Transcript RLM & Associates LLC Your Lean Six Sigma & Project

Six Sigma Introduction
6
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Six Sigma
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Six Sigma Roles
Six Sigma defines a taxonomy of
knowledge, skills and ability levels for
all members of the organization.
Each Six Sigma level has well
defined roles and
responsibilities for team
communications.
Executive
Deployment
Leader
Champions
Master Black Belts
Black Belts
Effect: Team members
are focused and
capable of meeting
project needs.
Green Belts
Yellow Belts
All Employees
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The Six Sigma Project
Finding the solution of Y = f(X)
Practical
Problem
Six Sigma
Project
A well-defined problem
statement and quantifiable
output expectations.
Project Characteristics:
Statistical
Problem
A data-oriented problem
analyzed with information,
facts and data analysis.
2. Definitive project start and
end dates
Statistical
Solution
Data driven solution with
known confidence/risk levels
versus an “I think” solution.
Control
Plan
Practical
Solution
Results
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A problem which impacts the
success of a process or function.
Documented approach to
assure sustainability of
solution.
Practical solutions that are
readily implement-able.
Tangible, measurable,
quantifiable financial results
with strategic value.
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1. Impacts profitability or
provides significant strategic
value
3. Targeted to reduce the
problem by >70% over
existing performance levels
Focus on solving a problem:
1. Hindering success
2. Adding costs
3. Decreasing customer
satisfaction
4. Impacting a customer
4
Six Sigma Summary
Lean Six Sigma
and its applications
facilitate
organizations to:
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1.
Distinguish problematic areas of
the business
2.
Write quantifiable goals and
objectives
3.
Identify projects that create
solutions to problems
4.
Attain financial benefit from Six
Sigma project improvements
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Define Phase
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Define Phase Overview
Define – identify the issue causing decreased
customer satisfaction. The following tools assist
with the Define Phase.
 Management Commitment – Plan – Do – Study – Act
 SIPOC – Supplier -
Input -
Process
- Output
- Customer
 Define the problem – the 5 whys and how
 Systems Thinking – process maps and value stream mapping
 Flowcharting
 Project Management
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Define Phase Overview
1. Which processes are key to the success of the organization and
are in need of improvement?
2. What specific problems can be solved to improve the
performance of this process and my organization?
3. What is the processes current performance baseline?
4. When does the organization expect to see improvement in the
processes level of performance, what is my objective?
5. What financial benefit will the organization see if the projects
objectives are met?
6. Which organizational goal(s) will this project impact?
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Steps for Defining a Project
1. Agree on what needs to be improved, this is defined as “Y”
Inputs (X’s)
Process
Process
Output Needing
Improvement (Y)
2. Identify the baseline performance of the “Y”
3. Create a process map
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Steps for Defining a Project
4. Identify the problem cost and impact.
+
5. Write a Problem Statement
Be sure the statement includes:
What
Where
When
Baseline
Cost
6. Write an Objective Statement
Be sure the statement includes:
A METRIC
BASELINE performance level
The GOAL
A TIME FRAME to achieve some BENEFIT
The linkage to a specific CORPORATE GOAL or OBJECTIVE.
7. Obtain sponsor approvals and launch the project
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Writing a Problem Statement
POOR Problem Statements:
1. Customers are complaining about
their pizza delivery times.
2. There is a problem with the number
of burnt pizzas.
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Writing a Problem Statement
GOOD Problem Statements:
1. Since August 1, 2009, the average time to deliver pizza within a
fifteen-mile radius is 39 minutes - a low of 24 minutes and a high
of 49 minutes - causing us to miss our goal of less than 35
minutes 39% of the time. This causes customer complaints,
delivery of cold pizzas and loss of business. This costs us $47,500
per year in scrapped/free pizzas, $9,750 in drivers’ expenses and
an annual revenue loss of $300,000.
2. For the past 6 months, 8.5% of pizzas have been scrapped prior
to boxing due to burnt crust. Also, 3.75% of pizzas delivered have
been scrapped due to burnt areas in the cheese and toppings.
Annually, this costs us $124,000 plus loss of customer
satisfaction.
Include the following: WHAT is wrong, WHERE and WHEN is it occurring,
what is the BASELINE magnitude at which it is occurring and what is it
COSTING me?
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Writing an Objective Statement
POOR Objective Statements:
1. Improve pizza delivery times.
2. Re-train employees to reduce the
number of burnt pizzas.
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Writing an Objective Statement
GOOD Objective Statements:
1.
Reduce the number of pizzas delivered in over 35 minutes from
39% to less than 5% by August 1, 2010. This will support our
Customer Satisfaction goal and achieve a hard savings of
$85,000.
2.
Reduce the number of burnt pizzas, including the
cheese/ingredient area, from an average of 12.25% to less than
0.5% with an upper control limit of 1% by June 15, 2010. This
will support our goal of operational excellence and provide a
savings of $135,000.
Include the following: Improve some METRIC from some BASELINE
level to some GOAL, by some TIME FRAME, to achieve some BENEFIT
and improve upon some CORPORATE GOAL or OBJECTIVE.
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Summary
The likelihood of success for a
Lean Six Sigma project is
significantly enhanced as soon
as it is accurately defined.
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Measure Phase
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Measure Phase Overview
Measure – collect data from the process. Common
tools used in the measure phase include:
 Management Commitment – Plan – Do – Study – Act
 Identify a data collection plan
 Measurement System Analysis
 Collect Data – check sheets, histograms, Pareto charts, runs
charts, scatter diagrams
 Identify Variability – instability, variation, off-target
Benchmarking – start by establishing baselines
Start calculating the cost of quality
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Measure Phase Overview
1. What is the actual process being performed compared
to what I think it is (Process Map)?
2.
How are the processes associated with this problem really
working (Capability)?
3. Is my ability to measure/detect accurate enough to make good
decisions (measurement system analysis)?
4.
Which inputs (critical X’s) seem to have the greatest effect on
the outputs (Y’s)?
Identify the true process and determine the most likely
contributors including the statistical determination of the accuracy
and repeatability of the data that characterize the process.
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The Leverage Funnel
The many Xs
when we first start
(The trivial many)
XXXXXXXX XX
XXXXXXXX XX
X XX XXXXX X X
X XX XXXXX X X
XX XX XX X
The quantity of Xs
when
remaining
we apply
after
leverage
DMAIC
(The vital
few)
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The quantity of Xs
after
keepwe
reducing
think as
you
about
work
Y=f(X)
the project
+e
XXX
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Process Mapping
To correctly manage a process one must be able to
communicate it so that it is easily understood.
 The preferred method for describing a process is to
show the workflow with a Process Map and describe
each operations purpose.
 The Measure Phase starts by describing the process
under review.
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Process Mapping
Processes mapping helps identify important and
relevant project information such as:
1.
2.
3.
4.
5.
6.
Process inputs
Process outputs
Supplier requirements
Customer requirements
Value-added and non-value added activities
Data collection points
a) Takt and Cycle times
b) Defect and defective levels
c) Inventory levels
d) Cost of poor quality, etc.
7. Decision points
8. Process control needs
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Process Mapping
There are usually three views of a process:
1
What you THINK it is..
2
What it ACTUALLY is..
3
What it SHOULD be..
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Process Mapping Levels
Level 1 – The Macro Process Map
Customer
Hungry
Calls for
Order
Take
Order
Make
Pizza
Cook
Pizza
Pizza
Corre
ct
Box
Pizza
Deliver
Pizza
Customer
Eats
Level 2 – The Process Map
Pizza
Dough
No
Take Order
from Cashier
Place in
Oven
Add
Ingredients
Observe
Frequently
Check
if Done
Yes
Remove
from Oven
1
Start New
Pizza
Scrap
No
1
Pizza
Correct
Yes
Place in
Box
Tape
Order on
Box
Put on
Delivery Rack
Level 3 – The Micro Process Map
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Analyze Phase
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Analyze
Analyze – study the process and data for clues to
what is going on
 Management Commitment – Plan – Do – Study - Act
 Continual Improvement
 Preventative Maintenance
 Cleanliness
 Central Limit Theorem
Shop audits
Experiments
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Defects, Defectives and Opportunities
What is a defect?
 Any type of undesired result is a defect.
Invoice
A failure to meet one of the acceptance criteria of your
customers. A defective unit may have one or more
defects.
The non-conformance to intended usage requirement.
What is a defective?
The word defective describes an
entire unit that fails to meet
acceptance criteria, regardless of
the number of defects within the
unit.
What is an opportunity?
The number of characteristics,
parameters or features that if any
one is bad (a defect), would
result in a defective unit.
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Supplier Data
1. Name
2. Tax Id #
3. Address
4. State
5. Zip Code
6. Qualified - Yes or No
7. Product Id
8. Required Payment Date
Total Defects per Unit
1
x
x
Invoice #
2
3
4
5
x
Hospital_________
Charge
x
x
3
1
1
0
0
DPU: 5 Defects / 5 Units = 1.0
Defects per Unit
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Opportunities – Patient Statements
Opportunity - Any area within a product, process,
service, or other system where a defect could be produced
or where you fail to achieve the ideal product in the eyes
of the customer. In a product, the areas where defects
could be produced are the parts or connection of parts
within the product. In a process, the areas are the value
added process steps. If the process step is not value
added, such as an inspection step, then it is not
considered an opportunity.
Opportunities are the things which must go right to satisfy
the customer. It is not the number of things we can
imagine that can go wrong .
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Internal vs. External Performance
Internal Performance
(Services &
Transactions)
Sigma
2
3
4
5
6
Process
Capability
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PPM
308,537
66,807
6,210
233
3.4
Defects per
Million
Opportunities
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Internal vs. External Performance
Internal Performance
(Services &
Transactions)
Sigma
2
3
4
5
6
Process
Capability
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External Performance
(Customers)
PPM
Sigma
308,537
66,807
6,210
233
3.4
2
3
4
5
6
Defects per
Million
Opportunities
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Process
Capability
PPM
308,537
66,807
6,210
233
3.4
Defects per
Million
Opportunities
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Internal vs. External Performance
Internal Performance
(Services &
Transactions)
Sigma
2
3
4
5
6
Process
Capability
External Performance
(Customers)
PPM
Sigma
308,537
66,807
6,210
233
3.4
2
3
4
5
6
Defects per
Million
Opportunities
Process
Capability
PPM
308,537
66,807
6,210
233
3.4
Defects per
Million
Opportunities
Lower Internal Performance Represents Additional Screening,
Reworking and Cost Incurred to Meet Customer Expectations
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Sigma Score Performance Observations
Prescription Writing
DPM
IRS - Tax Advice
Restaurant Bills
1,000,000
Baggage Handling
100,000
10,000
Payroll Processing
1,000
100
10
Airline
Safety Rate
1
0
1
2
3
4
Sigma Score
5
6
7
What is the difference between an IRS Tax Advice sigma of
2.5 and an Airline Safety sigma of 7?
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Analyze Phase Tools
Analyze Phase Tools:
 Graphical Analysis
 Fishbone Diagrams
 Histograms
 Box Plots
 Probability Distributions
 Time Series Charts
 Run Charts
 Scatter Plots
 Failure Modes and Effects Analysis
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Improve Phase
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Improve
Improve – act on the data to change the process
for improvement
 Management Commitment – Plan – Do – Study – Act
 Process improvement
 Organizational development
 Variation reduction
 Problem solving
 Brainstorming alternatives
 Create “should be” or “future state” maps or flowcharts
 Conduct FMEA
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Trial and Error Experiments
The usual approach:
 For the most part X’s are not
controlled. Some X’s may not be
known.
 When conducting a trial and error
approach the value of the X’s are
often selected based on
experience.
 Responses or outputs are
monitored. If preferred outcomes
are not attained (error) a further
set of inputs are selected (Trial).
 If the results meet expectations,
the experiment is considered a
success…or is it?
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Brainstorming
No
Ideas
Trials
Problem Solved?
Yes??
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(OFAT) Approach
INPUTS
Select only
one at a time
Fix A
Vary
Fix
B
Fix
D
C
OUTPUTS
Monitor 1
or More
Y1
Y=f(X)
Process,
Product or
Service
Y2
Y3
Responses
Noise Inputs
OUTPUTS
Y1
*
* Y1
** ** * * * ** * *
* *
* *
*
*
* * Y3
*
INPUT B
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Design of Experiments
Controllable
Factors X’s
Vary
A
Vary
Vary
B
Vary
D
C
The variables
manipulated during the
experiment to observe
their effects on the
response variables
LEVELS
The values, quantitative
or qualitative of each
factor during the
experiment
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Y=f(X)
Process,
Product or
Service
Noise Factors
Y’s
Responses
Y1
Y2
Y3
The variables that are
the outcome of the
experiment
The uncontrolled
variables not selected or
are not known which can
affect the response
variable during the
experiment
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Experimental Roadmap
Narrowing of possible
factors, generally more
than 7, to a critical few
Screening
Experiments
Quantify the functional
relationship between
approximately 4 to 7 factors (X’s)
and outputs response variables
(Y’s)
Characterization
Experiments
Optimization
Experiments
Find the optimal process settings with
only 2 to 4 factors.
With an iterative approach one can manage the complexity
of any single experiment.
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Design Of Experiments
Level
Factor A
Factor B
High
Low
High
Low
Process,
Product or
Service
Y
In general, the number of
experimental runs will be 2k,
where k is the number of
variables being studied.
– Example: An experiment
studying 4 variables will have
24 = 16 runs.
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Run
X1
X2
Y
1
Low
Low
.578
2
Low
High
.600
3
High
Low
.559
4
High
High
.589
A
B
C
D
-
-
-
-
-
-
-
+
-
-
+
-
-
-
+
+
-
+
-
-
-
+
-
+
-
+
+
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Design of Experiments
Experimental Results
Bond Strength – Pounds
23
USL
22
21
Vendor A
Vendor B
20
19
LSL
18
17
600F
595F
590F
585F
580F
16
At this level of process analysis one no longer needs to inspect
process outputs. Instead, simply control the input settings and let
the process take care of itself.
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DOE Terminology
Factor Any variable whose effect on an output is being studied.
Synonyms include variable, treatment, X, input.
Levels The specific settings used during the experiment for each
of the factors.
Noise The disturbance effect of those variables not purposefully
included as factors.
Response The variable whose output is the object of the study.
Synonyms include output and Y.
Condition A specific set of input variable settings.
Replication Repetition of an experimental condition to assess the
level of noise in the system.
Randomization Running experimental conditions in a random
order to mitigate the effect of noise variables.
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DOE Terminology
Main Effects The impact of a single factor, by itself, on the
output.
Interaction Effects The impact of a simultaneous combination of
factors on the output.
Runs Each time an experimental condition is processed through
the system being studied.
Design The work done before the experiment is conducted to
configure the test settings and conditions so the maximum
amount of information is obtained from the minimum number of
experimental runs.
Analysis The work done after the experiment is conducted to
refine data into useful information.
Factorial Experiment An experiment that has 2k orthogonal
experimental conditions.
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Primary Sources of Variation
Inadequate
Design
Margin
+
Unstable
Material
& Equipment
+
Insufficient
Process
Management
+
Inconsistent
Organizational
Approaches
The individual
variances add
together to form
the total
variation
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Control Phase
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Control
Control – monitor the system to sustain the gains
 Management Commitment – Plan - Do – Study – Act
 Develop control plans
 Develop long-term Measurement System Analysis
 Mistake – proofing
 Process behavior charts
 Updated lessons learned
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Interpreting Control Charts
One or more observations
occurring more than 3
standard deviations from
the average, i.e. any
points occurring above or
below the control limits.
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UCL
+2
+1
Average
-1
-2
LCL
46
Interpreting Control Charts
Fifteen consecutive
observations occurring
within one standard
deviation from the
average.
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UCL
+2
+1
Average
-1
-2
LCL
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Interpreting Control Charts
Two out of three consecutive
observations, all on the same
side of the average and
occurring more than two
standard deviations away form
the average.
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UCL
+2
+1
Average
-1
-2
LCL
48
Interpreting Control Charts
Eight consecutive
observations that are
more than one
standard deviation
from the average.
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UCL
+2
+1
Average
-1
-2
LCL
49
Interpreting Control Charts
Four out of five
consecutive
observations, all on one
side of the centerline
occurring more than one
standard deviation from
the average.
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UCL
+2
+1
Average
-1
-2
LCL
50
Interpreting Control Charts
Fourteen consecutive
observations that
alternate up and down.
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UCL
+2
+1
Average
-1
-2
LCL
51
Interpreting Control Charts
Eight consecutive
observations on one side
of the average.
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UCL
+2
+1
Average
-1
-2
LCL
52
Interpreting Control Charts
Six consecutive
observations that
trend downward or
upward.
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UCL
+2
+1
Average
-1
-2
LCL
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The Control Chart
How to Constructing Control Charts
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
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Select critical “X’s” to be charted.
Identify purpose of the chart.
Determine data-collection points.
Create the basis for sub-grouping the Y’s.
Choose the type of Control Chart.
Agree on the measurement method/criteria.
Select the sampling interval/frequency.
Agree on the sample size.
Determine the basis of calculating the Control Limits.
Prepare written instructions for all phases.
Conduct the necessary training.
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I-MR Chart
Individuals Chart
Observation
Measure
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
4
3
2
1
0
-1
-2
-3
-4
Data
LCL
Xbar
UCL
M Rbar Chart
Observation
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
5
4
Range
We chart it!
1
Range
3
LCL
2
Rbar
UCL
1
0
Xbar Chart
Subgroup
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
1.5
1
Xbar
Xbar
0.5
0
LCL
-0.5
Xbarbar
-1
UCL
-1.5
-2
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Rbar Chart
Subgroup
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
6
Rbar
5
Rbar
4
LCL
3
Rbar
2
UCL
1
0
U Chart
Sample
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
1
DPU
0.8
DPU
0.6
LCL
0.4
Ubar
UCL
0.2
0
P Chart
Sam ple
1
Proportion Defective (P)
And we chart it some more!
Xbar-R Chart
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
P
LCL
Pbar
UCL
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Summary
Choose Appropriate
Control Chart
type
of data
ATTRIBUTE
type of
attribute
data
DEFECTS
CONTINUOUS
subgroup
size
DEFECTIVES
Sample size 1
type
of defect
type of
subgroups
CONSTANT
VARIABLE
CONSTANT
VARIABLE
C Chart
U Chart
NP
Chart
P Chart
Number of
Incidences
Incidences
per Unit
Number of
Defectives
Proportion
Defectives
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2-5
10+
I – MR
Chart
X–R
Chart
X–S
Chart
Individuals
& Moving
Range
Mean &
Range
Mean &
Std. Dev.
SPECIAL CASES
Cusum
Chart
EWMA
Chart
Cumulative
Sum
Exponentially
Weighted Moving
Average
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Managing the Process Performance
“Inbound”
inputs (X’s)
Information
People
Energy
Tools
Equipment
Activity
Actions
Blending of inputs
Methods
Procedures
Materials
Environmental
effects
“Inside”
inputs (X’s)
Control the Critical X’s
with appropriate control
methods (processcontrol plans)
P1
P2
P4
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Step
P3
P5
P1
P2
P3
Q1
P4
“Outbound”
outputs (Y’s)
Process
Information
People
Energy
Tools and
Equipment
Activity
Actions
Blending of Inputs
Methods
Procedures
Materials
Environmental
Effects
Manage CTQ’s with the
process-management
system summary chart
Process A
Process Flow
Sub processes
combined to create
an output to the
next “customer”
“Inside”
outputs (Y’s)
Process
P1
Indicator
Proce
ss
Ow
ner
Ste
p
Perfor
mance
Target
Sortin
g
Jon
es
P1
4.2%
1.3%
© 2010 RLM & Associates LLC
Tren
d
Links
To:
Custo
mer
Improve
ment
Activities
Merge
I4
Smith
None
Comme
nts
58
Measuring Process Management Maturity
Level 1
Where we are starting
Level 2
Disciplined Process
Level 3
Standard, Consistent
Process
 Processes not documented
 Indicators not in place
 Process performance not consistent
 Success depends on individual efforts
 Process flowcharts in place
 Indicators are identified
 Indicators are linked to “next-process customer”
 Regular, reliable data reporting
 Improvement opportunities identified
 Processes are standardized and integrated
 Supervisors use Process Management Systems
 Improvement projects are prioritized based on data
Level 4
Predictable Process
 Upstream prevention in place
 Using Statistical Process Control
 Process performance is: Statistically stable and
capable of meeting customer requirements
Level 5
Optimized Process
 Continuous improvement: Reduces variability of
process, Increases process flexibility
 Innovation and “break-through”
 Exceeding product and service quality goals
7/18/2015
© 2010 RLM & Associates LLC
59