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1BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Six Sigma at Six Sigma at Boston ScientificBoston Scientific
Tuesday 12 September 2006Tuesday 12 September 2006Steve CzarniakSteve Czarniak
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2BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Session ObjectivesSession Objectives
•Describe the Boston Scientific Six Sigma Model•Describe the Boston Scientific Six Sigma Roadmaps•Identify which Minitab graphs to use to assess measurement system performance
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3BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Six Sigma at BSC is...Six Sigma at BSC is...
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4BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Improvement ChallengesImprovement Challenges
•Solution Known•Change in Performance•Operational Defect / Variation Reduction•Flow•Design
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5BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
BSC Six Sigma BSC Six Sigma Problem Solving RoadmapProblem Solving Roadmap
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6BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
BSC Six Sigma Operational BSC Six Sigma Operational Process Improvement RoadmapProcess Improvement Roadmap
Yield
Time
Process Improvement
Process
Define
Identify Opportunity
Identify y’s(Outputs)
Measure
y = f(x)IdentifyKey x’s(Inputs)
Analyze Optimize x’s
Improve Controlx’s
Control
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7BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControl Control Key x’s
Validate Process
Verify Long Term Capability
Monitor y’s
Finalize the Control System
Finalize Project Charter
DefineDefine Identify
Opportunity
Define Project Goal
Define Process
Establish Boundaries
Determine Customer Requirements
Define Key Y Variables
Develop Measures (y’s)
Evaluate Measurement System
Determine Process Stability
Determine Process Capability
Determine the Improvement Approach
Identify Potential x’s
Analyze x’s
Identify Key x’s
Determine Stability & Capability of Key x’s
Establish Relationships between y’s & x’s
Establish Targets & Tolerances for Key x’s
Implement Mistake Proofing
Develop, Select & Verify Process Improvements
DMAIC DMAIC Improvement ProcessImprovement Process
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8BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Balloon Scrap ReductionBalloon Scrap Reduction
Define: Reduce balloon scrap for major scrap code by 80%Scrap % by Reason Code
0%
10%
20%
30%
40%
50%
60%
70%
Cause 1 Cause 2 Cause 3 Cause 4 Other
Scrap Code
Scra
p
Observation
Indi
vidu
al V
alue
28252219161310741
2
1
0
-1
-2
_X=0.271
UCL=2.406
LCL=-1.864
Observation
Mov
ing
Rang
e
28252219161310741
3
2
1
0
__MR=0.803
UCL=2.623
LCL=0
Scaled Scrap Trend
Gage name:Date of study:Reported by:Tolerance:Misc:
0
0.0
0.5
1.0
1.5 1 2
Xbar Chart by Operator
Sam
ple
Mea
n
Mean=0.6719UCL=0.7200LCL=0.6238
0
0.0
0.1
0.2 1 2
R Chart by Operator
Sam
ple
Ran
ge
R=0.02557
UCL=0.08354
LCL=0
2 3 5 12 14 16 21 27 30 32 33
0.0
0.5
1.0
1.5
Part
OperatorOperator*Part Interaction
Aver
age
1 2
1 2
0.0
0.5
1.0
1.5
Operator
By Operator 2 3 5 12 14 16 21 27 30 32 33
0.0
0.5
1.0
1.5
Part
By Part
%Contribution %Study Var %Process %Tolerance
Gage R&R Repeat Reprod Part-to-Part0
50
100
Components of Variation
Per
cent
Gage R&R (ANOVA) for Min Measure
Stable!
Measure: Length
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9BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Balloon Scrap ReductionBalloon Scrap Reduction
Analyze: Designed Experiment
Effect
Perc
ent
2.01.51.00.50.0-0.5-1.0
99
9590
80706050403020
105
1
A Adhesive TypeB BC CD DE E
Factor Name
Not SignificantSignificant
Effect Type
A
Normal Probability Plot of the Effects(response is Scaled Length, Alpha = .05)
Lenth's PSE = 0.289116
Improve / Control:Mistake Proofing – only use preferred adhesive type!
60% scrap reduction!
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10BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Business Process Improvement Business Process Improvement Roadmap - DMAICRoadmap - DMAIC
DefineDefine
What are you trying to accomplish?
MeasureMeasure
How will you know the project has been successful?
AnalyzeAnalyze
What elements in your process can be leveraged for improvement?
ImproveImprove
What is your improvement?
ControlControl
What is your plan to implement and maintain the improvement?
Lean and Six Sigma both use the DMAIC roadmap as a common
approach for process improvement
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11BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Business Process ImprovementBusiness Process Improvement
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12BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
DefineDefine
Defined goal, talked to the customers and started to understand process complexity
AnalyzeAnalyze
Developed detailed process maps, identified waste and non-value added steps, identified gaps between ideal and current state
ImproveImprove
Developed target state, piloted tools for standardizing price approvals and automating repetitive tasks
ControlControl
Developed control plan, implemented and monitored new process
MeasureMeasure
Collected data on time and logistics for price approvals
Price Approval Process – Reduce Price Approval Process – Reduce Time, Increase ConsistencyTime, Increase Consistency
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13BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Price Approval - ResultsPrice Approval - Results
• 75% reduction in response time to customer• 62% reduction in process steps• 88% reduction in decision steps• Standardized processes: consistency, accuracy• Customer driven solution
“With BPI, our main focus was on our Customer and the requirements that they had. Without their feedback and keeping them our main focus, we would have probably come up with a totally different solution for the process of requesting and receipt of approvals” – Team Leader
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14BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Does this product meet spec?Does this product meet spec?
Lower Spec Upper Spec
A: yesB: noC: maybeD: not sure - phone a friend
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Copyright 2006 Boston Scientific
Measurement System Analysis:Measurement System Analysis:Gage R&RGage R&R
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16BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
The Basic ModelThe Basic Model
The total observed variation is equal to the real process variation plus the variation due to the measurement system.
222tmeasuremenprocessobserved
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17BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
11010090807060504030
15
10
5
0
Observed
Freq
uenc
y
LSL USL
Actual process variation - No measurement variation
Total observed variation - With measurement variation
11010090807060504030
15
10
5
0
Process
Freq
uenc
y
LSL USL
Effect of Measurement Effect of Measurement VariationVariation
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18BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Gage R & RGage R & R
• Means of assessing the repeatability and reproducibility of a measurement system.
• Evaluates how much total observed variation is due to the measurement device and measurement methods
11010090807060504030
15
10
5
0
Observed
Freq
uenc
y
LSL USL
Measurement Variation vs. Actual Process Variation ?
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19BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Gage R&R Example:Gage R&R Example: Graphical OutputGraphical Output
Perc
ent
Part-to-PartReprodRepeatGage R&R
100
50
0
% Contribution% Study Var
Sam
ple
Rang
e 0.10
0.05
0.00
_R=0.0383
UCL=0.1252
LCL=0
1 2 3
Sam
ple
Mea
n
1.00
0.75
0.50
__X=0.8075UCL=0.8796LCL=0.7354
1 2 3
Part10987654321
1.00
0.75
0.50
Operator321
1.00
0.75
0.50
Part
Aver
age
10 9 8 7 6 5 4 3 2 1
1.00
0.75
0.50
123
Operator
Gage name: Date of study:
Reported by: Tolerance: Misc:
Components of Variation
R Chart by Operator
Xbar Chart by Operator
Measurement by Part
Measurement by Operator
Operator * Part Interaction
Gage R&R (ANOVA) for Measurement
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20BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Measurement System TermsMeasurement System Terms
•Stability•Accuracy•Precision•Resolution•Bias•Reproducibility•Linearity•Discrimination•Repeatability•Calibration
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21BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Gage R&R Example:Gage R&R Example: Graphical OutputGraphical Output
1
3
2
4
5
6
Perc
ent
Part-to-PartReprodRepeatGage R&R
100
50
0
% Contribution% Study Var
Sam
ple
Rang
e 0.10
0.05
0.00
_R=0.0383
UCL=0.1252
LCL=0
1 2 3
Sam
ple
Mea
n
1.00
0.75
0.50
__X=0.8075UCL=0.8796LCL=0.7354
1 2 3
Part10987654321
1.00
0.75
0.50
Operator321
1.00
0.75
0.50
Part
Aver
age
10 9 8 7 6 5 4 3 2 1
1.00
0.75
0.50
123
Operator
Gage name: Date of study:
Reported by: Tolerance: Misc:
Components of Variation
R Chart by Operator
Xbar Chart by Operator
Measurement by Part
Measurement by Operator
Operator * Part Interaction
Gage R&R (ANOVA) for Measurement
At each table, identify ONE graphic that best describes each term.
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22BSC Six Sigma: ASQ Meeting – 12 September 2006 Copyright 2006 Boston Scientific
Destructive Gage R&R Destructive Gage R&R
Reference:De Mast, Jeroen; and Trip, Albert (2005). “Gauge R&R Studies for Destructive Measurement”. Journal of Quality Technology 37 (1), pp. 40-49.