6sigma绿带介绍(ppt94)-精益生产(编辑修改稿)

6sigma绿带介绍(ppt94)-精益生产(编辑修改稿)内容摘要：

Welch (GE’S CEO)畫三個圓圈：核心、高科技與服務。 GE公司未來都要在其中一個圓圈內。 公司任何人不再任一個圓圈內者，未來將會被解雇。 圓圈外的的事業將被整頓、關閉或出售。 三個圓圈的策略讓 GE公司找到焦點，不再是集團 (似乎什麼都做 )。 • Define Steps (3) Select Target Product/Service Analysis Business Process Analysis Core Process Identify Customer Listen to VOC Specify Customer Requirement Select CTQ (Big Y) Specify CTQ (Small Y) Evaluate Potential Projects Select Project amp。 Build Effective Team • Define Steps (4) • CTQ Critical to Quality • 只要是顧客要求的 ， 就是關鍵品質(CTQ)。 亦稱為 『 重要成果 』 、 『 特殊限制 』 或流程的 『 Y變數 』。 CTQ係任何會直接影響顧客對產品 /服務品質觀感之因素。 顧客 『 在乎 』 的事 ， 就是企業或組織在乎的事。 『 新點子 』 要採納『 外部觀點 』 (Outsidein Perspective)，即從顧客的眼光來看企業或組織的一切。 . DMAIC Methodology 5 Stages DMAIC Methodology and Statistical Tools • Phase: Measure • Steps。 Work Breakdown amp。 Tool • M1 Specify Project。 • CTQ Tree, Process Map, Performance Index • M2 Assess Measurement System。 • Measurement System Analysis, Gage Ramp。 R • M3 Identify Sigma Level。 • Graph Analysis, Capability Analysis, Confidence Interval • M1 Specify Project • M1 step covers the followings: ◎ CTQ Breakdown ◎ Define Scope ◎ Process Mapping ◎ Pareto Analysis ◎ Define performance index and specifications The success of any 6 activities relies mostly on the CTQ definition and selection • Define Performance Index Customer Requirements Internal Process Improved Process Customer Satisfaction Index of current level Index of improved level Perform project for improvement Clear Quantifiable Simple • Example of Performance Index ◎ Yield ◎ Cycle time ◎ Defect rate ◎ Machine failure rate ◎ Customer standby hours ◎ Number of invoice errors ◎ Elapse Time from loan application to money transfer to the customer account ◎ Hours taken from receiving order to delivery to the customer M2 Measurement System Analysis • M2 step covers the followings: ◎ Statistic fundamentals ◎ Sampling plan ◎ Data collection plan ◎ Variation of measurement system ◎ Gage Ramp。 R study ◎ Improvement of measurement system Without accurate measure, can’t identify any symptom of problem • 6  Metrics Data Type Statistic measurement data Comparison to specification Zvalue Discrete Data Continuous Data Defect unit opportunity (DPMO) Average, Standard variation, Shape SPEC Zvalue Sigma calculation • Definition of DPMO terminology • DPU: Defect per Unit • (Defect: Anything that results in customer dissatisfaction。 • Anything that results in nonconformance) • DPO: Defect per Opportunity • DPMO: Defect per Million Opportunities • Example of Sigma calculation: Discrete Data • Case (1): Over the last several years, you have collected data on trips to the airport. Of the 100 trips sampled, you have missed only 5 flights. If you indicate this situation as Sigma level, what will it be? • Sol. DPU = DPO =5/100 = • = , Z = •  level = Z + = + = Case (2). An accounting term conducted an internal audit for the financial report of year 2020 and they observed 25 nonconforming record. There were 2 steps of probable incorrect entry identified in the process and the total observation was 25,000 records. What is DPO? What is DPMO? What is Sigma level of financial reporting process? • Sol. DPU = 25/25000, DPO = 25/(2*25000) =, DPMO = *10^6 =2020 • 1 = , Z = •  level = Z + = + = • Example of Sigma calculation: • Continuous Data(1) 1  Mean Median Mode 70 80 90 100 110 120 130 +   Normal Distribution with mean = 100 and std. = 10 • Continuous Data(2) (1) Mathematical Model； (2) Continuous； (3) Smooth；(4) Symmetrical。 (5)Tail asymptotic to Xaxis； (6) Bell shaped； (7) Mean = Median = Mode (8) Total area under curve = 1 (1) The normal distribution has the following properties. ◎ % of the data fall within 1 ◎ % of the data fall within 2 ◎ % of the data fall within 3 (2) In order to assess the quality of the process, we must pare the process characteristics (via the location, spread and shape) to the specification limits and targeted value. • Continuous Data(3) • Standardization of Normal Distribution • The Sigma of a Process is the number of standard deviation between the mean and the Specification Limits. 1  Z = (X)/ No. of standard deviation USL Sigma of the process Z = • Measurement System and Measurement Error(1) • Measurement system is viewing as a pro。