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Evaluating & Monitoring Your Process Using MSA & SPC
 

Evaluating & Monitoring Your Process Using MSA & SPC

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An overview of the basic principles of system evaluation, measurement system analysis, Gauge R&R, process monitoring and the methods for evaluating the measurement process popularized by Donald J. ...

An overview of the basic principles of system evaluation, measurement system analysis, Gauge R&R, process monitoring and the methods for evaluating the measurement process popularized by Donald J. Wheeler. These slides accompanied Peter Bartell’s JMP webcast on Evaluating & Monitoring Your Process Using MSA & SPC. Watch the webcasts at http://www.jmp.com/mastering

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    Evaluating & Monitoring Your Process Using MSA & SPC Evaluating & Monitoring Your Process Using MSA & SPC Presentation Transcript

    • Copyri ght © 2014, SAS Institute Inc. Al l ri ghts reserved. EVALUATING & MONITORING YOUR PROCESS USING MSA AND SPC Peter Bartell JMP Systems Engineer peter.bartell@jmp.com
    • Copyri ght © 2014, SAS Institute Inc. Al l ri ghts reserved. OBJECTIVES • At the end of this presentation you will be able to • List the key components of a sound and effective measurement system evaluation process • Using JMP, list the key steps for Gauge Repeatability and Reproducibility studies. • Using JMP, list the key steps for performing measurement system evaluation using select methods articulated by Don Wheeler in “EMP III – Using Imperfect Data” (2006). • List the key components of a sound and effective process monitoring approach • Using JMP, list the key steps for creating and analyzing select Shewhart, Rare Event, and multivariate control charts.
    • Copyri ght © 2014, SAS Institute Inc. Al l ri ghts reserved. BASIC MEASUREMENT SYSTEM EVALUATION PRINCIPLES • The three principles of Statistical Thinking • All work is a process. • All processes are variable. • Use data to make decisions and guide actions. • “Measure something once, you know what you’ve got. Measure it again…you’ve got no clue.” Which process do you want?
    • Copyri ght © 2014, SAS Institute Inc. Al l ri ghts reserved. BASIC MEASUREMENT SYSTEM EVALUATION PRINCIPLES Start Define Process Monitor Process Stable ? Identify, Remove Causes Estimate Bias, Precision Adequate ? Establish Control Charts Stop Improve ProcessNo Yes Yes No My focus today…
    • Copyri ght © 2014, SAS Institute Inc. Al l ri ghts reserved. AN EXAMPLE OF GAUGE R & R • Essentially a designed experiment coupled with appropriate analysis. • Continuous and attribute responses. • Focuses on repeatability and reproducibility of the system. • Fixed, random effects, nesting vs. crossed designs, all considerations. • Measuring multiple items, by multiple operators, across instruments, sites, etc. Cindy Tom GeorgeOperator (i) Part (j) 1….10 Measurement (k) y111… y3,10,3 Example: Using 2 Factors Crossed.jmp
    • Copyri ght © 2014, SAS Institute Inc. Al l ri ghts reserved. AN EXAMPLE OF THE “EMP” METHOD • Described by Don Wheeler in “EMP III – Using Imperfect Data” (2006) • A novel use of xbar and R charts and other graphical approaches. A B COperator (i) Part (j) 1….5 y111… y3,5,2 Example: Using gasket.jmp Measurement (k)
    • Copyri ght © 2014, SAS Institute Inc. Al l ri ghts reserved. PROCESS MONITORING • “Is the process behaving in a way that suggests there are no assignable causes of variation occurring?” • “If assignable causes rear their heads or occur, how will I know?” AND • “How can I balance the risk of making either of these two mistakes?” • Going to look for assignable causes when they aren’t present. • Failing to look for assignable causes when they are present. • As Dr. Deming often asked, “By what method?”
    • Copyri ght © 2014, SAS Institute Inc. Al l ri ghts reserved. PROCESS MONITORING APPROACH • Phase I • Process stabilization, characterizing common cause variability. • Phase II • Process monitoring, ongoing characterizationto identify assignable cause variability in a timely fashion, with acceptable risk.
    • Copyri ght © 2014, SAS Institute Inc. Al l ri ghts reserved. STATISTICAL PROCESS CONTROL CHARTS • Shewhart variables and attribute. • AnnualSnowfall.jmp, (Individuals, Moving Range charts), • SocketThickness.jmp (xbar, r charts), BottleTops.jmp (np chart) • Rare event. • FanBurnout.jmp (t chart) • Multivariate charts (Hotelling’s T2) • ThicknessPhaseI.jmp • ThicknessPhaseII.jmp • ThicknessTargets.jmp • Via either the Control Chart Builder or Analyze -> Quality and Process -> Control Chart path.