lean six sigma measure phase tollgate review. lean six sigma dmaic tools and activities review...
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Lean Six Sigma Measure Phase Tollgate Review Measure
Phase
Lean Six Sigma DMAIC Tools and
Activities Review Project Charter Validate High-Level Value
Stream Map and Scope Validate Voice of the
Customer & Voice of the Business
Validate Problem Statement and Goals
Validate Financial Benefits Create Communication Plan Select and Launch Team Develop Project Schedule Complete Define Tollgate
Identify Root Causes Reduce List of Potential Root
Causes Confirm Root Cause to
Output Relationship Estimate Impact of Root
Causes on Key Outputs Prioritize Root Causes Value-Add Analysis Takt Rate Analysis Quick Wins Statistical Analysis Complete Analyze Tollgate
Develop Potential Solutions Evaluate, Select, and
Optimize Best Solutions Develop ‘To-Be’ Value Stream
Map(s) Develop and Implement Pilot
Solution Implement 5s Program Develop Full Scale
Implementation Plan Cost/Benefit Analysis Benchmarking Complete Improve Tollgate
Develop SOP’s, Training Plan & Process Controls
Implement Solution and Ongoing Process Measurements
Confirm Attainment of Project Goals
Identify Project Replication Opportunities
Training Complete Control Tollgate Transition Project to Process
Owner
Project Charter Voice of the Customer and
Kano Analysis SIPOC Map Project Valuation/ROIC
Analysis Tools RACI and Quad Charts Stakeholder Analysis Communication Plan Effective Meeting Tools Inquiry and Advocacy Skills Time Lines, Milestones,
and Gantt Charting Pareto Analysis
Value Stream Mapping Process Cycle
Efficiency/Little’s Law Operational Definitions Data Collection Plan Statistical Sampling Measurement System
Analysis (MSA) Gage R&R Kappa Studies Control Charts Spaghetti Diagrams Histograms Normality Test Process Capability Analysis
Process Constraint ID and Takt Time Analysis
Cause & Effect Analysis FMEA Hypothesis Tests/Conf.
Intervals Simple & Multiple Regression ANOVA Components of Variation Conquering Product and
Process Complexity Queuing Theory
Replenishment Pull/Kanban Stocking Strategy Process Flow Improvement Process Balancing Analytical Batch Sizing Total Productive Maintenance Design of Experiments (DOE) Solution Selection Matrix Piloting and Simulation Work Control System Setup reduction Pugh Matrix Pull System
Mistake-Proofing/Zero Defects
Standard Operating Procedures (SOP’s)
Process Control Plans Visual Process Control Tools MGPP Statistical Process Controls
(SPC) Solution Replication Visual Workplace Metrics Project Transition Model Team Feedback Session
Value Stream Map Flow Identify Key Input, Process
and Output Metrics Develop Operational
Definitions Develop Data Collection Plan Validate Measurement
System Collect Baseline Data Determine Process Capability Complete Measure Tollgate
Define Measure
Analyze
Improve
Control
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Kaizen Events Targeted in Measure to Accelerate Results
Project Charter
Problem: Describe problem in non-technical terms Statement should explain why project is important; why
working on it is a priorityGoal: Goals communicate “before” and “after” conditions
Shift mean, variance, or both? Should impact cost, time, quality dimensions
Express goals using SMART criteria Specific, Measurable, Attainable, Resource
Requirements, Time Boundaries Explain leverage and strategic implications (if any)
Problem/Goal Statement
Tollgate Review Schedule
Financial Impact
Team
State financial impact of project Expenses Investments (inventory, capital, A/R) Revenues
Separate “hard” from “soft” dollars State financial impact of leverage opportunities (future
projects)
PES Name Project Executive Sponsor (if different from PS) PS Name Project Sponsor/Process Owner DC Name Deployment Champion GB/BB Name Green Belt/Black Belt MBB Name Master Black BeltCore Team Role % Contrib. LSS Training Team Member 1 SME XX YB Team Member 2 TM XX GB Team Member 3 SME XX PSExtended Team Team Member 1 BFM XX Not Trained Team Member 2 IT XX Not Trained
Review high-level schedule milestones here: Phase Completions Tollgate Reviews
Tollgate Scheduled Revised CompleteDefine: XX/XX/XX - XX/XX/XXMeasure: XX/XX/XX XX/XX/XX XX/XX/XXAnalyze: XX/XX/XX XX/XX/XX XX/XX/XXImprove: XX/XX/XX XX/XX/XX XX/XX/XXControl: XX/XX/XX XX/XX/XX XX/XX/XX
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Data Collection Plan
For each performance measure (Y), update a data collection plan Include MSA measure plan (Gantt chart, MS project plan is Optional) Add Financial measure plan if separate from performance Y Add any Time Study or other data collection plans for Value Stream Map Sample Size Calculation Use additional slides if needed
Performance Measure
Operational
Definition
Data Source and Location
How Will Data Be
Collected
Who Will Collect Data
When Will Data Be Collected
Sample Size
Stratification Factors
How will data be used?
VOC
MSA
Process
VSM
Financials
Others
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Operational Definitions
Y – Continuous data (Process start/stop and cycle time boundaries (such as the unit of measure (ex minutes), the unit (the thing you are measuring), will you include weekends, holidays, non-business hours?)
Y – Discrete data (Define Success/Defect or other attribute values you will measure
X – The subgroups values or X-factor groupings you will use on your project data collection
Other unique terms that apply to your project that require clear operational definitions
Use additional slides as needed to complete your operational definitions
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MSA Conclusions
The measurement systems are acceptable. The data is considered to have no potential for significant error. Need to be careful to appropriately use the data during the Analyze Phase.
Type of Measurement
ErrorDescription Considerations to this Project
Discrimination (resolution)
The ability of the measurement system to divide into “data categories”
Work hrs can be measured to <.25 hrs. Tool usage measure to +- 2 min.
Bias The difference between an observed average measurement result and a reference value
No bias - Work hours and radar start-stop times consistent through population.
Stability The change in bias over time No bias of work hrs & radar usage data.
Repeatability The extent variability is consistent Not an issue. Labor and radar usage is historical and felt to be accurate enough for insight and analysis.
Reproducibility Different appraisers produce consistent results
Remarks in usage data deemed not reproducible, not used in determining which radars were used in each op
Variation The difference between parts n/a to this process.
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Baseline Basic Statistics
The current process has a non-normal distribution with the P-Value < 0.05 but does have a normal bell-shape.
Since the mean and median are the same in days (29) +/- 0.5 days, we will not transform data.
The range is 35 and the standard deviation is 2.7 days
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Median
Mean
29.429.329.229.129.028.928.8
Anderson-Darling Normality Test
Variance 7.169Skewness 0.201075Kurtosis -0.471714N 266
Minimum 24.000
A-Squared
1st Quartile 27.000Median 29.0003rd Quartile 31.000Maximum 35.000
95% Confidence Interval for Mean
28.805
1.95
29.451
95% Confidence Interval for Median
29.000 29.000
95% Confidence Interval for StDev
2.468 2.927
P-Value < 0.005
Mean 29.128StDev 2.677
95% Confidence I ntervals
Summary for Delivery Time
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Baseline Process Capability
266 data points collected between 11/1/04 thru 11/30/04
Mean 29 days, St. Dev. 2.9 days, CP is 1.16 indicating process needs centering to the LSL of 10 and USL of 30 days. Cpk is .1 indicating that the process is exceeding the USL.
With an overall PPM of 371,895 defects per million opportunity, the current process has a Sigma Quality Level of 1.8 or a 62% yield
36322824201612
LSL Target USL
Process Data
Sample N 266StDev(Within) 2.87033StDev(Overall) 2.69154
LSL 10Target 20USL 30Sample Mean 29.1203
Potential (Within) Capability
CCpk 1.16
Overall Capability
Pp 1.24PPL 2.37PPU 0.11Ppk
Cp
0.11Cpm 0.35
1.16CPL 2.22CPU 0.10Cpk 0.10
Observed PerformancePPM < LSL 0.00PPM > USL 281954.89PPM Total 281954.89
Exp. Within PerformancePPM < LSL 0.00PPM > USL 379619.67PPM Total 379619.67
Exp. Overall PerformancePPM < LSL 0.00PPM > USL 371895.18PPM Total 371895.18
WithinOverall
Process Capability of Delivery Time
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Xbar 15S 2
USL 18LSL 5
Sigma = 3 Sigma
1.5
0.933193
0.066807
-5
2.87E-07
2.87E-07
0.066807
0.933193
93.3193%
3.00
Sigma Quality LevelDelete if no LSL (Lower Specification Limit)Delete if no USL (Upper Specification Limit)Standard DeviationMean (Average)Enter Values in Yellow
702009 O ##
Worksheet For Calculating Process SigmaWorksheet For Calculating Process SigmaContinuous Data Long-TermContinuous Data Long-Term
2. Determine Area 1:
Find Z1
Look up Z1 in Normal Table
Area 1 = 1 – Look Up Area 1 = 1 – Norm Dist (Z1) = 1 – ( )
4. Determine Total Area:
5. Yield = 1 – Total Area
6. Process Sigma Comes FromTable Look Up Of Yield
Total Area = Area 1 + Area 2 = ( ) + ( )
Yield = 1 – Total Area = 1 – ( )
SigmaST = Look Up Value in Sigma Table
(Z1) = Normal Table Look Up for Z1Norm Dist
=
( ) – ( )( )
=USL – x
sZ1 = =
= x 100%
=
3. Skip this step if there is no LSL
Area 2
2. Determine Area 2:
Find Z2
Look up Z2 in Normal Table
Area 2 = Look Up =
=
=LSL – x
sZ2 = =
(Z2) = Normal Table Look Up for Z2Norm Dist =
( ) – ( )( )
=
=
=
n X valuen X+s valuen USL & Shade Area To The Rightn LSL & Shade Area To The Left
s
x x+s
s USL = 22
Area 1Area 2
10 18
LSL = 8
1. Label The Normal Curve With The Following:
Example:
Example:The average processing time = 15
days (Xbar = 15)
The standard deviation was 2 days (s = 2)
A unit processed longer than 18 days was too late to the customer
(USL = 18)
A unit processed faster than 5 days was too early to the customer
(LSL = 5)
Sigma Quality Level = 3
Sigma Calculator: Continuous Data
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1 N = 2001002 D = 35
3 O =
4 DPMO = #DIV/0!5 Sigma = #DIV/0!
General Worksheet For Calculating Process Sigma
Solve For Defects Per Million Opportunities (DPMO)Look Up Process Sigma In Abridged Sigma Conversion Table
Number Of Defect Opportunities Per Unit
Total Number Of Defects Made (Include Defects Made And Later Fixed)
Number Of Units Processed
Enter Values Below in Yellow
Example:200 pairs of boots were supplied (N = 200)35 shoelaces were found broken (D = 35)
Each shoe had 1 lace and there were 2 shoes per pair (O = 2)
Sigma Calculator: Discrete Data
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Quick Win Documentation Template
1. Root Cause: _________________________________________________2. Obvious Solution: __________________________________________3. Low or No Cost: __________________________________________4. Low Risk:
________________________________________________5. Implementation Plan: ______________________________________________6. Stakeholder (s) Approval: ___________________________________________
Process Name: __________________ Process Lead: ___________________
Process Owner: ______________________ Start Date: ______________
Process Area: ________________________ Stop Date: ______________
Benefits: __________________________________________________________ __________________________________________________________ __________________________________________________________
5s 4-Step Setup Reduction Inventory Reduction MSA Improvements Price reductions Reduced DOWNTIME
(NVA steps or work) Pull System Kaizen events Other
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Sources of Waste ? ? ? ? ?
Sources of Waste
NVA
Defect Overproduction Transportation
WaitingInventoryMotion
Area 1
Sub area 1
Area 1
Sub area 1
Area 1
Sub area 1
Processing
Area 1
Sub area 1
Area 1
Sub area 1
Area 1
Sub area 1
5%5%
5%
40%10%
30%
5%Defect
Overproduction
Transportation
Waiting
Inventory
Motion
Processing
< Insert your waste percentage as shown
in pie chart >
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Swim Lane Process Map
Client Contact
Client HR
Admin
Client Mgr
Places information
into HR database
Sends Email to Admin
Sends exit date to IT, telecom & facilities
Re-verifies with mgr on employee’s exit status
NT Admin
Email Vendor
Utilize e-mail vendor’s web tool to submit delete
request to vendor
Sends Email to Admin
Generates ticket & forwards to Admin
Delete account
Mark request as completed on
admin web site
Create ticket if request coming
directly from client
Avg.Delay2 days
Avg. Delay2 days
Avg.Delay1 day
Avg.Delay1 day
Avg.Delay
4 days
Notify HR of employee exit date
Form require
approval?
No
Secure approval(s)
Yes
Note: Steps in blue shapes are non-value added steps
Admin closes ticket and
manager notified
Avg. Delay2 days
Oval shapes : Start/Stop of processDiamonds: Decision pointsRectangles: process stepsHalf-Moon: Delay/Queue Time
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Value Stream MapCurrent State
Order Mgmt Supervisor
DISTOrder MgmtOrder MgmtOrder Mgmt Order Mgmt
P/T = 2 min
Error Rate=2%
Volume=800
P/T = 6 Min
Error Rate=0%
Volume=800
P/T = 6 Min
Error Rate=2%
Volume=800
P/T = 2 Min
Error Rate=1%
Volume=800
20 Orders
3 min
LargeBusiness
Home
6 Customers
5 Customers
3 Customers
SmallBusiness
CustomerInfo
4
ProductNeed4
Pricing4
ShippingInfo
4
PickPack & Ship
P/T = 120 Min
Error Rate=1%
Volume=1200
10
2 min 6 min 6 min 2 min 120 min
240 min5 min
Customer call time = 24 min
Service lead time = 384 minSUPPLIERS
2-5 days
Manual Update
Weekly Update
Phone CallTrigger:
Completion Criteria:
Cycle Time:
Takt Time:
Number of People:
Number of Approvals:
Items in Inbox:
% Rework:
# of Iterations (cycles):
# of Databases:
Top 3 Rework Issues:
1.
2.
3.
CUSTOMER
Screen for Acct Mgr
Order Mgmt
Phone Call
P/T = 3 min
Lost calls=10%
Volume=1200
Simplify/ Mistake Proof
AutomateMonitoring
ForecastImprovement
ImproveVisibility
Simplify/Combine
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Business Impact
State financial impact of future project leverage opportunities Separate “hard or Type 1” from “soft Type 2 or 3” dollars
Annual Estimate Replicated Estimate
Revenue Enhancement
• Type 1: ?• Type 2: ?• Type 3: ?
• Type 1: ?• Type 2: ?• Type 3: ?
Expenses Reduction
• Type 1: ?• Type 2: ?• Type 3: ?
• Type 1: ?• Type 2: ?• Type 3: ?
Loss Reduction • Type 1: ?• Type 2: ?• Type 3: ?
• Type 1: ?• Type 2: ?• Type 3: ?
Cost Avoidance • Type 1: ?• Type 2: ?• Type 3: ?
• Type 1: ?• Type 2: ?• Type 3: ?
Total Savings • Type 1: ?• Type 2: ?• Type 3: ?
• Type 1: ?• Type 2: ?• Type 3: ?
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Business Impact Details
Type 1: Describe the chain of causality that shows how you determined the Type 1 savings. (tell the story with cause–effect relationships, on how the proposed change should create the desired financial result (savings) in your project )
Show the financial calculation savings and assumptions used. Assumption #1 (i.e. source of data, clear Operational Definitions?) Assumption #2 (i.e. hourly rate + incremental benefit cost + travel)
Type 2: Describe the chain of causality that shows how you determined the Type 2 savings. (tell the story with cause–effect relationships, on how the proposed change should create the desired financial result (savings) in your project )
Show the financial calculation savings and assumptions used. Assumption #1 (i.e. Labor rate used, period of time, etc…) Assumption #2 (i.e. contractor hrs or FTE, source of data, etc…)
Describe the Type 3 Business Impact(s) areas and how these were measured Assumption #1 (i.e. project is driven by the Business strategy?) Assumption #2 (i.e. Customer service rating, employee moral, etc…)
Other Questions Stakeholders agree on the project’s impact and how it will be measured in financial terms? What steps were taken to ensure the integrity & accuracy of the data? Has the project tracking worksheet been updated?
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Current Status
Key actions completed
Issues Lessons
learned Communication,
team building, organizational activities
W/E:
Due Revised Due
For deliverables due thru:
Deliverable/Action Who Due Revised Due Comments/Resolution Need Help
Issue/Risk Who Due Revised Due Recommended Action Need Help
Lean Six Sigma Project Status and Planning
Upcoming Deliverables/Tasks - 2 weeks out Comments
Deliverables/Tasks Completed last week Comments
Actions Scheduled for next 2 Weeks
Current Issues and Risks
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Next Steps
Key actions Planned Lean Six Sigma Tool use
Last Revised:
No. Description/RecommendationStatus
Open/Closed/HoldDue Date
Revised Due Date
Resp Comments / Resolution
12345678910
Lean Six Sigma Project Issue Log
Questions to answer Barrier/risk mitigation activities
18International Standards for Lean Six Sigma
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Sign Off
I concur that the Measure phase was successfully completed on MM/DD/YYYY
I concur the project is ready to proceed to next phase: Analyze
Enter Name Here Deployment Champion
Enter Name Here Financial Representative
Enter Name Here Green Belt/Black Belt
Enter Name Here Master Black Belt
Enter Name Here Sponsor / Process Owner
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Tollgate ReviewsBackup Slides
Go Forward
Wait - Go Back
Halt - HoldD
M
A
I
C
MeasureTollgate Checklist
Has a more detailed Value Stream Map been completed to better understand the process and problem, and where in the process the root causes might reside?
Has the team conducted a value-added and cycle time analysis, identifying areas where time and resources are devoted to tasks not critical to the customer?
Has the team identified the specific input (x), process (x), and output (y) measures needing to be collected for both effectiveness and efficiency categories (i.e. Quality, Speed, and Cost measures)?
Has the team developed clear, unambiguous operational definitions for each measurement and tested them with others to ensure clarity/consistent interpretation?
Has a clear, reasonable choice been made between gathering new data or taking advantage of existing data already collected by the organization?
Has an appropriate sample size and sampling frequency been established to ensure valid representation of the process we’re measuring?
Has the measurement system been checked for repeatability and reproducibility, potentially including training of data collectors?
Has the team developed and tested data collection forms or check sheets which are easy to use and provide consistent, complete data?
Has baseline performance and process capability been established? How large is the gap between current performance and the customer (or project) requirements?
Has the team been able to identify any complete ‘Quick Wins’? Have any Kaizen opportunities been identified to accelerate momentum and results? Have key learning(s) to-date required any modification of the Project Charter? If so,
have these changes been approved by the Project Sponsor and the Key Stakeholders?
Have any new risks to project success been identified, added to the Risk Mitigation Plan, and a mitigation strategy put in place?
Tollgate ReviewTollgate Review
Stop
Key Deliverables: Detailed Value Stream
Map(s) Data Collection Plan Measurement Collection
Results Process Capability Results Current Baseline Process
Performance Quick Wins, if applicable Identification of Kaizen
Opportunities, if applicable Refined Charter, as
necessary Updated Risk Mitigation Plan
Deliverables Uploaded to Central Storage Location or Deployment Management System.
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AnalyzeTollgate Checklist
Has the team examined the process and identified potential bottlenecks, disconnects and redundancies that could contribute to the problem statement?
Has the team analyzed data about the process and its performance to help stratify the problem, understand reasons for variation in the process, and generate hypothesis as to the root causes of the current process performance?
Has an evaluation been done to determine whether the problem can be solved without a fundamental recreation of the process? Has the decision been confirmed with the Project Sponsor?
Has the team investigated and validated (or devalidated) the root cause hypotheses generated earlier, to gain confidence that the “vital few” root causes have been uncovered?
Does the team understand why the problem (the Quality, Cycle Time or Cost Efficiency issue identified in the Problem Statement) is being seen?
Has the team been able to identify any additional ‘Quick Wins’? Have learnings to-date required modification of the Project Charter? If so, have
these changes been approved by the Project Sponsor and the Key Stakeholders? Have any new risks to project success been identified, added to the Risk
Mitigation Plan, and a mitigation strategy put in place?
Tollgate ReviewTollgate Review
Stop
Deliverables: List of Potential Root causes
Prioritized List of Validated Root Causes
Additional “Quick Wins”, if applicable
Refined Charter, as necessary
Updated Risk Mitigation Plan Deliverables Uploaded to Central
Storage Location or Deployment Management System
Has the team identified the key factors (critical X’s) that have the biggest impact on process performance? Have they validated the root causes?
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Long-TermYeild
ProcessSigma (ST)
Defects Per1,000,000
Defects Per100,000
Defects Per10,000
Defects Per1,000
Defects Per100
99.99966% 6.0 3.4 0.34 0.034 0.0034 0.0003499.9995% 5.9 5 0.5 0.05 0.005 0.000599.9992% 5.8 8 0.8 0.08 0.008 0.000899.9900% 5.7 10 1 0.1 0.01 0.00199.8000% 5.6 20 2 0.2 0.02 0.00299.9970% 5.5 30 3 0.3 0.03 0.00399.9960% 5.4 40 4 0.4 0.04 0.00499.9930% 5.3 70 7 0.7 0.07 0.00799.9900% 5.2 100 10 1 0.1 0.0199.9850% 5.1 150 15 1.5 0.15 0.01599.9770% 5.0 230 23 2.3 0.23 0.02399.9670% 4.9 330 33 3.3 0.33 0.03399.9520% 4.8 480 48 4.8 0.48 0.04899.9320% 4.7 680 68 6.8 0.68 0.06899.9040% 4.6 960 96 9.6 0.96 0.09699.8650% 4.5 1350 135 13.5 1.35 0.13599.8140% 4.4 1860 186 18.6 1.86 0.18699.7450% 4.3 2550 255 25.5 2.55 0.25599.6540% 4.2 3460 346 34.6 3.46 0.34699.5340% 4.1 4660 466 46.6 4.66 0.46699.3790% 4.0 6210 621 62.1 6.21 0.62199.181% 3.9 8190 819 81.9 8.19 0.81998.930% 3.8 10700 1070 107 10.7 1.0798.610% 3.7 13900 1390 139 13.9 1.3998.220% 3.6 17800 1780 178 17.8 1.7897.730% 3.5 22700 2270 227 22.7 2.2797.130% 3.4 28700 2870 287 28.7 2.8796.410% 3.3 35900 3590 359 35.9 3.5995.540% 3.2 44600 4460 446 44.6 4.4694.520% 3.1 54800 5480 548 54.8 5.4893.320% 3.0 66800 6680 668 66.8 6.6891.920% 2.9 80800 8080 808 80.8 8.0890.320% 2.8 96800 9680 968 96.8 9.6888.50% 2.7 115000 11500 1150 115 11.586.50% 2.6 135000 13500 1350 135 13.584.20% 2.5 158000 15800 1580 158 15.881.60% 2.4 184000 18400 1840 184 18.4
78.80% 2.3 212000 21200 2120 212 21.275.80% 2.2 242000 24200 2420 242 24.272.60% 2.1 274000 27400 2740 274 27.469.20% 2.0 308000 30800 3080 308 30.865.60% 1.9 344000 34400 3440 344 34.461.80% 1.8 382000 38200 3820 382 38.258.00% 1.7 420000 42000 4200 420 4254.00% 1.6 460000 46000 4600 460 46
50% 1.5 500000 50000 5000 500 5046% 1.4 540000 54000 5400 540 5443% 1.3 570000 57000 5700 570 5739% 1.2 610000 61000 6100 610 6135% 1.1 650000 65000 6500 650 6531% 1.0 690000 69000 6900 690 6928% 0.9 720000 72000 7200 720 7225% 0.8 750000 75000 7500 750 7522% 0.7 780000 78000 7800 780 7819% 0.6 810000 81000 8100 810 8116% 0.5 840000 84000 8400 840 8414% 0.4 860000 86000 8600 860 8612% 0.3 880000 88000 8800 880 8810% 0.2 900000 90000 9000 900 908% 0.1 920000 92000 9200 920 92
Abridged Process Sigma Conversion Table…
24
z 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.090.0 0.0000 0.0040 0.0080 0.0120 0.0160 0.0190 0.0239 0.0279 0.0319 0.03590.1 0.0398 0.0438 0.0478 0.0517 0.0557 0.0596 0.0636 0.0675 0.0714 0.07530.2 0.0793 0.0832 0.0871 0.0910 0.0948 0.0987 0.1026 0.1064 0.1103 0.11410.3 0.1179 0.1217 0.1255 0.1293 0.1331 0.1368 0.1406 0.1443 0.1480 0.15170.4 0.1554 0.1591 0.1628 0.1664 0.1700 0.1736 0.1772 0.1808 0.1844 0.18790.5 0.1915 0.1950 0.1985 0.2019 0.2054 0.2088 0.2123 0.2157 0.2190 0.22240.6 0.2257 0.2291 0.2324 0.2357 0.2389 0.2422 0.2454 0.2486 0.2517 0.25490.7 0.2580 0.2611 0.2642 0.2673 0.2704 0.2734 0.2764 0.2794 0.2823 0.28520.8 0.2881 0.2910 0.2939 0.2969 0.2995 0.3023 0.3051 0.3078 0.3106 0.31330.9 0.3159 0.3186 0.3212 0.3238 0.3264 0.3289 0.3315 0.3340 0.3365 0.33891.0 0.3413 0.3438 0.3461 0.3485 0.3508 0.3513 0.3554 0.3577 0.3529 0.36211.1 0.3643 0.3665 0.3686 0.3708 0.3729 0.3749 0.3770 0.3790 0.3810 0.38301.2 0.3849 0.3869 0.3888 0.3907 0.3925 0.3944 0.3962 0.3980 0.3997 0.40151.3 0.4032 0.4049 0.4066 0.4082 0.4099 0.4115 0.4131 0.4147 0.4162 0.41771.4 0.4192 0.4207 0.4222 0.4236 0.4251 0.4265 0.4279 0.4292 0.4306 0.43191.5 0.4332 0.4345 0.4357 0.4370 0.4382 0.4394 0.4406 0.4418 0.4429 0.44411.6 0.4452 0.4463 0.4474 0.4484 0.4495 0.4505 0.4515 0.4525 0.4535 0.45451.7 0.4554 0.4564 0.4573 0.4582 0.4591 0.4599 0.4608 0.4616 0.4625 0.46331.8 0.4641 0.4649 0.4656 0.4664 0.4671 0.4678 0.4686 0.4693 0.4699 0.47061.9 0.4713 0.4719 0.4726 0.4732 0.4738 0.4744 0.4750 0.4756 0.4761 0.47672.0 0.4772 0.4778 0.4783 0.4788 0.4793 0.4798 0.4803 0.4808 0.4812 0.48172.1 0.4821 0.4826 0.4830 0.4834 0.4838 0.4842 0.4846 0.4850 0.4854 0.48572.2 0.4861 0.4864 0.4868 0.4871 0.4875 0.4878 0.4881 0.4884 0.4887 0.48902.3 0.4893 0.4896 0.4898 0.4901 0.4904 0.4906 0.4909 0.4911 0.4913 0.49162.4 0.4918 0.4920 0.4922 0.4925 0.4927 0.4929 0.4931 0.4932 0.4934 0.49362.5 0.4938 0.4940 0.4941 0.4943 0.4945 0.4946 0.4948 0.4949 0.4951 0.49522.6 0.4953 0.4955 0.4956 0.4957 0.4959 0.4960 0.4961 0.4962 0.4963 0.49642.7 0.4965 0.4966 0.4967 0.4968 0.4969 0.4970 0.4971 0.4972 0.4973 0.49742.8 0.4974 0.4975 0.4976 0.4977 0.4977 0.4978 0.4979 0.4979 0.4980 0.49812.9 0.4981 0.4982 0.4982 0.4983 0.4984 0.4984 0.4985 0.4985 0.4986 0.49863.0 0.4987 0.4987 0.4987 0.4988 0.4988 0.4989 0.4989 0.4989 0.4990 0.49903.1 0.4990 0.4991 0.4991 0.4991 0.4992 0.4992 0.4992 0.4992 0.4993 0.49933.2 0.4993 0.4993 0.4994 0.4994 0.4994 0.4994 0.4994 0.4995 0.4995 0.49953.3 0.4995 0.4995 0.4995 0.4996 0.4996 0.4996 0.4996 0.4996 0.4996 0.49973.4 0.4997 0.4997 0.4997 0.4997 0.4997 0.4997 0.4997 0.4997 0.4997 0.4998
Table of the Standard Normal (z) Distribution
Welcome
and Introduction
s25
Lean Six Sigma DMAIC Improvement Process
Tollgate Review
Tollgate Review
Stop
Define
Measure
Analyze
Improve
Control
Tollgate Review
Tollgate Review
Stop
Tollgate Review
Tollgate Review
Stop
Tollgate Review
Tollgate Review
Stop
Define the opportunity from both the customer and business perspective
Understand the baseline process performance
Identify the critical X factors and root causes impacting process performance
Develop solutions linked to critical x’s
Implement solutions & control plan
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15%
35% 35%
15%
0%
5%
10%
15%
20%
25%
30%
35%
40%
Innovators Early Adopters Late Adopters Resistors
Attitude Charting
Key Constituents Map
Finance37%
Operations25%
Customer13%
HR25%
Attitude Charting & Key Constituency Map (Optional)
“Critical mass must be won-over”
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Sample Size: Continuous Data (Optional)
Calculation for Confidence Intervals - Continuous Data
Population Size (N) 10,000
Confidence Level (1-alpha) 0.95000 (Percent expressed as decimal)
Observed Sample Mean 25.00000 (Best estimate from data)
Observed Sample Std. Dev. 5.00000 (Best estimate from data)
Actual Sample Size 100
Lower Conf. Int. Limit (Mean) 23.86764596 (Corrected for finite population)Upper Conf. Int. Limit (Mean) 26.13235404 (Corrected for finite population)
Lower Conf. Int. Limit (S.D.) 4.390034232Upper Conf. Int. Limit (S.D.) 5.808376227
Calculation for Sample Size - Continuous Data
Population Size (N) 860
Confidence Level (1-alpha) 0.95000 (Percent expressed as decimal)
Power Level (1-beta) 0.90000 (Percent expressed as decimal)
Standard Deviation (s) 10.00000 (Best prior estimate or Range/5)
Required Precision (+/- delta) 3.00000 (Margin of Error)
Initial Sample Size 117 (Assumes infinite population)Corrected for Population 104 (Correction for finite population)
Recommended Sample Size 104
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? ? ? ? ?
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Sample Size:Discrete Data (Optional)
Calculation for Sample Size - Discrete Data (Proportions)
Population Size (N) 1,000
Confidence Level (1-alpha) 0.95000 (Percent expressed as decimal)
Power Level (1-beta) 0.90000 (Percent expressed as decimal)
Expected Proportion (p) 0.50000 (Best prior estimate or 0.50)
Required Precision (+/- delta) 0.03000 (Margin of Error)
Initial Sample Size 2919 (Assumes infinite population)Corrected for Population 746 (Correction for finite population)
Recommended Sample Size 746Calculation for Confidence Interval - Discrete Data
Population Size (N) 10,000
Confidence Level (1-alpha) 0.95000 (Percent expressed as decimal)
Observed Proportion (p) 0.50000 (Best estimate from data)
Actual Sample Size 100
Lower Conf. Int. Limit 0.402488147 (Corrected for finite population)Upper Conf. Int. Limit 0.597511853 (Corrected for finite population)
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Measurement Systems Analysis (MSA) (Optional)
Measurement system is acceptable with the Total % Contribution <10%
Per
cent
Part-to-PartReprodRepeatGage R&R
100
50
0
% Contribution
% Study Var
Sam
ple
Ran
ge
0.10
0.05
0.00
_R=0.0417
UCL=0.1073
LCL=0
1 2 3Sa
mpl
e M
ean
10.00
9.75
9.50
__X=9.7996
UCL=9.8422
LCL=9.7569
1 2 3
Part10987654321
10.00
9.75
9.50
Operator321
10.00
9.75
9.50
Part
Ave
rage
10 9 8 7 6 5 4 3 2 1
10.00
9.75
9.50
Operator
12
3
Gage name:Date of study:
Reported by:Tolerance:Misc:
Components of Variation
R Chart by Operator
Xbar Chart by Operator
Response by Part
Response by Operator
Operator * Part Interaction
Gage R&R (ANOVA) for ResponseGage R&R %ContributionSource VarComp (of VarComp)Total Gage R&R 0.0015896 3.70 Repeatability 0.0005567 1.29 Reproducibility 0.0010330 2.40 Operator 0.0003418 0.79 Operator*Part 0.0006912 1.61Part-To-Part 0.0414247 96.30Total Variation 0.0430143 100.00 Study Var %Study VarSource StdDev (SD) (6 * SD) (%SV)Total Gage R&R .039870 0.23922 19.22 Repeatability 0.023594 0.14156 11.38 Reproducibility 0.032140 0.19284 15.50 Operator 0.018488 0.11093 8.91 Operator*Part 0.026290 0.15774 12.68Part-To-Part 0.203531 1.22118 98.13Total Variation 0.207399 1.24439 100.00
Number of Distinct Categories = 7
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29
Probability Plot (Optional)
40353025201510
99.9
99
95
90
80706050403020
10
5
1
0.1
QTY
Perc
ent
Mean 24.74StDev 4.177N 100AD 0.380P-Value 0.397
Normal - 95% CIProbability Plot of Anderson-Darling Normality
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30
Control Chart(Optional)
The current baseline delivery time is stable over time with both the Moving Range (MR) (3.22 days) and Individual Average (29.13 days) experiencing common cause variation
255 data points collected with zero subgroups, thus the I&MR control chart selected
Observation
Ind
ivid
ua
l V
alu
e2442171901631361098255281
40
35
30
25
20
_X=29.13
UCL=37.70
LCL=20.56
Observation
Mo
vin
g R
an
ge
2442171901631361098255281
10.0
7.5
5.0
2.5
0.0
__MR=3.22
UCL=10.53
LCL=0
I-MR Chart of Delivery Time
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PDCA(Optional)
Plan: ? ?
Do: ? ?
Check: ? ?
Act: ? ?
?
?
?
?
Plan
Do
Check
Act
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5s(Optional)
Sort ? ?Set Order ? ?Shine ? ?Standardize ? ?Sustain ? ?
ITEM NAME TAG NUMBER TAGGED BY
TAG DATE
o RAW MATERIAL o TOOLS o FURNITURE o OTHER (EXPLAIN)
o WIP o SUPPLIES o OFFICE MATERIAL
o FINISHED GOOD o EQUIPMENT o BOOKS/MAGAZINESQUANTITY CELL / AREA
o UNNECESSARY o LEFTOVER MATERIAL
o DEFECTIVE o UNKNOWN
o NON-URGENT o OTHER (EXPLAIN)
o DISCARD o TRANSFER
o IN-CELL STORAGE o LONG-TERM STORAGE
o REDUCE o OTHER (EXPLAIN)
ACTION DESCRIPTION APPROVED BY
DATE
NEW LOCATION NEW CELL / AREA
5s FORM
ACTION TAKEN
IDENTIFICATION
CLASSIFICATION
REASON
DISPOSITION REQUIRED
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Benchmark Analysis(Optional)
Based on the information above, what is the performance objective*?• Reduce defects by % • Reduce long-term DPMO from to .• Improve short-term Z from to .
*If you do not benchmark, performance standards are based on:• For a process with 3 sigma level, decrease % defects by 10x.• For a process with > 3 sigma level, decrease % defects by 2x.• Other….please explain (corporate mandate, compliance/legal, VOC data, etc)
CTQProcess
Capability (X/Y)
BenchmarkGap /
OpportunitySource Assumptions Risks
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34
Key Buying Factor Analysis(Optional)
4.0
5.0
6.0
7.0
8.0
9.0
10.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0CTQ Importance Company Comp 1 Comp 2 Comp 3CTQ Importance Company Comp 1 Comp 2 Comp 3
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Sample Value Stream Mapping Symbols (Optional)
Machining C/T = 36 Sec
Set Up Time 7 Min
Uptime 86%
Process Box
Data Box
IQueue/
Inventory
1
Personnel
Flow(Information)
Electronic Information
Sign Off Point
Push Systems
Truck Shipment
Quotes
Supplier/Customer
Flow(Physical)
Physical Pull
ProjectBurst
SupermarketReplenishment
KanbanStation
PaperKanban
ElectronicData
System F I F OFIFO Lane
PhysicalTransport
“Go See”Monitoring
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To Office Parking LotEAST
Vault
(finance)
Supply
Room
(paper and office supplies)
Records
Room
(Order Management)
OM Supr Office
Reception
Engineering Offices
CafeteriaRestrooms
Foyer
Order Taker 1
Order Taker 2
Order Taker 3
Order Entry 1
Order Entry 2
Order Entry 3
CC & Val 2
CC & Val 3
CC & Val 1
OM LeadPrinter, Fax
Copier
Indicates an in-box or outbox where work (forms/ information) waits to be worked on or transferred
Planning &
Scheduling
Lines indicate paper/information travel:
- No set path
- Lots of rework
Spaghetti Diagram(Optional)
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AS-IS Process Mapping Symbols (Optional)
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