6S 标准培训教材英文

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2. 6 Overview Six Sigma: - A Definition - Applied to GE - GE Quality Initiative - Why This Approach? - Origin of Six Sigma - The “Breakthrough Strategy” - Arriving at Sigma Six Sigma Structure Key Concepts & Tools A Practical ExampleAn Overview....Not a lot of Details!!
3. 6 Overview “Six Sigma” If we can’t express what we know in the form of numbers, we really don’t know much about it. If we don’t know much about it, we can’t control it. If we can’t control it, we are at the mercy of chance. Mikel J. Harry President & CEO Six Sigma Academy, Inc.A Rigorous Method for Measuring & Controlling Our Quality “...will bring GE to a whole new level of quality in a fraction of the time it would have taken to climb the learning curve on our own.”John F. Welch, Jr. 1995 GE Annual Report
4. 6 Overview What Does “Sigma” Mean? Sigma is a Measure of the Consistency of a ProcessIt (is Also the 18th Letter in the Greek Alphabet!
5. Why Does GE Need A Quality Initiative?GE Raising The Bar New Goal to be “Best in the World” vs. #1 or #2 Customers are Expecting More, we Must Deliver “Ship-and-fix” Approach no Longer Tolerated in the Market Aim to Speed Past Traditional Competitors in 5 Years Goal Consistent with Reduced Total Costs We Must Acknowledge Our Vulnerabilities Poor Quality That Impacts Customers Problems with NPI Too High Internal Costs6 Overview We Need a Major Initiative to Move From Where we Are to Where we Want to be
6. 6 Overview Why Does GE Need A Quality Initiative?40%35%30%25%20%10%15% 5%Cost of Failure (% of Sales)Defects per Million3.4233621066,807308,537500,000Sigma654321 Estimated Cost of Failure in US Industry is 15% of Sales; Taking GE From a 3 to a 6 Company Will Save ~ $10.5 Billion per Year!
7. Why “Six Sigma”?Proven Successful in “Quality-Demanding” Industries e.g., Motorola, Texas Instruments (many process steps in series) Proven Method to Reduce Costs Highly Quantitative Method – Science and Logic Instead of Gut Feel Includes Manufacturing & Service (close to customer) and Provides Bridge to Design for Quality Concepts Has Support and Commitment of Top ManagementIt Works!!!
8. 6 Overview Sigma3456SpellingMoneyTime1.5 Misspelled Words per Page in a Book1 Misspelled Word per 30 Pages in a Book1 Misspelled Word in a set of Encyclopedias1 Misspelled Word in all of the Books in a Small Library$2.7 Million Indebtedness per $1 Billion in Assets$570 Indebtedness per $1 Billion in Assets$63,000 Indebtedness per $1 Billion in Assets$2 Indebtedness per $1 Billion in Assets3 1/2 Months per Century2 1/2 Days per Century30 Minutes per Century6 Seconds per Century6 is Several Orders of Magnitude Better Than 3!!!Sigma: A Measure of Quality
9. 6 Overview Where Does “Six Sigma” Come From? Mikel J. Harry one of the Original Architects Previously Headed Quality Function at ABB and Motorola Now President/CEO of Six Sigma Academy in Phoenix, Arizona Has Consulted for Texas Instruments, Allied Signal (and others) Currently Retained by GE to Teach the Implementation, Deployment and Application of Six Sigma Concepts & Tools Learning from Those Who Have had Success With 6Will Accelerate its Implementation at GE
10. 6 Overview So...What is Six Sigma? A Measurement System A Problem-Solving Approach A Disciplined Change Process“THE SIX SIGMA BREAKTHROUGH STRATEGY”MeasureAnalyzeImproveControl
11. 6 Overview How Do We Arrive at Sigma?Measuring & Eliminating Defects is the “Core” of Six SigmaMeasurement SystemIdentify the CTQsLook for Defects in Products or Services “Critical to Quality” Characteristics or the Customer Requirements for a Product or Service Count Defects or failures to meet CTQ requirements in all process steps Define Defect Opportunities Any step in the process where a Defect could occur in a CTQ Arrive at DPMO Use the SIGMA TABLEConvert DPMO to Sigma Defects Per Million Opportunities2 3 4 5 6308,537 66,807 6,210 233 3.4PPM Defects per Million of Opportunity Sigma Level
12. 6 Overview Measurement System2 3 4 5 6308,537 66,807 6,210 233 3.4PPM SIGMA LEVEL DEFECTS per MILLION OPPORTUNITYIRS Tax AdviceBest CompaniesAirline SafetyAverage CompanyGEAirline BaggageDoctor’s PrescriptionRestaurant BillsAverage Company in 3 to 4Range Some Sigma “Benchmarks”
13. 6 Overview Measurement SystemA Graphic/Quantitative Perspective on VariationAverage ValueMany Data Sets Have a Normal or Bell ShapeNumber of People Arriving at CRDTime7:00 7:15 7:30 7:45 8:00 8:15 8:30 8:45 9:00 9:15
14. 6 Overview Problem Solving ApproachCenter ProcessReduce SpreadXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXOff-TargetUnpredictableOn-Target 6Helps us Identify and Reduce VARIATION due to: - Insufficient Process Capability - Unstable Parts & Materials - Inadequate Design Margin
15. TargetUSLLSLTargetUSLLSLTargetUSLLSLCenter ProcessReduce SpreadOff-TargetUnpredictableOn-TargetDefects6 Overview Problem Solving Approach“Lower Specification Limit” “Upper Specification Limit”Less Variation Means Fewer Defects & Higher Process Yields
16. 6 Overview Problem Solving ApproachKey Components of “BREAKTHROUGH STRATEGY”MeasureAnalyzeImproveControl Identify CTQ & CTP (Critical to Process) Variables Do Process Mapping Develop and Validate Measurement Systems Benchmark and Baseline Processes Calculate Yield and Sigma Target Opportunities and Establish Improvement Goals Use of Pareto Chart & Fishbone Diagrams Use Design of Experiments Isolate the “Vital Few” from the “Trivial Many” Sources of Variation Test for Improvement in Centering Use of Brainstorming and Action Workouts Set up Control Mechanisms Monitor Process Variation Maintain “In Control” Processes Use of Control Charts and Procedures A Mix of Concepts and Tools Will Also Integrate with NPI Process
17. 6 Overview Disciplined Change ProcessA New Set of QUALITY MEASURES Customer Satisfaction Cost of Poor Quality Supplier Quality Internal Performance Design for Manufacturability Will Apply to Manufacturing & Non-Manufacturing Processes and be Tracked & Reported by Each Business
18. 6 Overview StructureQuality Council Members: Labs & Functions “Pipeline” & BB Project Priorities Training & Certification Measurements & Rewards CommunicationsChampions Leadership: Overall Initiative Project Funding HR: Training & RewardsBlack Belts Lead 6 Project Teams “Measure/Analyze” “Improve/Control” Out with Businesses Here at CRDMaster Black Belts Teach 6 Mentor Black Belts Monitor BB Projects Work “Pipeline” Projects A Resource PoolTeam Members Learn/Use 6 Tools Work on BB Projects Part of The Job Out with Businesses 6 Projects with the GE Businesses
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21. Tabulation of GE Six Sigma Results
22. Benefit Target & UpdateCurrent benefits level @ 10.865 MMQPID loading : Carryover from 1999 : 4.059 Completed Projects 2000 : 3.313 Active Projects 2000 : 3.285 Total : 10.865 MM
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24. Key Concepts & Tools 6 Overview
25. 6 Overview Changing Focus From Output to Process Y Dependent Output Effect Symptom Monitor X1. . . XN Independent Input-Process Cause Problem Control Identifying and Fixing Root Causes Will Help us Obtain the Desired Outputf (X)Y =
26. Process Capability6 Overview Sustained Capability of the Process (long term)USLTTime 1Time 2Time 3Time 4Inherent Capability of the Process (short term)LSLTargetOver Time, a “Typical” Process Will Shift and Drift by Approximately 1.5
27. 6 Overview “Short Term Centered” versus “Long Term Shifted”Six Sigma CenteredLSLUSLT Process CapabilitySHORT TERM.001 ppm.001 ppm+6 LONG TERMLSLUSLT3.4 ppmSix Sigma Shifted 1.5 Process CapabilityHigher Defect Yield in Long Term Process Capability than Short Term Process Capability -6 4.5 1.5
28. 6 Overview Tying it All TogethershiftCDAB0.5 1.0 1.5 2.0 2.51 2 3 4 5 6C O N T R O LPOORGOODTECHNOLOGYPOORGOODABCD Good Control/ Poor TechnologyPoor Control/Poor TechnologyPoor Control/ Good Technology WORLD CLASS!!!short termProblem Could be Control, Technology or Both
29. 6 Overview Short Term CapabilityShort Term Capability Ratio(Cp)Cp =LSL-6USLExampleUSLLSL 3.0==-3.063.0-( - 3.0Cp =Cp =1LSLUSL2.5 0.53.0Process MeanTTargetA 3 ProcessThe Potential Performance of a Process, if it Were on Target
30. 6 Overview Long Term Capability (Cpk)CpCpk=Long Term Capability RatioExampleCp =1 (previous chart)Target = -0.5 =0Cpk1 - (-0.5-03 =Cpk =0.83-Off-Target Penalty Target - 3The Potential Performance of a Process, Corrected for an Off-Target MeanLSLUSL2.5 0.53.0Process MeanTTargetA 3 Process
31. 6 Overview Z - Scale of MeasureZ =A Unit of Measure Equivalent to the Number of Standard Deviations that a Value is Away from the Target Value-3.0-0.53.0Z - Values USLLSL2.50.53.0= Process MeanZ TTarget 0A 3 Process
32. The Definitions of YieldFinal Test Process(Process 4)PassProcess 3Process 1Process 2100(Units Tested) 65 70 8291Yield 1Yield 2Yield 3 Loss 1 Loss 3Rejects Loss 2 9 9 125 First Time Yield (Yft)=Units PassedUnits Tested= 65 70=0.93 Rolled Thruput Yield (Yrt)=(Yield 1)(Yield 2)(Yield 3) . . . . = 91 82 65 70(((())))=0.65100 91 70 82 Normalized Yield (Ynm)==1/n(Yrt)(0.65)1/4=0.89( n: Total Number of Processes ) 6 Overview Yield Exclusive of ReworkProbability of Zero DefectsAverage Yield of All Processes
33. 6 Overview The Impact of ComplexityThe Impact of ComplexityRolledRolled Yield YieldNumber of OperationsNumber of Operations1.001.000.900.900.800.800.700.700.600.600.500.500.400.400.300.300.200.200.100.100.000.00 1 10 100 1,000 10,000 100.000 1,000,000 1 10 100 1,000 10,000 100.000 1,000,000Process Mean Centered on Each OperationProcess Mean Centered on Each Operation 1 10 100 1,000 10,000 100.000 1,000,000 1 10 100 1,000 10,000 100.000 1,000,000RolledRolled Yield YieldNumber of OperationsNumber of Operations1.001.000.900.900.800.800.700.700.600.600.500.500.400.400.300.300.200.200.100.100.000.00 As the Number of Operations Increases, a High Rolled Yield Requires a High for Each Operation 5 4 3 6 6 5 4 3Process Mean Shifted 1.5at Each Operation
34. 6 Overview Baselining & Benchmarking an Existing Processp (x)DefectsBenchmarkBaseline Entitlement Benchmark.....A World-Class Performance Entitlement.....Achievable Performance Given the Investments Already Made Baseline.....The Current Level of PerformanceBaselining = Current Process / Benchmarking = Ultimate Goal
35. Some Basic 6-Related Tools6 Overview Scatter Diagram Over Slept Car Would Not StartWeather Family ProblemsOtherPareto Diagram Frequency of OccurenceReasons for Being Late for WorkArrival Time at WorkTime Alarm Went Off
36. MaterialsPeopleThe HistogramControl Charts---------------------------------------------6 Overview Some Basic 6-Related ToolsThe Fishbone DiagramMeasurementsMethodsTechnologyStatementCause & EffectBeing Late for WorkPlot of Daily Arrival Time 9:157:00 7:15 7:30 7:45 8:00 8:15 8:30 8:45 9:00Average ValueNumber of People Arriving at CRDTime
37. 6 Overview LCLUCLRange ChartROut of Control ConditionLCLXUCLX Bar ChartSome Basic 6-Related ToolsLCL = Lower Control LimitUCL = Upper Control LimitX = MeanR= Average RangeMonitors Changes in Average or Variation Over Time
38. Design of Experiments6 Overview SCREENINGOPTIMIZATIONCHARACTERIZATION For Experiments Involving a Large Number of Factors Useful in Isolating the “Vital Few “ from the “Trivial Many” For Experiments Involving a Relatively Small Number of Factors Useful When Studying Relatively Uncomplicated Effects & Interactions For Experiments Involving Only 2 or 3 Factors Useful When Studying Highly Complicated Effects & RelationshipsDOE is More Effective Than Testing One Factor at a Time
39. 6 Overview Using the “One Factor at a Time” Approach Reduce Commute to Work to 15 Minutes (without working an abnormal work schedule) The GoalThe Variables Time of Departure from Home & Route Taken to WorkThe Approach Try 3 Potential Routes at Current Departure Time (7:45), Select the Best & Vary the Departure Time ‘til we get to 15 MinutesTime of Departure3 2 17:157:307:458:008:15RouteCombination SelectedThe ResultUse Route 2 and Leave at 7:15 to Reach Goal
40. 6 Overview Using “Design of Experiments” (DOE)Time of DepartureDOE (i) Better Accounts for Interactive Variables Missed by “One Factor at a Time”, and (ii) Efficiently Searches for “Sweet Spot” in Parameter SpaceThe Variables Time of Departure from Home & Route Taken to WorkThe Approach Vary time of Departure and Route Simultaneously, in a Systematic FashionThe ResultA Better Combination Allowing 15 More Minutes of Sleep!!!Actual Commuting Time Averages (minutes)3 2 17:157:307:458:008:15Route17 20 23 21 1915 18 20 19 1612 15 21 20 18 Original Conclusion Best Combination “Sweet Spot” Reduce Commute to Work to 15 Minutes (without working an abnormal work schedule) The Goal
41. A Practical Example (The “Cookbook”)6 Overview
42. 6.....and Baking BreadYEAST FLOURUsing a 12 Step Process6 Overview The “BETTER BREAD” Company
43. Step 1.....Selecting “Critical to Quality” (CTQs or Y)What is Important to the Customer? Rise Texture Smell Freshness TasteY = Taste!!6 Overview Measure
44. Step 2.....Defining Performance Standards for CTQs or Y6 Overview How Could We Measure Taste (Y)? Panel of Tasters Rating System of 1 to 10 Target: Average Rating at 8 Desired: No Individual Ratings (“defects”) Below 7 Y = 1 2 3 4 5 6 7 8 9 10 TargetDefectsWorstBestBut.....Is this the Right System?Measure
45. 6 Overview Step 3.....Validating the Measurement System for YHow Could We Approach This? Blindfolded Panel Rates Several Loaf Samples Put “Repeat” Pieces from Same Loaf in Different Samples Consistent Ratings* on Pieces from Same Loaf = “Repeatability” Consistent Ratings* on Samples Across the Panel = “Reproducibility” “Repeatability” &“Reproducibility” Suggest Valid Measurement Approach Panel Member Loaf 1 Loaf 2 Loaf 3 A 5 8 9 B 4 9 1 C 4 9 2 D 8 9 8 E 4 8 2 F 5 9 1 G 8 9 2* Within One Taste UnitMeasure
46. 6 Overview Step 4.....Establish Product Capability for Y (Taste)This is a 3 Process!7 Defects (ratings below 7)24 Ratings (from our panel)=.292292,000 Defects per 1,ooo,ooo LoavesOR7 6 5 4 3 2 11 2 3 4 5 6 7 8 9 10 # of RatingsRating64321143Defects <7Target = 8AnalyzeHow Do We Approach This? Bake Several Loaves Under “Normal” Conditions Have Taster Panel Again Do the Rating Average Rating is 7.4 But Variation is too Great for a 6 Process3 x 10 + 4 x 9 + 6 x 8 + 4 x 7 + 3 x 6 + 2 x 5 + 1 x 4 + 1 x 31 + 1 + 2 + 3 + 4 + 6 + 4 + 3
47. 6 Overview Step 5.....Define Improvement Objectives for Y (Taste)How do we Define Improvement? Benchmark the Competition Focus on Defects ( i.e. taste rating < 7) Determine What is an “Acceptable Sigma Level” Set Improvement Objectives Accordingly Maybe a 5 Process Will Suffice!1,000,000 - 100,000 - . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10,000 - . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,000 - . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 - . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 - . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 - 2 3 4 5 6 7 “BETTER BREAD” Baking Process Best Competitor Range for Improvement Defects Per MillionSigma Scale Freihofer WONDER Pepperidge Farm SunbeamAnalyze
48. 6 Overview Step 6.....Identify Sources of Variation in Y (Taste)How do we Determine the Potential Sources of Variation (Xs)? Have the Chefs Brainstorm Some Likely Ones Might be: - Amount of Salt Used - Brand of Flour - Baking Time - Baking Temperature - Brand of Yeast YEAST FLOURMultiple Sources: Chefs, Suppliers, ControlsAnalyze
49. 6 Overview Step 7.....Screen Potential Causes of Variation (Xs)How do we Screen for Causes of Variation (Xs)? Design an Experiment Use Different Sources of Potential Variation Have Panel Rate the Bread Used in the Experiment Results Lead to the “Vital Few” CausesYEAST FLOURSourceConclusionNegligibleMajor CauseNegligibleMajor CauseNegligibleFocus on The “Vital Few”Improve
50. 6 Overview Step 8.....Discover Variable Relationships Between “Vital Few” (Xs) and YHow do we Find the Relationship Between the “Vital Few” (Xs) and Taste (Y)? Conduct a More Detailed Experiment Focus: Oven Temperature from 325 to 375 and 3 Brands of Flour RUN# TEMP BRAND 1 325 A 2 325 B 3 325 C 4 350 A 5 350 B 6 350 C 7 375 A 8 375 B 9 375 C FLOUR FLOUR FLOURBrand ABrand BBrand CImproveResults: 350 & Brand A is Best Combination of Temperature & FlourNote: Time is a Factor Only if Temperature Changes Significantly
51. 6 Overview Step 9.....Establish Tolerances on “Vital Few” (Xs)How do we Ensure Oven Temperature is Controlled? Data Suggests 350 ( 5 ) is best Temperature to Reduce Taste Variation Brand A Flour to be Used Except in Case of Emergency “BETTER BREAD” to Search for Better Alternative Supplier of Flour Just in Case FLOURBrand ABut.....Is Our Measurement System Correct?Improve
52. 6 Overview Step 10.....Validate the Measurement System for XsHow Could We Approach This? Need to Verify the Accuracy of Our Temperature Gauges Need for “Benchmark” Instrumentation for Comparison Rent Some Other “High End” Gauges Compare the ResultsVerify that our Instruments are AccurateControl
53. 6 Overview Step 11.....Determine Ability to Control Vital Few XsHow Could We Approach This? Check A Number of Ovens Monitor Temperatures Over Time Focus on the Process Capability Look for Degree of VariationVariation OK But...Average is High (and the algorithm should be checked)30345 # of OvensTemperature34635734734834935035135235335435535625201510 5Control
54. 6 Overview Step 12.....Implement Process Control System on XsWhat do we do Going Forward? Check Ovens Daily for Temperature Levels Audit Usage Frequency of Alternative Flour Supplier (e.g., Brand C) Periodically Reassemble the Panel to Test Taste Chart the ResultsAnd.....Plot the Data Over Time FLOUR“Brand C”354 353 352 351 350 349 348 1 3 5 7 9 11 13 15 17 19 21 23 25Control

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