©2/2001 cayman systems revision m (513) 777-3394 -- 16949.com slide 1, printed 9/12/2015...
TRANSCRIPT
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 1, Printed 04/21/23Measurement Systems Analysis
Measurement Systems Analysis
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 2, Printed 04/21/23Measurement Systems Analysis
Don’t Let This Happen To YOU!
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 3, Printed 04/21/23Measurement Systems Analysis
VariationThink of Measurement
as a Process
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 4, Printed 04/21/23Measurement Systems Analysis
Definition
Measurement
The assignment of numbers to material things to represent the relationships among them with respect to particular properties.
C. Eisenhart (1963)
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 5, Printed 04/21/23Measurement Systems Analysis
Measurement Systems Analysis
• Basic Concepts of Measurement Systems
A Process
• Statistics and the Analysis of Measurement Systems
• Conducting a Measurement Systems Analysis
• ISO - TC 69 is the Statistics Group
• Ensures high ‘Data Quality’ (Think of Bias)
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 6, Printed 04/21/23Measurement Systems Analysis
Course Focus & FlowMeasurement as a Process
• Mechanical Aspects (vs Destructive)
Piece part
Continuous (fabric)
• Features of a Measurement System
• Methods of Analysis
• Gauge R&R Studies
• Special Gauging SituationsGo/No-Go
Destructive Tests
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 7, Printed 04/21/23Measurement Systems Analysis
Place Timeline Here
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 8, Printed 04/21/23Measurement Systems Analysis
The Target & Goal
Prototype
Pre-Launch
Production
USLLSL
Continuous Improvement
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 9, Printed 04/21/23Measurement Systems Analysis
Key Words
• DiscriminationAbility to tell things apart
• Bias [per AIAG] (Accuracy)
• Repeatability [per AIAG] (Precision)
• Reproducibility
• Linearity
• Stability
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 10, Printed 04/21/23Measurement Systems Analysis
Terminology
• Error ≠ Mistake
• Error ≠ Uncertainty
• Percentage Error ≠ Percentage Uncertainty
• Accuracy ≠ Precision
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 11, Printed 04/21/23Measurement Systems Analysis
Measurement Uncertainty
• Different conventions are used to report measurement uncertainty.
• What does ±5 mean in m = 75 ±5? Estimated Standard Deviation: Estimated Standard Error: m = /√N
Expanded Uncertainty of ± 2 or 3Sometimes ± 1 (Why?)
95% or 99% Confidence Interval
Standard Uncertainty: u
Combined Standard Uncertainty: uc
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 12, Printed 04/21/23Measurement Systems Analysis
Measurement Uncertainty
• Typical Reports
• Physici
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 13, Printed 04/21/23Measurement Systems Analysis
Measurement as a Process
Basic Concepts
• Components of the Measurement System
• Requirements of a Measurement System
• Factors Affecting a Measurement System
• Characteristics of a Measurement SystemFeatures (Qualities) of a Measurement Number
• Units (Scale)
• Accuracy
• Precision (Consistency or Repeatability)
• Resolution (Reproducibility)
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 14, Printed 04/21/23Measurement Systems Analysis
Measurement Related Systems
Typical Experiences with
Measurement Systems
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 15, Printed 04/21/23Measurement Systems Analysis
Basic Concepts
• Every Process Produces a “Product”
• Every Product Possesses Qualities (Features)
• Every Quality Feature Can Be Measured
• Total Variation= Product Variation + Measurement Variation
• Some Variation Inherent in System Design
• Some Variation is Due to a Faulty Performance of the System(s)
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 16, Printed 04/21/23Measurement Systems Analysis
The Measurement Process
What is the ‘Product’ of the Measurement Process?
What are the Features or Qualities of this Product?
How Can We Measure Those Features?
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 17, Printed 04/21/23Measurement Systems Analysis
Measurement Systems Components• Material to be Inspected
Piece
Continuous
• Characteristic to be Measured
• Collecting and Preparing Specimens
• Type and Scale of Measurement
• Instrument or Test Set
• Inspector or TechnicianAIAG calls these ‘Appraiser’
• Conditions of Use
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 18, Printed 04/21/23Measurement Systems Analysis
Where Does It Start?
During the Design (APQP) Stage:
The engineer responsible for determining inspections and tests, and for specifying appropriate equipment should be well versed in measurement systems. The Calibration folks should be part of the process as a part of a cross-functional team.
Variability chosen instrument must be small when compared with:
Process Variability
Specification Limits
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 19, Printed 04/21/23Measurement Systems Analysis
Typical Progression
Determine ‘Critical’ Characteristic
Determine What Equipment is Already
Available
Determine Required Resolution
Consideration of the Entire Measurement System for
the Characteristic(Variables)
Cross-Functional
Product Engineer
Product Engineer
Metrology
How will the data be used?
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 20, Printed 04/21/23Measurement Systems Analysis
Measurement Systems Variables
Measurement
Instrument Environment
Material Inspector Methods
Sample Preparation
Sample Collection
Parallax
Reproducibility
Training
Practice
Ergonomics
Test Method
Workmanship
Samples
Standards
Discrimination
Repeatability
Bias
Calibration
Linearity
Vibration
Lighting
Temperature
Humidity
These are some of the variables in a measurement system. What others can you think of?
FixtureEyesightAir PressureAir MovementFatigue
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 21, Printed 04/21/23Measurement Systems Analysis
Determining What To Measure
• Voice of the CustomerYou Must Convert to Technical Features
• Technical Features
• Failure Modes Analysis
• Control Plan
Convert To
External Requirements
Internal Requirements
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 22, Printed 04/21/23Measurement Systems Analysis
Voice of the Customer
• External and Internal Customers
• Stated vs Real and Perceived Needs
• Cultural Needs
• Unintended Uses
• Functional Needs vs. Technical Features
Customer may
specify causes
rather than output
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 23, Printed 04/21/23Measurement Systems Analysis
Convert to Technical Features• Agreed upon
Measure(s)
• Related to Functional Needs
• Understandable
• Uniform Interpretation
• Broad Application
• Economical
• Compatible
• Basis for Decisions
Y
ZTechnical Feature
Functional Need
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 24, Printed 04/21/23Measurement Systems Analysis
Failure Modes Analysis
• Design FMEA
• Process FMEA
• Identify Key Features
• Identify Control Needs
Critical Features are Defined Here!
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 25, Printed 04/21/23Measurement Systems Analysis
Automotive FMEAProcess Failure Mode And Effects Analysis Low - High
Process: Outside Suppliers Affected: Engineer: 1 - 10
Primary Process Responsibility: Model Year/Vehicle(s): Part Number:
Other Div. Or People Involved: Scheduled Production Released: PFMEA Date: Rev.
Approvals: Quality Assurance Manager Quality Assurance Engineer
Operations Manager Senior Advisor
Part Name Operation Number Process Function
Potential Failure Mode
Potential Effects Of Failure Potential Cause Of Failure Current Controls OccuredSeverityDetectionRPN
Recommended Actions And
StatusActions Taken OccuredSeverityDetectionRPN
Responsible Activity
SIR Take TPPE Wrong MaterialFragmented Container Insufficient Supplier Control Material Certification 1 9 2 18
Container Material Held In Unpredictable Deployment Improper Handling Required With Each
1 Storage Area Misidentified Material Shipment
Release Verification
Out Of Spec Fragmented Container Supplier Process Control Periodic Audit Of 3 10 3 90
Material Unpredictable Deployment Supplier Material
Contaminated Fragmented Container Open Boxes Visual Inspection 1 9 7 63
Material Unpredictable Deployment
Material Fragmented Container Engineering Change Release Verification 1 10 7 70
Composition Unpredictable Deployment Supplier Change Green "OK" Tag
Change Customer Notification
2 Move To Unreleased Fragmentation Untrained LTO Check For Green "OK" 5 10 1 50
Approved Untrained Personnel Tag At Press
Storage Trace Card
Check List
Training
Leading to MSA. Critical features are determined by the FMEA (RPN indicators) and put into the Control Plan.
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 26, Printed 04/21/23Measurement Systems Analysis
Control Plan / Flow Diagram• Inspection Points
• Inspection Frequency
• Instrument
• Measurement Scale
• Sample Preparation
• Inspection/Test Method
• Inspector (who?)
• Method of Analysis
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 27, Printed 04/21/23Measurement Systems Analysis
GM Process Flow ChartProcess Flow Diagram Approved By:
Part Number: Date: 4/5/93 QA Manager
Part Description: Rev. : C Operations Manager
Prepared By: Senior AdvisorQA Engineer
Step FabricationMoveStoreInspectOperation Description Item # Key Product Characteristic Item # Key Control Characteristic
1 Move "OK" Vinyl Material 1.0 Material Specs 1.0 Material Certification TagFrom Storage Area andLoad Into Press.
2 Auto Injection Mold Cover 2.0 Tearstrip In Cover 2.1 Tool SetupIn Tool # 2.2 Machine Setup
3.0 Hole Diameter In Cover 2.1 Tool Setup2.2 Machine Setup
4.0 Flange Thickness In Cover 2.1 Tool Setup2.2 Machine Setup
5.0 Pressure Control Protrusions 2.1 Tool SetupHeight 2.2 Machine Setup
3 Visually Inspect Cover 6.0 Pressure Control Protrusions 2.1 Tool SetupFilled Out 2.2 Machine Setup
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 28, Printed 04/21/23Measurement Systems Analysis
Standard Control Plan Example
Control Plan Number Key Contact / Phone Date (Orig.) Date (Rev.)
Part No./ Latest Change No. Core Team Customer Engineering Approval/Date
Part Name/Description Supplier/Plant Apoproval/Date Customer Quality Approval/Date
Supplier/Plant Supplier Code Other Approval/date (If Req'd) Other Approval/date (If Req'd)
Characteristics Methods
Part/ Process Number
Process Name/ Operation
Description
Machine, Device,
Jig, Tools for Mfg. No. Product Process
Special Char. Class
Product/ Process Spec/
Tolerance
Evaluation Measurement
Technique SizeFrequ- ency
Control Method
Reaction Plan
This form is on course disk
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 29, Printed 04/21/23Measurement Systems Analysis
Ford’s Dimensional Control Plan (DCP)
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 30, Printed 04/21/23Measurement Systems Analysis
Measurement as a System• Choosing the Right Instrument
Instrument Calibration Needs
Standards or Masters Needed
Accuracy and Precision
• Measurement PracticesWhere
How Many Places
• Reported FiguresSignificant Figures Rule
2 Action Figures
Rule of 10
Individuals, Averages, High-Lows
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 31, Printed 04/21/23Measurement Systems Analysis
Measurement Error
Measured Value (y) =
True Value (x) + Measurement Error
Deming says there is no such thing as a
‘True’ Value.
Consistent (linear)?
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 32, Printed 04/21/23Measurement Systems Analysis
Sources of Measurement Error• Sensitivity (Threshold)
Chemical Indicators
• Discrimination
• Precision (Repeatability)
• Accuracy (Bias)
• Damage
• Differences in use by Inspector (Reproducibility)Training Issues
• Differences Among Instruments and Fixtures
• Differences Among Methods of Use
• Differences Due to Environment
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 33, Printed 04/21/23Measurement Systems Analysis
Types of Measurement Scales
• VariablesCan be measured on a continuous scale
Defined, standard Units of Measurement
• AttributesNo scale
Derived ‘Unit of Measurement’Can be observed or counted
Either present or not
Needs large sample size because of low information content
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 34, Printed 04/21/23Measurement Systems Analysis
How We Get Data• Inspection
• Measurement
• Test
Includes Sensory (e.g..: Beer)
Magnitude of Quality
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 35, Printed 04/21/23Measurement Systems Analysis
Operational Definitions
• Is the container Round?
• Is your software Accurate?
• Is the computer screen Clean?
• Is the truck On Time?
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 36, Printed 04/21/23Measurement Systems Analysis
Different Method = Different Results
In SpecOut of Spec
Method 1Method 2
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 37, Printed 04/21/23Measurement Systems Analysis
Measurement System Variability
• Small with respect to Process Variation
• Small with respect to Specified Requirements
• Must be in Statistical Control
Measurement IS a Process!
Free of Assignable Causes of variation
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 38, Printed 04/21/23Measurement Systems Analysis
Studying the Measurement System
• Environmental Factors
• Human Factors
• System Features
• Measurement Studies
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 39, Printed 04/21/23Measurement Systems Analysis
Standards
• NationalIn the US - Kept or Tracked by NIST
• PrimaryCopied directly from National Standard using ‘State-of-the-Art’ Equipment
• SecondaryTransferred from Primary Standard
• WorkingUsed to calibrate laboratory and shop instruments
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 40, Printed 04/21/23Measurement Systems Analysis
Environmental Factors• Temperature
• Humidity
• Vibration
• Lighting
• Corrosion
• Wear
• ContaminantsOil & Grease
Aerosols
Where is the study performed?1. Lab?2. Where used?3. Both?
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 41, Printed 04/21/23Measurement Systems Analysis
Human Factors• Training
• Skills
• Fatigue
• Boredom
• Eyesight
• Comfort
• Complexity of Part
• Speed of Inspection (parts per hour)
• Misunderstood Instructions
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 42, Printed 04/21/23Measurement Systems Analysis
• Sources of ErrorsInadvertent Errors
• Attentiveness
• Random• Good Mistake-Proofing Target
Technique Errors• Consistent
Wilful Errors (Bad mood)
• Error Types (Can be machine or human)
Type I - Alpha Errors [ risk]
Type II - Beta Errors [ risk]
Human Measurement Errors
Accept
Reject
Good Bad
OK!
OK!alpha
betaTraining
Issue
Process in control, but needs
adjustment, False alarm
Unaware of problem
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 43, Printed 04/21/23Measurement Systems Analysis
Measurement System Features
• DiscriminationAbility to tell things apart
• Bias [per AIAG] (Accuracy)
• Repeatability [per AIAG] (Precision)
• Reproducibility
• Linearity
• Stability
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 44, Printed 04/21/23Measurement Systems Analysis
Discrimination• Readable Increments of Scale
• If Unit of Measure is too course: Process variation will be lost in Rounding Off
• The “Rule of Ten”: Ten possible values between limits is ideal
Five Possible Values: Marginally useful
Four or Less: Inadequate Discrimination
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 45, Printed 04/21/23Measurement Systems Analysis
Discrimination
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 46, Printed 04/21/23Measurement Systems Analysis
Range Charts & Discrimination
Indicates Poor Precision
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 47, Printed 04/21/23Measurement Systems Analysis
Bias and Repeatability
Precise Imprecise
Accurate
InaccurateBias
You can correct for BiasYou can NOT correct for Imprecision
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 48, Printed 04/21/23Measurement Systems Analysis
Bias• Difference between
average of measurements and an Agreed Upon standard value
• Known as Accuracy
• Cannot be evaluated without a Standard
• Adds a Consistent “Bias Factor” to ALL measurements
• Affects all measurements in the same way
StandardValue
Measurement Scale
Bias
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 49, Printed 04/21/23Measurement Systems Analysis
Causes of Bias
• Error in Master
• Worn components
• Instrument improperly calibrated
• Instrument damaged
• Instrument improperly used
• Instrument read incorrectly
• Part set incorrectly (wrong datum)
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 50, Printed 04/21/23Measurement Systems Analysis
Bias and QS9000Bias - The difference between the observed Average of measurements and the master Average of the same parts using precision instruments. (MSA Manual Glossary)
The auditor may want evidence that the concept of bias is understood. Remember that bias is basically an offset from ‘zero’. Bias is linked to Stability in the sense that an instrument may be ‘zeroed’ during calibration verification. Knowing this we deduce that the bias changes with instrument use. This is in part the concept of Drift.
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 51, Printed 04/21/23Measurement Systems Analysis
Bias
• I choose a caliper (resolution 0.01) for the measurement. I measure a set of parts and derive the average.
• I take the same parts and measure them with a micrometer (resolution 0.001). I then derive the average.
• I compare the two averages. The difference is the Bias.
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 52, Printed 04/21/23Measurement Systems Analysis
Repeatability• Variation among
repeated measurements
• Known as Precision
• Standard NOT required
• May add or subtract from a given measurement
• Affects each measurement randomly
Measurement Scale
Repeatability
Margin of ErrorDoesn’t address Bias
5.15 = 99%
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 53, Printed 04/21/23Measurement Systems Analysis
Repeatability Issues
• Measurement StepsSample preparation
Setting up the instrument
Locating on the part
• How much of the measurement process should we repeat?
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 54, Printed 04/21/23Measurement Systems Analysis
Using Shewhart Charts I
Repeatability
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 55, Printed 04/21/23Measurement Systems Analysis
Using Shewhart Charts II
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 56, Printed 04/21/23Measurement Systems Analysis
• Same appraiser, Same part, Same instrument
• Multiple readings (n≥10 with 20 to 40 better)
• AnalysisAverage minus Standard Value = Bias
5.15* Standard Deviation = Repeatability
or +/- 2.575 [99% repeatability]
or +/- 2 [95% repeatability]
• Histogram
• Probability
Evaluating Bias & Repeatability
AIAGTrue
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 57, Printed 04/21/23Measurement Systems Analysis
Repeatability Issues
• Making a measurement may involve numerous steps
Sample preparation
Setting up the instrument
Locating the part, etc.
• How much of the measurement process should we repeat? How far do we go?
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 58, Printed 04/21/23Measurement Systems Analysis
Bias & Repeatability Histogram
Never include assignable cause errors
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 59, Printed 04/21/23Measurement Systems Analysis
Linearity
• The difference in the Bias or Repeatability across the expected operating range of the instrument.
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 60, Printed 04/21/23Measurement Systems Analysis
Plot Biases vs. Ref. Values
Linearity = |Slope| * Process Variation = 0.1317*6.00 = 0.79% Linearity = 100 * |Slope| = 13.17%
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 61, Printed 04/21/23Measurement Systems Analysis
Causes of Poor Linearity
• Instrument not properly calibrated at both Upper and Lower extremes
• Error in the minimum or maximum Master
• Worn Instrument
• Instrument design characteristics
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 62, Printed 04/21/23Measurement Systems Analysis
Reproducibility• Variation in the
averages among different appraisers repeatedly measuring the same part characteristic
• Concept can also apply to variation among different instruments
Includes repeatability which must be accounted for.
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 63, Printed 04/21/23Measurement Systems Analysis
Reproducibility Example
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 64, Printed 04/21/23Measurement Systems Analysis
Calculating Reproducibility (I)
• Find the range of the appraiser averages (R0)
• Convert to Standard Deviation using d2*(m=# of appraisers; g=# of ranges used = 1)
• Multiply by 5.15
• Subtract the portion of this due to repeatability
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 65, Printed 04/21/23Measurement Systems Analysis
Calculating Reproducibility
People variance
Trials
Times done
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 66, Printed 04/21/23Measurement Systems Analysis
Stability• Variation in
measurements of a single characteristic
• On the same master
• Over an extended period of time
• Evaluate using Shewhart charts
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 67, Printed 04/21/23Measurement Systems Analysis
Evaluate Stability with Run Charts
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 68, Printed 04/21/23Measurement Systems Analysis
Stability
Both gages are stable, but.....
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 69, Printed 04/21/23Measurement Systems Analysis
Importance of Stability
• Statistical stability, combined with subject-matter knowledge, allows predictions of process performance
• Action based on analysis of Unstable systems may increase Variation due to ‘Tampering’
• A statistically unstable measurement system cannot provide reliable data on the process
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 70, Printed 04/21/23Measurement Systems Analysis
Methods of Analysis
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 71, Printed 04/21/23Measurement Systems Analysis
Analysis Tools
• Calculations of Average and Standard Deviation
• Correlation Charts
• Multi-Vari Charts
• Box-and-Whisker Plots
• Run charts
• Shewhart charts
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 72, Printed 04/21/23Measurement Systems Analysis
Average and Standard Deviation
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 73, Printed 04/21/23Measurement Systems Analysis
Correlation Charts
Describe Relationships
• Substitute measurement for desired measurement
• Actual measurement to reference value
• Inexpensive gaging method versus Expensive gaging method
• Appraiser A with appraiser B
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 74, Printed 04/21/23Measurement Systems Analysis
Substitute Measurements
• Cannot directly measure quality
• Correlate substitute measure
• Measure substitute
• Convert to desired quality
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 75, Printed 04/21/23Measurement Systems Analysis
Comparing Two Methods• Two
methods
• Measure parts using both
• Correlate the two
• Compare to “Line of No Bias”
• Investigate differences
Magnetic
Stripping
Line of Perfect Agreement
Line of Correlation
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 76, Printed 04/21/23Measurement Systems Analysis
Measurements vs. Reference Data
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 77, Printed 04/21/23Measurement Systems Analysis
Measurements vs. Reference Correlation
Disparity
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 78, Printed 04/21/23Measurement Systems Analysis
Comparing Two Appraisers
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 79, Printed 04/21/23Measurement Systems Analysis
Run Charts Examine Stability
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 80, Printed 04/21/23Measurement Systems Analysis
Multiple Run Charts
More than 3 appraisers confuses things...
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 81, Printed 04/21/23Measurement Systems Analysis
Multi-Vari Charts
High Reading
Low Reading
Average Reading
• Displays 3 points
• Length of bar; bar-to-bar; Bar cluster to cluster
• Plot High and Low readings as Length of bar
• Each appraiser on a separate bar
• Each piece in a separate bar cluster
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 82, Printed 04/21/23Measurement Systems Analysis
Multi-Vari Type I• Bar lengths
are long
• Appraiser differences small in comparison
• Piece-to-piece hard to detect
• Problem is repeatability
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 83, Printed 04/21/23Measurement Systems Analysis
Multi-Vari Type II• Appraiser
differences are biggest source of variation
• Bar length is small in comparison
• Piece-to-piece hard to detect
• Problem is reproducibility
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 84, Printed 04/21/23Measurement Systems Analysis
Multi-Vari Type III• Piece-to-piece
variation is the biggest source of variation
• Bar length (repeatability) is small in comparison
• Appraiser differences (bar-to-bar) is small in comparison
• Ideal Pattern
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 85, Printed 04/21/23Measurement Systems Analysis
Multi-Vari Chart ExampleNormalized Data
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 86, Printed 04/21/23Measurement Systems Analysis
Multi-Vari Chart, Joined
Look for similar pattern
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 87, Printed 04/21/23Measurement Systems Analysis
Using Shewhart Charts
• Subgroup = Repeated measurements,, same piece
• Different Subgroups = Different pieces and/or appraisers
• Range chart shows precision (repeatability)
• Average chart “In Control” shows reproducibilityIf subgroups are different appraisers
• Average chart shows discriminating powerIf subgroups are different pieces
(“In Control” is BAD!)
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 88, Printed 04/21/23Measurement Systems Analysis
Shewhart Charts
This is not a good way to plot this data
Too many lines
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 89, Printed 04/21/23Measurement Systems Analysis
Shewhart Chart of Instrument
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 90, Printed 04/21/23Measurement Systems Analysis
Gage R&R Studies
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 91, Printed 04/21/23Measurement Systems Analysis
Gauge R&R Studies
• Developed by Jack Gantt
• Originally plotted on probability paper
• Revived as purely numerical calculations
• Worksheets developed by AIAG
• Renewed awareness of Measurement Systems as ‘Part of the Process’
Consider Numerical vs. Graphical Data Evaluations
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 92, Printed 04/21/23Measurement Systems Analysis
Terms Used in R&R (I)
• n = Number of Parts [2 to 10]Parts represent total range of process variation
Need not be “good” parts. Do NOT use consecutive pieces.
Screen for size
• a = Number of AppraisersEach appraiser measures each part r times
Study must be by those actually using
• R - Number of trials– Also called “m” in AIAG manual
• g = r*a [Used to find d2* in table 2, p. 29 AIAG manual]
1 Outside Low/High1 Inside Low/High
Target
Minimum of 5.2 to 10 To accommodate
worksheet factors
1 23
4 5
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 93, Printed 04/21/23Measurement Systems Analysis
• R-barA = Average range for appraiser A, etc.• R-double bar = Average of R-barA, R-barB
• Rp = Range of part averages
• XDIFF = Difference between High & Low appraiser averagesAlso a range, but “R” is not used to avoid confusion
• EV = 5.15 = Equipment variation (repeatability)
• EV = 5.15 = Equipment variation (reproducibility)
• PV = Part variation
• TV = Total variation
Terms Used in R&R (II)
Process Variation
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 94, Printed 04/21/23Measurement Systems Analysis
R&R Calculations
Measurement System Variation
Product Process Variation
Left over Repeatability
Remember - Nonconsecutive
Pieces
Left over Repeatability
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 95, Printed 04/21/23Measurement Systems Analysis
Accumulation of Variances
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 96, Printed 04/21/23Measurement Systems Analysis
Evaluating R&R
• %R&R=100*[R&R/TV] (Process Control)
• %R&R=100*[R&R/Tolerance] (Inspection)
• Under 10%: Measurement System Acceptable
• 10% to 30%: Possibly acceptable, depending upon use, cost, etc.
• Over 30%: Needs serious improvement
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 97, Printed 04/21/23Measurement Systems Analysis
Analysis of Variance I
• Mean squares and Sums of squares
• Ratio of variances versus expected F-ratio
• AdvantagesAny experimental layout
Estimate interaction effects
• DisadvantagesMust use computer
Non-intuitive interpretation
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 98, Printed 04/21/23Measurement Systems Analysis
Analysis of Variance II
• The n*r measurements must be done in random sequence [a good idea anyway]
• Assumes that EV [repeatability] is normal and that EV is not proportional to measurement [normally a fairly good assumption]
• Details beyond scope of this course
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 99, Printed 04/21/23Measurement Systems Analysis
Special Gauging Situations
• Go/No-Go
• Destructive Testing
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 100, Printed 04/21/23Measurement Systems Analysis
If Gauges were Perfect
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 101, Printed 04/21/23Measurement Systems Analysis
But Repeatability Means We Never Know The Precise Value
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 102, Printed 04/21/23Measurement Systems Analysis
So - Actual Part Acceptance Will Look Like This:
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 103, Printed 04/21/23Measurement Systems Analysis
The Effect of Bias on Part Acceptance
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 104, Printed 04/21/23Measurement Systems Analysis
Go/No-Go gauges
• Treat variables like attributes
• Provide less information on the process, but...
• Are fast and inexpensive
• Cannot use for Process Control
• Can be used for Sorting purposes
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 105, Printed 04/21/23Measurement Systems Analysis
“Short” Go/No-Go Study
• Collect 20 parts covering the entire process range
• Use two inspectors
• Gage each part twice
• Accept gauge if there is agreement on each of the 20 parts
* May reject a good measuring system
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 106, Printed 04/21/23Measurement Systems Analysis
Destructive Tests
• Cannot make true duplicate tests
• Use interpenetrating samples
• Compare 3 averages
• Adjust using √n
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 107, Printed 04/21/23Measurement Systems Analysis
Destructive Tests: Interpreting Samples
AIAG does not address
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 108, Printed 04/21/23Measurement Systems Analysis
Summary
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 109, Printed 04/21/23Measurement Systems Analysis
Measurement Variation
• Observed variation is a combination of the production process PLUS the measurement process
• The contribution of the measurement system is often overlooked
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 110, Printed 04/21/23Measurement Systems Analysis
Types of Measurement Variation
• Bias (Inaccuracy)
• Repeatability (Imprecision)
• Discrimination
• Linearity
• Stability
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 111, Printed 04/21/23Measurement Systems Analysis
Measurement Systems
• Material
• Characteristic
• Sampling and Preparation
• Operational Definition of Measurement
• Instrument
• Appraiser
• Environment and Ergonomics
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 112, Printed 04/21/23Measurement Systems Analysis
Measurement Systems Evaluation Tools
• Histograms
• Probability paper
• Run Charts
• Scatter diagrams
• Multi-Vari Charts
• Gantt “R&R” analysis
• Analysis of Variance (ANOVA)
• Shewhart “Control” Charts
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 113, Printed 04/21/23Measurement Systems Analysis
Shewhart Charts
• Range chart shows repeatability
• X-bar limits show discriminating power
• X-double bar shows bias(if a known standard exists)
• Average chart shows stability(sub-groups overtime)
• Average chart shows reproducibility(sub-groups over technicians/instruments)
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©2/2001 Cayman Systems Revision M(513) 777-3394 -- 16949.com Slide 114, Printed 04/21/23Measurement Systems Analysis
Conclusion
• Rule of Ten
• Operating Characteristic Curve
• Special Problems
Go/No-Go Gages
Attribute Inspection
Destructive Testing