6 Sigma training

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1. 6 簡介6 SIGMA 起源及主要概念 6 SIGMA 組織及人員認證基本統計應用執行主要步驟 D-M-A-I-C Case Study QRA : 2001/8/27
2. The Origins of SixSigma It originated in the 1980's as Motorola responded to the threat of Japanese competition which had far lower defective rates. The approach spread to AlliedSignal and to General Electric, whose Chief Executive Officer, Jack Welch, has been the most passionate advocate of SixSigma. Since introducing it worldwide in 1996, GE has made over $1 billion of cost savings.
3. 1979 年，當時 Motorola一位資深業務主管 Arthur Sundry 在高階主管會議上說："Our quality levels really stink !" Six Sigma Quality Program 此名稱乃為 Motorola工程師 Bill Smith所建議，為Robert Galvin所採納。何謂 6-Sigma ?Motorola :
4. 衡量指標標竿研究願景 Philosophy 方法工具符號目標價值s23456308,53766,8076,2102333.4.sDPMO可用以計算與衡量任何流程Sigma 之另一稱呼為標準差2000年達成 6-Sigma水準 4, 1996 --- Jack Welch變成我們文化的一部份 -- 成為我們生活的一部份.59
5. 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
6. What Does “Sigma” Mean? Sigma is a Measure of the Consistency of a ProcessIt (is Also the 18th Letter in the Greek Alphabet!
7. Motorola公司認為數據是滿足顧客的關鍵，他們常說： 1.如無法用數據表示我們所知的,那麼我們對它所知不多 (If we cannot express what we know in numbers, we don't know much about it) 2.如果對它所知不多，就無法控制它 (If we don't know much about it, we cannot control it) 3.如果我們不能控制它，那只有靠運氣了 (If we cannot control it, we are at the mercy of chance)
8. 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!!!
9. 6有多小?SigmaPPM0.0020.574263.372,70045,500317,310面積一般教室2倍約6甲地約30個天安門廣場略大於台北市東莞市台灣省的面積時間1 秒鐘4.8 分鐘9 小時半個月約 9 個月5 年6-Sigma 狹隘解釋 -- DPPM
10. 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
11. 6的品質水準0.002 DPPM , Cp=2中心值±1.5的偏移3.4 DPPM, Cpk=1.5或用 DPMO (Defects Per Million Opportunities)表示
12. 4.5
13. 偏移±1.5在動態的真實世界中，每一件事都在不停的變化著溫度溼度工具的磨耗原料的差異 ...... 1.5乃由機率、估計、經驗而來參考資料:Evans, D.H. (1975) : Statistical Tolerancing : The State of the Art, Part III. Shifts and Drifts.
14. 6的四個假設常態分配 ±1.5偏移 和已知缺點乃隨意分佈，且不同零件製程相互獨立
15. 品質改善的流程1. 定義產品或服務 2. 鑑定顧客及其需求 3. 列出滿足顧客需求所需之條件 4. 定義(規劃)流程 5. 防範流程錯誤並消除浪費 6. 確保持續改善廣義解釋 -- 流程改善(改造)/設計
16. Six-Sigma 如何創造不一樣局面 ?願景 (Vision) 哲學 (Philosophy) 積極目標 (Aggressive goal) 量化指標 (Metric, standard of measurement) 方法 (Method) 工具用於: 顧客焦點 (Customer focus) 突破性改善 (Breakthrough improvement) 持續改善 (Continuous improvement) 人員參與 (People Involvement)
17. Six-Sigma 願景 Six-Sigma 的願景是將我們所做的每一件事, 透過達成Six-Sigma水準的表現, 交付世界級品質產品或服務以取悅客戶.
18. Six-Sigma 哲學Six-Sigma 哲學是應用結構化、系統化觀點於我們事業各嶺域達成突破性改善
19. 推行 6-Sigma 之必要條件 •重點攻擊 •與變格管理相聯接 •依核心流程(非功能) 組織黑帶或碩士級黑帶 • 儘量聯接與事業相關重點, 共同與言… •追求即早勝利 (大且易見) •支持基礎結構/追溯系統 •改變衡量系統以更有效推動專案行動 • 選擇與工作直接相關專案 • 高層參與- 克服障礙
20. 品質改善的流程1. 定義產品或服務 2. 鑑定顧客及其需求 3. 列出滿足顧客需求所需之條件 4. 定義(規劃)流程 5. 防範流程錯誤並消除浪費 6. 確保持續改善
21. Six-Sigma 整合改善、設計與績效管理方法論Six-Sigma 所使用的三個主要方法論: 流程改善(DMAIC)、流程設計與再設計(DFSS)與績效管理DMAIC用以改善現有流程、產品、服務、設計等等 DFSS用以產生新的流程、產品、服務、設計等等績效管理是一個系統用以將策略連接戰術、設定優先順序、資源整合持續達成DMAIC與DFSS目標流程改善方法論流程設計與再設計方法論績效管理方法論
22. 產品變異的來源設計製程材料元件不適當的設計允差製程管制不當零件材料不穩定
23. 6 品質方案的架構Total Customer Satisfaction縮短作業週期參與式管理Empowerment標竿研究........6 Quality Program, Cp, Cpk, DpuQUALITY METRICSIMPROVEMENT PROCESSIdentify product or services Identify customer requirements Identify your needs Define the process Mistake-proof the process and eliminate wasted effort Ensure continuous improvementTOOLS FOR SIX SIGMADesign to standard parts/materials Design to standard processes Design for assembly Part standardization Supplier SPC Process standardization Statistical process control ......and more
24. 5 階段問題分析解決流程 (DMAIC)提高目標另一主題第一階段第二階段第三階段第四階段第五階段管制 (Control)改善 (Improve)分析 (Analyze)衡量 (Measure)定義 (Define)•選擇專案 •成立專案小組 •確認 CTQs Y •定義衡量指標 ($ ?) •衡量系統驗證•定義不良 •基準線 •設定目標 •確認 X•重點少數 x’s •效果測試 (Pilot Soln) Y = f(x) •確認效果持續性
25. So...What is Six Sigma? A Measurement System A Problem-Solving Approach A Disciplined Change Process“THE SIX SIGMA BREAKTHROUGH STRATEGY”MeasureAnalyzeImproveControl
26. *DefineMeasureAnalyzeImproveControlDMAICProject Selection Team Formation Identify CTQs Y Define Specs Validate Measurement System Define Defects Baseline Set Goals Identify x’sFind and Confirm vital few x’s Pilot Soln Y = f(x)Ensure Solution is Sustainable
27. Key Customer Opportunity to grow or threat of lossIs the customer telling us when the issue is?Six Sigma Project IdentifiedDefine-Scope itMeasure-How are we doingImprove-ImplementControl-Make sure it sticksProblem has quick fix?Fix it!Analyze-Root Cause Preliminary look at how we think we are doingSet up customer meetingDefine/Refine CTQ’s What’s important to them?How are we doing on these CTQ’sHow can we improve?Six Sigma Is A Growth ToolYESYESNONODMAICCustomer Improvement Continuous Growth
28. DMAICDefine Measure Analyze Improve Control Define the project goals and customer (internal and external) deliverables Measure the process to determine current performance Analyze and determine the root cause(s) of the defects Improve the process by eliminating defects Control future process performance DMADVDefine Measure Analyze Design Verify Define the project goals and customer (internal and external) deliverables Measure and determine customer needs and specifications Analyze the process options to meet the customer needs Design (detailed) the process to meet the customer needs Verify the design performance and ability to meet customer needs
29. Six-Sigma 架構 MOA (Market Opportunity Analysis)事業策略展開 Business Strategy Deployment推行組織 (Implementing Organization)跨功能團對合作 Cross-functional Teaming (Gaining Commitment)(Culture Change)(Information Tech)(Training Systems)確認關鑑業務流程 Identifying Critical Business Processes專案選擇與審查 (Project Selection & Charting)專案管理 (Project Management)DFSS Flow (Design for Six-Sigma)DMAIC Flow•意識(Awareness)•統計工具(Statistical Tools)•管理工具(Management Tools)•推廣(Promotion)6-Sigma 基礎架構市場機會分析全體承諾訊息科技文化改變訓練體系
30. 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
31. Champions or Leaders are those senior managers who will ensure that resources are available for training and projects, and who will be involved in project reviews. Champion
32. Role . Mentor and train Blackbelts and others. . Technical leader in GEMS& 6 sigma . Mentor Greenbelts when referred by Blackbelts. Responsibility Develop & deploy 6 sigma tools & processes Own 6 sigma technical development roadmap Mentor Blakbelts/Greenbelts on Methodology Ensure rigor of 6 sigma methodology Assist in selection of Blackbelts Drive project closure Focus BBs,GBs on achieving business results Commitment 100% dedicated Certification Mentor 20 successful projects Master Blackbelt
33. BlackbeltRole Lead teams implementing 6 sigma Methodology Mentor Greenbeltsand refer to MBB as required. Responsibility Lead multiple projects to successful completion Drive awareness of methodology and tools to team members and broader organization Act as both technical and cultural change agent for quality Participate in 6 sigma roadmap development Mentor Greenbelts and attend GB reviews Update GB project status color codes Commitment 100% dedicated Certification 2 successfully closed BBs projects
34. Greenbelt Role Leads or participate in teams implementing the 6 sigma methodology on projects Responsibility Learn and apply methodology to projects in current job scope Put 6 sigma on Goals & Objectives. Proactively involve BBs, MBBs as required to advance project. Work together with other GBs to achieve function’s 6 sigma goal. Present project findings in the appropriate review sessions. Commitment Significant. Varies depending on quality of project definition and scope Certification 2 successfully closed GBs projects
35. 扮演角色綠帶/黑帶(GB/BB)碩士黑帶(MBB)•負專案全責 -- 黑帶(專職)/ 綠帶(兼職) •專注於1-2專案小組 •依專案特性挑選出流程盟主 (Process Champion)•專職之職位 •協助多個專案小組 •開發導入專家資源•管理之責任 •專注於一個關鍵流程或次流程 •被BU流程改造委員會依流程性質而選出•專案小組領導技巧 •專案管理技巧 •問題分析與解決技巧•跨功能工作經驗 •分析/技巧專長 •流程之指導/監督/教育技能•負責流程功能/目標達成/維持關鍵項目之管制/主導定期流程審查 •負責跨功能介面問題與議題之解決 •跨功能認識與了解 •溝通/談判技巧 •原因分析技能 •專案小組領導技巧•負責專案進度/小組工作計劃, 並將之與管理層級聯接 •開發衡量與管制系統 (如, 資料蒐集計劃/流程管制表等) •開發BB/帶動專案小組成功/ 提供流程改善與統計技巧的專長 •亦可能被指派加入流程管理小組專長職責敘述
36. 選擇核心專案小組成員訣竅 (core team) *理想人數 : 5~7人 *訓練展開之前先選定小組成員與黑帶, 再讓這些人一起受訓 *取得各階主管支持的承諾 *流程盟主最好來自事業部流程改造委員會, 以利溝通與學習 *專案執行期間,專案小組成員花在專案的時間可至每週 20小時 -- 每週小組會議為 4 ~ 6 小時 -- 每週改善專案為 10 ~ 16 小時 *改善專案包括延伸小組成員, 包括事業部財務代表與其他重要資源
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38. Sub-Process OwnersProcess OwnerProcess TeamMBBProcess ChampionMembers BB (GB)Improvement TeamMBBProcess Management TeamsImprovement/Design ProjectsBU 6-Sigma CouncilProcess Management System & OrganizationProcessRoles & ResponsibilitiesMeasurementProcess ReviewLinking & LeveragingProcess Champion
39. 356 個 Sigma 管理 ( 6 Program) 理念: 品質是由企業文化改變出來的策略: 創新(Innovation)/突破 (Breakthrough)/組織運作 /衡量(measures) 例 :流程簡化 (Simplification) 重點: 企業文化塑造/大量資源投入改造/有效量化執行成果 (KPIs $ )
40. 基本統計分析工具常態分配(Normal Distribution) 變異數與標準差(Variance & Sigma) 特性要因圖(Cause and Effect Diagrams) 品質機能展開 (QFD) 量測系統分析(Gauge R & R) 實驗計畫(DOE) 變異數分析(ANOVA) 相關與回歸分析(Correlation & Regression) 管制圖(Control Chart) 電腦應用程式(Computer software)
41. 常態分配(Normal Distribution)
42. 標準差　　一群觀察值與平均數之差，稱為離均差，各離均差之平方的平均數（即變異數）再予開方所得即為標準差。
43. 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
44. 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
45. DefineWhat do we want to know ? -- What is our problem ? -- What is our defect ?Practical Problem Project CTQ’s Solid Y, Spec Definition, and Defect Definition Building a Justifiable Business Case Approved Charter (R0)What did we learn ………Do we have a viable project ?
46. 特性要因圖
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48. The % Variation Due to the Measurement Method GAGE R & RGAGE: The instrument used for making Measurements that we want to validate.REPEATABILITY: Does the same operator get the same results When measuring the same part several times? REPRODUCIBILITY: Do different operators get the same results when measuring the same part several times?CAUTION: A Calibration Sticker does not imply that Gage R&R is acceptable!
49. MeasureWhat do we want to know ? Statistical Problem Project Y, Spec Definition, and Defect Definition Gage R&R on Y Data Process Map L1 to Show Z Values with Link to Financials Rationalization for Focused Y Descriptive Statistics for Focused YWhat did we learn ………Mean problem ? Variance ? Both ?
50. 時間GOODBAD3 Sigma6 SigmaBreakthrough ImprovementSix-Sigma 突破表現
51. 如果我們充份瞭解與掌握 X, 為何我們要持續測試與檢驗 Y?Y 相依 (Dependent) 輸出 (Output) 結果 (Effect) 不良結果 (Symptom) 監測 (Monitor)X1 . . . Xn 互相獨立 (Independent) 輸入 (Input-Process) 原因 (Cause) 問題 (Problem) 控制 (Control) 為了獲得好的結果, 我們是否要專注於 Y 或 X 的行為 ?f (X)Y=專注於 X 而非 YSix Sigma焦點
52. CTQ’s(成本, 品質, 交期, 顧客滿意度) 每單位缺點數複雜度 DPPM Rolled Thruput Yield Six-Sigma 分數流程底限 (Baseline) 流程標竿 (Benchmarking) KPOV’s KPIV’s 偏移與漂移 (Shift & Drift)Six-Sigma衡量指標現有衡量指標良率 RMA數量返修數量顧客抱怨數???? Leadership Must Ask the Right Questions What Gets Measured Gets ManagedSix-Sigma 衡量指標 (Metrics)
53. Six-Sigma 衡量指標 - 定義CTQ’s: 重要顧客滿意參數. 通常包括品質,成本,交期等. KPOV’s: 關鍵流程輸出變數 (Key Process Output Variables). 流程中由 KPIV’s反應矯正措施之結果 KPIV’s: 關鍵流程輸入變數 (Key Process Input Variables). 直接與其他KPIV’s相關, 影響改變流程輸出之變數
54. 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 =
55. Some Basic 6-Related ToolsScatter Diagram Over Slept Car Would Not StartWeather Family ProblemsOtherPareto Diagram Frequency of OccurrenceReasons for Being Late for WorkArrival Time at WorkTime Alarm Went Off
56. AnalyzeWhat do we want to know ? Statistical Problem Understood Link Process Map to Fishbone w/C, N, X Labeling Ensure Data is Collected for All Xs Drill Down to Vital Few Xs via ANOVA, GLM, T-test, F-test List of Vital Few X’s Quantified Financial OpportunitiesWhat did we learn ……… What were the causal Xs ? How did we identify them ?
57. PM/CE/CNX/SOPProcess MappingWhy?* Process visual foundation for current situation and analysis Aids in identifying bottlenecks, redundancies and waste Look for Non Value Add Look for Variables (CNX)How? Determine beginning and end of process to be mapped Involve people knowledgeable about the process Brainstorm steps & group in major process areas Layout activities in sequence Validate by physically walking through process
58. PM/CE/CNX/SOPCE: Cause & Effect Sources of VariationOutput(s) & Specs People Material MachineX CC NCNXX Measurement Method EnvironmentEvery variable on the diagram should be labeled as either: C = Constant N = Noise X = Experimental variable or Factor
59. PM/CE/CNX/SOPSOP: Standard Operating ProceduresStandard Operating Procedure are rules that we define to ensure that we have Consistent processes in everything we do. Based on good judgment Common sense Engineering knowledge Remember ISO 9000! Make sure we have defined processes and that the rules are being obeyed by all.
60. 數據分析1.Sample size risk Is the risk of say there is a difference when there really isn’t one(生產者冒險率) Is the risk of not finding a difference when there really is one (消費者冒險率) / is he magnitude or size of the difference been tested. This is sometimes called the test sensitivity.
61. A Basic Sample Size TableApplies to Continuous Data Onlyδ/σ
62. For example : The 1st adhesive has an average of 13.2 and a standard deviation of 3.27 The practical significance is such that any alternative Adhesive must have an average strength of 20 or more to make the change worth while. Q: For α=5% & β=10% what should be the sample size in each level of the experiment?Ans: How big of a change is important? δ/σ=(20-13.2)/3.27= 2.07 α=5% β=10% So follow the table we find the sample size is 5
63. 2.T-test : Comparing Means 3.F-test : Comparing Variances (Between 2 Groups) 4.ANOVA :(Analysis Of Variance) (Between multi-groups)
64. ImproveStatistical Control Poka-Yoke Plan (if Applicable) Confirmed Vital X’s ……Are They Statistically Significant ? Sample Size Calculation For Confirmation Run DOE Plan (if Applicable) Regression Equation Linked to statistical Problem SOP Changes and/or Optimal Solution Identified Plan to Implement SOP Changes and/or Optimal SolutionWhat contribution did each vital X have to the Y ? How can we control the Xs ?What do we want to know ?
65. How do we determine a modelCorrelation & RegressionCorrelation tells if you have a relationship between two variables(Y and X, or two Xs) Regression is used to identify the nature of the relationship, and be able to predict Y while better understanding Y and possibly improving the controllability of Y
66. CorrelationCorrelations (Pearson) Correlation of pull and temp = -0.978
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68. Regression Analysis (Minitab software) The regression equation is pull = 353 - 2.30 temp Predictor Coef StDev T P Constant 353.11 13.56 26.05 0.000 temp -2.29520 0.09001 -25.50 0.000 S = 0.3460 R-Sq = 95.6% R-Sq(adj) = 95.4% Analysis of Variance Source DF SS MS F P Regression 1 77.832 77.832 650.28 0.000 Error 30 3.591 0.120 Total 31 81.423 Unusual Observations Obs temp pull Fit StDev Fit Residual St Resid 12 150 9.3122 9.9752 0.1181 -0.6630 -2.04R 31 151 4.9778 5.8438 0.0864 -0.8660 -2.59R
69. DOE (Design of experiment)1.篩選主要因子 2.尋找最佳因子組合 3.結果再現性驗證找尋最佳之生產條件(製程參數 )
70. 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
71. ControlWhat do we want to know ? Statistical Control Poka-Yoke Plan (if Applicable) Measurement of Final Capability Using Confirmation Run Comparison of Before and After Distributions How Do You Control or Poka-Yoke the Vital Xs ? Is the Learning Transferrable Across the Business ……What’s the Plan ? Who Owns the Project Documentation File ? Final Financial Results Signed Off What Spin Off Projects Are There ?How will this change the way we work ?
72. Mistake proofing FMEA Process Monitor(SPC, Control chart…) Risk vs. Benefit Control tools
73. 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
74. 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
75. 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
76. Risk vs. Benefit BenefitLowHighLowMedHighRisk122Perform Confirmation Runs33Just do it 2. Probably stop 3. “Hire a consultant unless you have high confidence and experience”
77. 2 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”
78. 突破策略ABCDEFG1選擇輸出特性2定義輸入積效指標3定義有效衡量系統4建立產品能力5定義達成績效目標6定義變異來源7篩選潛在因素8發掘變因關係9建立管制公差10建立有效衡量系統11決定流程能力12導入流程管制改善專案突破要項流程認知定義衡量分析改善控制產品能力分析流程能力分析專注於Y專注於X目標 = Y = f (X1,X2,….,Xn)
79. DMAIC Black Belts 展開改善方法定義Define衡量Measure分析Analyze改善Improve管制Control1.建立專案審查小組 2. 確認支持者/小組成員/各類所需資源 3. 實施先期作業4. 確認專案小組目標 5. 定義現狀 6. 收集與展現資料 7. 決定流程/製程能力 8. 確認變異來源 9. 確認問題10. 產生改善構想 11. 決策評估 12. 進行實驗 13. 矯正計劃 14. 實施 15. 效果確認16. 管制計劃展開 17. 持續監控成孝 18. 標準化 / 防呆專案審查工具Project ID Tools 專案定義表格專案管理流程 SSPI 工具箱 SSPI工具箱 Process Mapping 價值分析腦力激盪優缺點列舉法多數表決法柏拉圖魚骨圖 QFD FMEA 查檢表 Run Charts 管制圖 Gage R&RCp & Cpk 研究多變量統計分析 Box Plots Marginal Plots 假設檢定實驗設計法交互作用分析迴歸分析變異數分析 (ANOVA) KJ 法魚骨圖 FMEA 腦力激盪 Best Practices Benchmarking 實驗設計法/田口方法假設檢定 Process Mapping 樹狀圖(Tree Diagrams) 計劃評核術(PERT) PDPC / FMEA 甘特圖查檢表 Run Charts 直方圖散佈圖管制圖柏拉圖內部稽核審查會 Poka-Yoke
80. 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
81. 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
82. TargetUSLLSLTargetUSLLSLTargetUSLLSLCenter ProcessReduce SpreadOff-TargetUnpredictableOn-TargetDefectsProblem Solving Approach“Lower Specification Limit” “Upper Specification Limit”Less Variation Means Fewer Defects & Higher Process Yields
83. 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
84. Why 6-Sigma so successful ? *It’s seeking “breakthrough” rather than “improvement”. * Top management involvement (Champion) * Focus on cross-functional critical business processes * Full-time manpower dedication * Quantitative data oriented -- $ (data stratification and confirmation) *A lot of training (especially statistical training) * P-D-C-A
85. 第 9 章：推行6-Sigma成功關鍵因素 * 尋求 “突破” 而非 “改善” * 高階主管積極參與 (Campaign) * 著眼於跨部門/功能重要事業流程 * 全職 (Full-time) 人力專注活動推動 * 量化指標導向$ (data stratification and confirmation) * 許多訓練課程 (尤其是統計課程) * 非常注重 Check 與 Act (P-D-C-A) 123
86. 6 Sigma is Process Knowledge6 sigmaScience = Process knowledge = 6 sigma quality = Success Art & Magic =Confusion =Fire Fighting =Waste We’ve All Seen the Results: Teams &/or Individuals *Flounder *Panic *Fail *Cover-upMore process knowledge will improve our competitiveness
87. A Practical Example (The “Cookbook”)6 Overview
88. 6.....and Baking BreadYEAST FLOURUsing a 12 Step ProcessThe “BETTER BREAD” Company
89. Step 1.....Selecting “Critical to Quality” (CTQs or Y)What is Important to the Customer? Rise Texture Smell Freshness TasteY = Taste!!Measure
90. Step 2.....Defining Performance Standards for CTQs or YHow 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
91. 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
92. 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
93. 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
94. 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
95. 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
96. 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
97. 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
98. 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
99. 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
100. 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
101. 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

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