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Measurement and Analysis Interaction A1

12/2/2003. Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook). 2. Output of Measurement Selection (A1). Project Y variable(s) (CTQ) identified and linked to problem/goalAt least one X variable (predictor) to help find cause of Y variable Start with stratification factor as initial type of X variablePlan for making sure you know:Where to collect measurementsData is availableIt is feasible (time, money, personnel) to collect dataExercise: CTQ TreeExercise: Measurement 29

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Measurement and Analysis Interaction A1

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    1. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 1 Measurement and Analysis Interaction (A1)

    2. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 2 Output of Measurement Selection (A1) Project Y variable(s) (CTQ) identified and linked to problem/goal At least one X variable (predictor) to help find cause of Y variable Start with stratification factor as initial type of X variable Plan for making sure you know: Where to collect measurements Data is available It is feasible (time, money, personnel) to collect data Exercise: CTQ Tree Exercise: Measurement Assessment Tree

    3. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 3 Output of Operational Definition (A2) Clear, concise, detailed, unambiguous description of what is being measured Definitions of key terms like defect, product and service Guidelines on how to interpret the routine and the unusual Initial data collection plan for what (sets up the when and how) Use Operational Definition Worksheet (pg. 169)

    4. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 4 Output of Identifying Data Sources (A3) Identification of existing data sources that will meet some (or all) measurement needs. Criteria for acceptable existing data include: Used the same operational definitions developed for the project collection efforts (especially in agreeing with customer definitions) Structured to support analysis stage (i.e. has required stratification factors) Identification of new data sources to needed to meet requirements Validating of ability to access and sort existing data

    5. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 5 Prepare Data Collection and Sampling Plan (A4) Identify/confirm stratification factors Must begin with some idea of the “end game” Data exploration (analysis stage) lives or dies on decisions made here Develop sampling scheme Create data collection forms

    6. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 6 Developing the Sampling Scheme (A4.2) Choice – Population or Process sampling? Population sampling: Large (essentially infinite), homogeneous pool of data Process sampling: Sample taken from a “running process stream” Ref: Tables 9-1 and 10-2 and Figures 10-6 to 10-10 Accounting for “sampling bias” Bad sampling processes: convenience sampling and judgment sampling Good sampling processes: systematic sampling, random sampling, stratified sampling Setting the Confidence Interval (CI) (Detailed discussion at end of Measure Stage of DMAIC model) Typical interval is set at 95% (this is Minitab default) Must know something about process to ballpark the sample size for a 95% CI Exercise: Manual Sample size calculation (pg. 171-172)

    7. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 7 Creating Data Collection Forms (A4.3) Avoiding pitfalls: KISS Good labeling Space for identifying data: date, time, collector Have consistent structure Include key STRATIFICATION FACTORS Types of collection forms: Check sheets Data sheets Travelers: Excellent method to “pair data” when stratification factor and Y-variable measurement don’t occur at same place and/or time

    8. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 8 Output of Data Collection and Sampling Plan (A4) A list of stratification factors Completed sampling plan Data collection forms

    9. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 9 Output of Implement/Refine Measurement Process (A5) Review/finalize collection plan Perform Measurement System Analysis including Gage R&R, bias assessment, stability and linearity testing, and calibration Prepare workplace: Let all know what’s going on Tested collection procedures: KISS and trial run Validate collector training Collect data Monitor measurement accuracy and refine Exercise: Gage R&R Assessment (continuous and discrete)

    10. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 10 Minitab Gage R&R Example

    11. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 11 Minitab Gage R&R Session Window

    12. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 12 Calculate Baseline Sigma Levels (B1) Key definitions Unit: Item being processed (focus of the project) Defect: Failure to meet customer expectation Defect Opportunity: Chance for product/service to be defective Guidelines for “defect opportunity” definition Focus on “defects that are important to the customer” Should reflect “number of places in the process where it can go wrong, NOT all the ways it can go wrong” Focus on routine defects – i.e. don’t count the “rare event” Group similar defects in a single “defect category” Be consistent (within defect and across company) Don’t change operation definition without compelling reason Simple 4-step process Exercise: Sigma Calculation Worksheet (pg. 178-179)

    13. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 13 Calculate Final and First-Pass Yield (B2) Looks at the internal structure of the process Two different ways of looking at yield and process sigma: final yield and first-pass yield Final yield: How many defect-free items emerge at the end of the process including those that were successfully reworked Internal defects and their costs are hidden First-pass yield: Number of items that make it through entire process without any rework included Same as Rolled Throughput Yield (RTY)

    14. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 14 Measuring the Cost of Poor Quality (B3) Cost is connected to, but not the same as defect counts or sigma levels Translate defect data into Cost of Poor Quality (COPQ)

    15. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 15 Output of Calculating the Performance Baseline Well defined units, defects and defect opportunity Calculated baseline sigma level Calculated final and/or first-pass yield for Y variable Identified labor and material rework costs Translated defects into dollars

    16. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 16 Long-Term vs. Short-Term Variation Short-term variation is less than long-term Process shift adjustment of 1.5 sigma Short-term capability: The best possible if process is centered Long-term capability: Sustained reproducibility of the process The Z calculation and the Z table

    17. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 17 Histogram and the Normal Distribution

    18. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 18 The “Z” Table

    19. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 19 “Z” Table Examples

    20. 12/2/2003 Six Sigma Green Belt (Ref: The Six Sigma Way Team Fieldbook) 20 “Z” Table Exercise

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