Course Description
Fundamental to collecting data on any process or equipment is a characterization of measurement. This includes variables data such as CMM measurements, laboratory measurements, or any measurements made on a continuous scale, as well as attribute inspection data into categories (e.g. pass/fail or defect categories). Data, which do not come from an accurate measurement system, may lead to erroneous conclusions.
This course provides the participants with an understanding of basic measurement process terminology including discrimination or resolution, bias, accuracy, precision, repeatability and reproducibility, along with measurement precision assessment. It provides the methodology to plan, conduct, analyze, and interpret measurements system capability study, which includes a gauge repeatability and reproducibility (R&R) study for variables data and attribute measurement study techniques for attribute data such as inspection processes. Questions such as operator differences, gauge drift issues, overkill, and escapes are addressed.
Who Should Attend
This course is designed for engineers, quality professionals, researchers, and managers who need to use data in statistical applications and who want to ensure that data is suitable for analysis.
Learning Objectives
Through training, participants will learn how to:
- Understand and use basic measurement process elements such as resolution, accuracy, bias, precision, and repeatability and reproducibility
- Plan, conduct, analyze, interpret, and present gauge studies for estimating precision (gauge r&r for repeatability & reproducibility analysis)
- Improve the precision of a measurement process
Course Outline
Measurement Terminology
- Why MSA Studies are Necessary
- Measurement Error to Confirm Data Validity
- Order of Data Collection
- Basic Measurement Model
- Terminology
- Resolution or Discrimination
- Bias
- Accuracy
- Precision
- Repeatability and Reproducibility
Gauge R&R Studies for Variables Data
- Resolution Assessment
- Percent of Tolerance
- Percent of Variation
- ndc: Number of Distinct Categories
- Data Checksheet
- Gauge Run Chart
- Crossed GRR Analysis
- Expanded GRR Analysis
- Destructive and Non-Repeatable Data Analysis
- The Short Method
- Improving a Measurement Process for Variables Data
- Planning a GRR Study
- Exercise: Hands-On Data Collection and Analysis
Attribute Agreement Analysis for Attribute Data
- Properties of Attribute Data
- Planning an Attribute Agreement Study
- Percent Agreement
- Kappa Statistic
- Determining Escape Rates and Over-kill Rates
- Improving a Measurement Process for Attribute Data
- Exercise: hands-On Data Collection and Analysis
Prerequisites
Basic SPC or Basic Statistics
Course Format
12 hours
Instructor-led class training, with opportunities to practice learned skills using prepared data and hands-on data collection exercises
Minitab or JMP Statistical Software
Course Instructor: Saleha Yusof-Mullenix – Consultant, Statistical/Quality Methods and Six Sigma for Manufacturing and Research
Course Evaluations Set 1
Course Evaluations Set 2
8:30am-4:30pm (EST) each day
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