Measurement Uncertainty Analysis Class Outline

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Training Measurement Uncertainty Training Uncertainty / SPC Analysis Course Outline

Uncertainty / SPC Analysis Course Outline

This outline applies to the measurement uncertainty analysis course presented by Integrated Sciences Group. This course not only includes instruction in the principles of measurement uncertainty analysis and statistical process control, it also emphasizes the practical application of these principles through hands-on training in the use of ISG's UncertaintyAnalyzer software. A course segment is also devoted to discussion of specific measurement uncertainty analysis problems relevant to the students' workplace. Click class schedule for our 2008 open-enrollment training locations and dates.

Course Objectives

This course is intended for engineers, scientists and other technical personnel responsible for designing, testing, calibrating, installing or maintaining measurement equipment and monitoring systems. This course is also beneficial for research and development personnel and quality assurance engineers in all fields of science and technology. Upon completion of the course, students will know how to:

Define measurement processes - direct, multivariate and system
Evaluate equipment specifications to identify sources of measurement error
Select the appropriate error distributions
Estimate uncertainties using Type A and Type B analysis methods
Identify and account for statistical outliers
Establish error correlations
Determine sensitivity coefficients
Combine uncertainties
Estimate uncertainty growth
Refine bias uncertainty estimates using Bayesian analysis
Develop and report uncertainty estimates for direct and multivariate measurements
Develop and report uncertainty estimates for measurement systems and system modules
Use uncertainty estimates to establish tolerance limits, analyze risks and perform statistical tests
Apply SPC to control measurement processes

Day One - Uncertainty Analysis Concepts

The first day discusses the need for uncertainty estimation, reviews guides and standards for estimating measurement uncertainty, and presents basic concepts central to measurement uncertainty analysis. Measurement errors are defined, error distributions and statistics are discussed, and the relationship between measurement error and uncertainty is clearly established. Instruction involves class quizzes to re-enforce key concepts and methods.

Why Estimate Uncertainty?
Standards and Guidelines
Technology Management Requirements

Uncertainty Analysis Guidelines
ISO 17025 and ANSI/NCSL Z540
NIST Technical Note 1297

Basic Concepts
Populations
Data Sampling and Related Statistics
Heuristic Estimates
Making Approximations

   Error Distributions
   Overview
   Key Elements
   Attribute Measurement
   Parameter Measurement
   Error Propagation
   Applicable Distributions

   Error and Uncertainty
   Measurement Error Definition
   Error Classification
   Error Description
   Parameter Measurement Error
   Uncertainty Definition

Day Two - Estimating Uncertainty

The second day covers methods and procedures for estimating and combining measurement uncertainties. Type A and Type B methods of estimating measurement process uncertainties are discussed and a general framework for conducting uncertainty analyses is presented. Using uncertainty estimates to make decisions, analyze risk and perform statistical tests is also discussed. Instruction involves class quizzes and hands-on exercises using UncertaintyAnalyzer to illustrate and re-enforce key concepts and methods.

Review of Day 1

Quantifying Uncertainty
Distribution Variance
Error Variance
Population Variance
The Variance Addition Rule
Combining Uncertainties

Types of Uncertainty Estimates
Type A Estimates
Type B Estimates
Type A,B Estimates

Estimating Process Uncertainties
Bias Uncertainty
Random Uncertainty
Resolution Uncertainty
Stress Response Uncertainty
Data Acquisition Uncertainty
Environmental Factors Uncertainty
Recap of Process Uncertainty Estimation

   The General Uncertainty Analysis Process
   Error Modeling
   Develop the Error Model
   Identify the Process Errors
   Recap of Error Modeling

   Using Uncertainty Estimates
   Set Tolerance Limits
   Analyze Risks in Testing and Calibration
   Perform Statistical Tests
   Apply SMPC (Bayesian Analysis)

Day Three - Estimating Uncertainty Analysis (cont.)

The third day focuses on the all important application of measurement uncertainty analysis principles and concepts. Instruction includes hands-on use of UncertaintyAnalyzer to illustrate and re-enforce key concepts, methods and procedures for analyzing and combining uncertainties for direct measurements. Instruction also includes an overview of uncertainty analysis for multi-parameter (multivariate) measurements and class quizzes using UncertaintyAnalyzer to illustrate and re-enforce key concepts and methods.

Review of Day 2

Overview of Program Features
Main Screen Functions
Analysis Guide Screen
Analysis Description Screen
User Defined Screen
System Analysis Screen
Measurement Units and Instrument Databases

Direct Measurement Analysis Overview
Defining the Measurement Configuration
Analyzing Measurement Process Uncertainties
Establishing Correlations
Uncertainty Combination
Uncertainty Growth

Direct Measurement Analysis Class Examples

   Multivariate Analysis Overview
   The System Equation
   Estimating Measurement Process Uncertainties
   Establishing Correlations
   Computing Uncertainty
   Developing a Measuring System

Day Four - Estimating Uncertainty

The fourth day includes hands-on class examples that reinforce multivariate analysis procedures. Instruction also includes an overview of measurement system analysis and hands-on class examples using UncertaintyAnalyzer that illustrate and re-enforce key concepts and methods. Other analysis examples, relevant to the students' workplace, will also be discussed as time allows.

Review of Day 3

Multivariate Analysis Class Examples

System Analysis Overview
Defining the System
Characterizing the Modules

Evaluating Module Uncertainties
Evaluating System Uncertainty

System Analysis Class Examples

Other Analysis Examples
Time will be spent solving uncertainty analysis problems relevant to the students' workplace.

Day Five - Applying Uncertainty Estimates and Process Control Concepts*

The fifth day focuses on the use of uncertainty estimates and on concepts that are important for controlling measurement processes, tracking and controlling equipment attribute values and setting parametric calibration intervals. Instruction includes hands-on class examples using SPCView to demonstrate and re-enforce key concepts and methods.

* Applies to 2008 classes only.

Applying Uncertainty Estimates

Develop Tolerances

Manage Risks
Select Measurement Method
Test Hypotheses
Apply SMPC (Bayesian Analysis)

Overview of SPC Concepts and Methods
The Measurement Process Model
Setting Up the Statistics
Evaluating the Process
Setting Control Limits
Using Control Limits
Practical Considerations

Controlling Measurement Processes
Setting Control Limits
Importing Uncertainty Analysis Data
Creating and Interpreting Control Charts
Rejecting Processes
Projecting Inspection Intervals

   Controlling Equipment Attributes
   Implementing Tolerance Limits
   Importing Measurement History Data
   Creating and Interpreting Trend Charts
   Estimating Calibration Intervals

   Estimating Parameter Intervals
   Setting Control Limits
   Importing Measurement History Data
   Projecting Calibration Intervals

Controlling Production Processes

Setting Control Limits

Evaluating Trends
Setting Process Inspection Intervals

What to Bring

PC Notebook
A PC laptop running Windows 98 or higher is required.

Study Materials
Pens, student workbook, UncertaintyAnalyzer and SPCView software and user manuals are provided.

Analysis Problems
Bring any uncertainty analysis problems that are of interest to your workplace.

Integrated Sciences Group
14608 Casitas Canyon Road Bakersfield, CA 93306
1-800-400-7866 FAX 1-661-872-3669 Tech Support 1-661-872-1683

Page Updated March 23, 2008