand
Available work time per day = 53,280 secs per day (2 shifts, 7.4 hrs ea.)
Customer demand = 18,400 units per month 920 units per day >>> 600 “LH”, 320 “RH”
TAKT time = 53,280 secs
920 units
= 58 secs / unit
Takt Time is the rate of customer demand
‘Current’ State – Value Stream Map
6 week
Forecast
Michigan
Steel Co
PRODUCTION
CONTROL
90/60/30 day
Forecasts
MRP
Daily
Order
Weekly
Fax
18,400 pcs/mo
12,000 “L”
6,400 “R”
Tray = 20 pcs
Weekly Schedule
500 ft Coil
Daily Ship
Schedule
Tues &
Thurs.
State
Street
Assembly
2 shifts
TAKT time = 58 secs / pc
1X Daily.
Which step is the constraint/ pacemaker ?
STAMPING
1
Coils 5
days
5 days
200 T
C/T = 1 sec
C/O = 1 hr
Uptime = 85%
2 shifts
26,640 sec avail.
1 second
4600 L
2400 R
7.5 days
S. WELD #1
S. WELD #2
1
1
C/T = 38 secs
C/O = 10 mins
Uptime = 100%
2 shifts
26,640 sec avail.
38 seconds
1100 L
600 R
1.8 days
C/T = 45 secs
C/O = 10 mins
Uptime = 80%
2 shifts
26,640 sec avail.
45 seconds
ASSEMBLY #1
ASSEMBLY #2
1
1600 L
850 R
2.7 days
C/T = 61 secs
C/O = 0
Uptime = 100%
2 shifts
26,640 sec avail.
61 seconds
SHIPPING
Staging
1
1200 L
640 R
2 days
C/T = 39 secs
C/O = 0
Uptime = 100%
2 shifts
26,640 sec avail.
39 seconds
2700 L
1440 R
4.5days
Lead Time =
23.6 days
V/A Time =
184 secs
Learning to See: Value-Stream Mapping to Create Value and Eliminate Muda : Version 1.3 June 2003 by James Womack, Mike Rother and John Shook (2003, Hardcover, Spiral)
Value Stream Analysis – Guidelines
1. Produce to your Takt Time.
2. Use Supermarket Pull System to control production where
continuous flow does not extend upstream.
3. Develop Continuous Flow whenever possible.
4. Try to send the customer Schedule to only one production process
5. Distribute the production of different products evenly over time at
pacemaker process (Level the Production Mix)
6. Create an “initial pull” by releasing and withdrawing small,
consistent increments of work at the pacemaker process (Level the
Production Volume)
Learning to See: Value-Stream Mapping to Create Value and Eliminate Muda : Version 1.3 June 2003 by James Womack, Mike Rother and John Shook (2003, Hardcover, Spiral)
Push and Pull Systems
Resources are provided to the consumer
based on forecasts or schedules
Controlling the flow of resources by
replacing only what has been consumed
The concept of pull in Lean production means to respond to the
pull, or demand, of the customer.
What is a “Supermarket”?
• A pull production technique to
control and level production
upstream from the pacemaker
• Materials in a supermarket are
pulled off the “shelves” by the
“customer”
• A supply of parts are stored near
the cell / line and as these parts are
used, they are replenished by the
upstream process
Build to Supermarket or to Shipping?
• Depends on the type of customer and the nature of the product.
• Build to a Supermarket if
– customer demand varies widely
– the range of finished part numbers requiring changeovers in the Product Family
is small, and
– the product is small enough and cheap enough to store cost effectively
• Alternatively, build directly to Shipping if the product
– has many custom features
– is of very high Value
– is very bulky, or is subject to spoiling
Learning to See: Value-Stream Mapping to Create Value and Eliminate Muda : Version 1.3 June 2003 by James Womack, Mike Rother and John Shook (2003, Hardcover, Spiral)
Value Stream Analysis – Guidelines
1. Produce to your Takt Time.
2. Use Supermarket Pull System to control production where
continuous flow does not extend upstream.
3. Develop Continuous Flow whenever possible.
4. Try to send the customer Schedule to only one production process
5. Distribute the production of different products evenly over time at
pacemaker process (Level the Production Mix)
6. Create an “initial pull” by releasing and withdrawing small,
consistent increments of work at the pacemaker process (Level the
Production Volume)
Completely Continuous Flow from raw material to customer is
almost never possible.
Learning to See: Value-Stream Mapping to Create Value and Eliminate Muda : Version 1.3 June 2003 by James Womack, Mike Rother and John Shook (2003, Hardcover, Spiral)
Batch Production
•Large lot production can lower a
company’s profitability in several
ways:
– the lead time between customer orders
and delivery of products is lengthened
– labor, energy, and space are required to
store and transport products
– the chances for product damage and/or
deterioration are increased
Production Batch (Lot) – Size Reduction
• Batch & Queue Processing (Lot Size = 10)
Process
Process
Process
A
B
C
10 minutes
10 minutes
10 minutes
Lead Time: 30+ minutes for total order
21+ minutes for first piece
• Transfer Batch Size (50% reduction, Lot Size = 5)
Process
Process
A
B
5 minutes
C
5 minutes
5 minutes
Lead Time: 15+ minutes for total order
11+ minutes for first piece
Flow Manufacturing
• One-piece flow production can help solve these
problems:
– customers can receive a flow of products with less delay
– risks for damage, deterioration, or obsolescence are lowered
– it allows for the discovery of other problems so that they can be
addressed
– it drives continuous improvement by eliminating inventory relied
upon to address problems
Batch Production vs. One-Piece Flow
• Transfer Batch Size (50% reduction, Lot Size = 5)
Process
Process
A
B
Process
C
5 minutes
5 minutes
5 minutes
Lead Time: 15+ minutes for total order
11+ minutes for first piece
• Continuous Flow Processing
ProcessProcessProcess
A
Lead Time:
B
C
7+ mins for 5-piece order
3+ mins for first piece
Where can we introduce Continuous Flow?
• We can only introduce continuous (or single-piece) flow when:
– Processing technologies can be scaled to run at Takt Time, and
– When a series of linked processing steps are highly repeatable and always
available.
• The place to start in introducing Continuous Flow is usually at the
beginning of the “pacemaker” Process in final assembly, from which
the product can flow straight through to shipping.
Learning to See: Value-Stream Mapping to Create Value and Eliminate Muda : Version 1.3 June 2003 by James Womack, Mike Rother and John Shook (2003, Hardcover, Spiral)
‘Current’ State – Value Stream Map
6 week
Forecast
TAKT time =
58 secs / unit
Michigan
Steel Co
PRODUCTION
CONTROL
90/60/30 day
Forecasts
MRP
Daily
Order
Weekly
Fax
18,400 pcs/mo
12,000 “L”
6,400 “R”
Tray = 20 pcs
Weekly Schedule
500 ft Coil
State
Street
Assembly
Daily Ship
Schedule
2 shifts
Tues &
Thurs.
1X Daily.
STAMPING
1
Coils 5
days
5 days
200 T
C/T = 1 sec
C/O = 1 hr
Uptime = 85%
2 shifts
26,640 sec avail.
1 second
4600 L
2400 R
7.5 days
S. WELD #1
S. WELD #2
1
1
C/T = 38 secs
C/O = 10 mins
Uptime = 100%
2 shifts
26,640 sec avail.
38 seconds
1100 L
600 R
1.8 days
C/T = 45 secs
C/O = 10 mins
Uptime = 80%
2 shifts
26,640 sec avail.
45 seconds
ASSEMBLY #1
ASSEMBLY #2
1
1600 L
850 R
2.7 days
C/T = 61 secs
C/O = 0
Uptime = 100%
2 shifts
26,640 sec avail.
61 seconds
SHIPPING
Staging
1
1200 L
640 R
2 days
C/T = 39 secs
C/O = 0
Uptime = 100%
2 shifts
26,640 sec avail.
39 seconds
2700 L
1440 R
4.5days
Lead Time =
23.6 days
V/A Time =
184 secs
Learning to See: Value-Stream Mapping to Create Value and Eliminate Muda : Version 1.3 June 2003 by James Womack, Mike Rother and John Shook (2003, Hardcover, Spiral)
One Piece Flow Simulation
https://www.youtube.com/watch?v=l0Mxn2MutjE LeanGamesFilms1
Lean Games – Plug Game
Plug factory simulation – this lean simulation is based on assembling 3 pin plugs, it
is a ideal simulation to demonstrate the following concepts:
– Layout
– Push/pull
– One piece flow
– Kanban
– Work balance
– Benefits of training
People are so much more willing to challenge working practices in a simulated
factory and are quick to identify waste in the system.
This provides ideal foundations for starting to challenge and find opportunities in
their own areas of work.
Value Stream Analysis – Guidelines
1. Produce to your Takt Time.
2. Use Supermarket Pull System to control production where
continuous flow does not extend upstream.
3. Develop Continuous Flow whenever possible.
4. Try to send the customer schedule to only one production process
5. Distribute the production of different products evenly over time at
pacemaker process (Level the Production Mix)
6. Create an “initial pull” by releasing and withdrawing small,
consistent increments of work at the pacemaker process (Level the
Production Volume)
Learning to See: Value-Stream Mapping to Create Value and Eliminate Muda : Version 1.3 June 2003 by James Womack, Mike Rother and John Shook (2003, Hardcover, Spiral)
At what single point in our VM will we schedule production?
• We want to stop Overproduction at any point along the Value
Stream.
• To do this we schedule only one point along the stream, the
pacemaker.
• The downstream and upstream processes are then linked to the
pacemaker by two simple rules.
1. Every activity upstream produces only to a precise replenishment signal
from the next downstream Process.
2. Processing downstream from the pacemaker must occur in Continuous
Flow
• The result of this control system will be that the pacemaker gets a
schedule and every other Process falls into step.
Learning to See: Value-Stream Mapping to Create Value and Eliminate Muda : Version 1.3 June 2003 by James Womack, Mike Rother and John Shook (2003, Hardcover, Spiral)
Value Stream Analysis – Guidelines
1. Produce to your Takt Time.
2. Use Supermarket Pull System to control production where
continuous flow does not extend upstream.
3. Develop Continuous Flow whenever possible.
4. Try to send the customer Schedule to only one production process
5. Distribute the production of different products evenly over time at
pacemaker process (Level the Production Mix)
6. Create an “initial pull” by releasing and withdrawing small,
consistent increments of work at the pacemaker process (Level the
Production Volume)
Learning to See: Value-Stream Mapping to Create Value and Eliminate Muda : Version 1.3 June 2003 by James Womack, Mike Rother and John Shook (2003, Hardcover, Spiral)
Definition of Pitch
• Pitch = how often work is released and monitored
• Pitch = takt time x pitch batch size (the batch size in which work is
released to the pacesetter process)
It is sometimes helpful to think
of Pitch like a train station.
The bus comes around on a
pre-determined schedule, and
you either make it or you don’t.
How do we Level Production at the pacemaker Process?
• Break orders up into small amounts, switching over
frequently between different products.
1 tray = 20 pieces
Palletized returnable
tray packaging with
20 brackets in a tray
and up to 10 trays on
a pallet.
• 31 trays of LH brackets (620 per day)
• 15 trays of RH brackets (300 per day)
Learning to See: Value-Stream Mapping to Create Value and Eliminate Muda : Version 1.3 June 2003 by James Womack, Mike Rother and John Shook (2003, Hardcover, Spiral)
What increment of Work will we release and take away from the
pacemaker Process?
• In general, Pitch will not be less than pack-out size
• But it’s highly desirable that it will not be much larger either
• The pacemaker Cell should receive an instruction every few
minutes of what to make next, typically generated by kanbans from
a Heijunka or load-leveling box located near the pacemaker.
Learning to See: Value-Stream Mapping to Create Value and Eliminate Muda : Version 1.3 June 2003 by James Womack, Mike Rother and John Shook (2003, Hardcover, Spiral)
8. What Process improvements will be necessary to
implement the changes?
• Will determine in the IMPROVE phase
5.2 HOSHIN PLANNING
Learning Objectives

Origin of Hoshin Kanri

The Hoshin Planning Process

Hoshin Planning, Lean and Six Sigma Relationships

Benefits of the Hoshin Planning
‘Hoshin Planning’ is …

An Executive-level process for developing and achieving business plans,
whereby the plan and its related goals are deployed throughout the organization.

Draws on:

systems thinking

teamwork

the PDCA cycle

a series of creative and logical tools


the Lean Philosophy
Designed to accelerate the achievement of the ‘Hoshin’ objectives.’
Hoshin Translates the Vision Into Tangible and
Measurable Objectives for Achieving the Breakthrough
Origin of ‘Hoshin Planning’

In 1965, Bridgestone Tire published a report
analyzing the planning techniques used by Deming
Prize winning companies.

The techniques described were given the name
Hoshin Kanri.

The Japanese is actually ‘Ho Shin Kan Ri’.
– ‘Shining Metal Pointing Direction’.
– Ship in a storm on the right path
– Strategic policy deployment

A VISION COMPASS!
Hoshin Kanri – Driven by Vision …
Not Today’s Problems
Connecting Intent with Execution
The Leadership Team is galvanized around the transformational
vision
◼ That vision is translated into a tree of business priorities that are
causally cascaded through the organizational hierarchy
1. Metrics and accountability are attached to each objective at all
levels
2. Specific methodologies, projects and people are deployed to
achieve the objectives
3. Periodic reviews are conducted to refine direction and objectives,
and to ensure execution to plan

Hoshin Planning Process Steps
FIND your Hoshin
•Assess Current Situation
•Envision Future State
•Identify Breakthrough Objectives
ALIGN the organization and the objectives
•Identify Links to Daily Management
•Create Breakthrough Plan
DEPLOY the plans
❖ “Catchball” Means Communication
❖ Socializing Ideas
❖ A Process of Aligning Hoshins
Between Levels, Through the Use
of Factual (Root/cause) Analysis
• “Catchball”
IMPLEMENT the changes
•Review Plan
REVIEW and improve all along
the way
•Conduct Periodic Reviews
Hoshin Deployment, Work, & Review
Review
Hoshin Deployment
Make Hard
Choices
Review
Catchball Vertical
Create Work
Plans
Consolidate
plans
(“rollup”)
Do Work
Review
Do Work
Catchball Horizontal
Review
Do Work
Hoshin Planning: What is Meant by ‘Catchball’ ~3 mins

eature=player_detailpage&v=_ya0i-2XmdY
Uploaded by industryweek on Aug 4, 2009
In this session at the 2009 IW Best Plants Conference, Wes Waldo, Vice President for the Manufacturing
Practice, Breakthrough Management Group, provides you with a basic understanding of what Hoshin Planning
is and how it can significantly improve your business. You see real world examples of how aligning your
business infrastructure towards a common set of goals will reinvigorate your entire organization. In this clip,
Waldo discusses what is meant by ‘catch ball.’ This is a video excerpt, to see the full video, please go to
http://www.industryweek.com/videos/hoshin-planning-best-plants-2009.aspx
More videos are available at http://www.industryweek.com/videos
Simply put . . .

Hoshin Kanri is a system of forms and rules that
encourages employees to analyze situations, create
plans for improvement, conduct performance checks
and take appropriate action
‘X Matrix’
– Forms provide the planning structure
– Rules provide the process for using the forms

Define metrics and goals for each Hoshin objective
–Y = f (X1, X2, X3, …)
– Start with available data and models
– Improve using the feedback built into the Hoshin process

Create strategies to accomplish the Hoshin objective(s)

Select strategy owners
The Process Provides Alignment and Standard Work
‘A3’s’
In summary, Hoshin Planning …
Provides organization-wide focus; makes priorities obvious
◼ Helps ensure consensus on issues and priorities
◼ Aids coordination across departments and functions eliminating duplication of
effort and misdirected action
◼ Facilitates teamwork
◼ Provides methodology for including customer needs
◼ Clarifies responsibility and ownership
◼ Allows better decisions and correction of significant problems
◼ Provides alignment and synergy of efforts
◼ Leverages Lean Transformation Initiatives and Six Sigma Projects

Improves the Strategic Planning Process …
Assures Excellence in Execution

feature=player_detailpage&v=f5SDpIoXNJM
Why Use Hoshin Planning? ~ 10 mins
In this session at the 2009 IW Best Plants Conference, Wes Waldo, Vice President for the
Manufacturing Practice, Breakthrough Management Group, provides you with a basic understanding
of what Hoshin Planning is and how it can significantly improve your business. You see real world
examples of how aligning your business infrastructure towards a common set of goals will
reinvigorate your entire organization. In this clip, Waldo discusses why to use Hoshin Planning and
some key themes. This is a video excerpt, to see the full video, please go to
http://www.industryweek.com/videos/hoshin-planning-best-plants-2009.aspx More videos are
available at http://www.industryweek.com/videos
Class Discussion Topic #4
Albert Einstein stated:
“The significant problems we
face cannot be solved at the
same level of thinking we were
at when we created them”
Discuss the importance of
innovation and out-of-box
thinking in LEAN Six Sigma

Purchase answer to see full
attachment

aalan

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