Measurement Systems Analysis
Statistical and Analytical Courses
Measurement Systems Analysis is designed for Engineers, Scientists and Managers who have direct responsibility for measurement evaluation, selection and control. This course covers the basic concepts associated with measurement systems analysis, repeatability, reproducibility, accuracy, linearity, stability, standards selection and use, calibration and compensation and measurement control.

Download Curriculum

Download the full curriculum for Statistical and Analytical courses in PDF format.

Biotech, Pharmaceutical & Medical Device Courses

Systematic product development, Quality by Design courses, consulting services and analytical training for biotechnology, pharmaceutical and medical device industries. QbD provides guidance to facilitate design of products and processes that maximize the product’s efficacy and safety profile while enhancing product manufacturability and control.

Lean Six Sigma

Complete curriculum for new product development, manufacturing and business process performance optimization.

Tools & Templates

Development tools and templates created by Thomas A. Little Consulting have been used by numerous companies to aid and support various aspects of product development, problem solving, data analysis and risk assessment.

Course Objectives
  1. Determine gage capability.
  2. Assess accuracy, linearity, stability, repeatability and reproducibility in test equipment
  3. Design and deploy SPC for measurement control.
  4. Select and establish standards.
  5. Describe proper methods for instrument calibration and compensation.
  6. Conduct gage capability for inspection activities.
  7. Discuss how MSA impacts customer satisfaction.
Detailed Course Outline
Section I: Introduction to MSA
MSA is a key to systematic product development
Background statistical principles
Sources of error
Focus on the measurement process
Section II: Terms and Definitions
Section III: R&R, Linearity, & Accuracy
2 factor crossed design for Variables MSA
Repeatability & Reproducibility
R&R and Capability Example
Accuracy example
Linearity example
Section IV: Correlation, Calibration and Compensation
Correlation and compensation
Soft compensation versus standard calibration
Scatterplot Method
Problems with r²
Section V: SPC for Measurement Control
Selection and utilization of Standards
SPC for Measurement Control
SPC using stable standards
SPC using unstable standards
Section VI: MSA for Attributes
Operational Definitions
Effectiveness, P(miss), P(false alarm)
Kappa, escape rate and bias