Measurement Systems Analysis (MSA)
Understand the approaches used in measurement systems analysis.
Overview
This course provides learners with an overview of Measurement Systems Analysis (MSA), and the approaches used to analyse both attribute and variable measurements systems defined in the reference manual.
Who Should Attend Measurement Systems Analysis? h3 >
Anyone supporting the Advanced Product Quality Planning (APQP) process, especially those involved in gage design, process measurement and initial process studies to support new product and process introduction.
Prerequisites h3 >
Learners should be able to explain ISO 9001 and IATF 16949 requirements which can be obtained by attending our IATF 16949:2016 Requirements Course.
Course Summary
1 day
4-12 candidates
Classroom, Virtual Classroom & Online
Course Dates
Measurement Systems Analysis (MSA) currently does not have any dates scheduled. If you are interested in this course, please click below to get in touch with us so we can organise a date for you.
Get in touchMeasurement Systems Analysis Course Outcomes
You will have the knowledge to:
- Identify the correct measurement systems analysis tool to use when evaluating measurement systems
- Determine whether a measurement system is acceptable for its intended use
- Understand the different sources of variation present in a measurement system
- Explain stability, bias, linearity, repeatability and reproducibility
You will learn the skills to:
- Analyse both variable and attribute gages
- Conduct stability studies, bias studies and linearity studies
- Conduct repeatability and reproducibility (GR&R) studies on variable measurement systems
- Conduct measurement systems study on attribute measurement systems using risk analysis methods
- Understand the statistical properties of measurement systems
- Appreciate how measurement systems errors can affect the quality of the output data leading to incorrect decisions
- Recognize the different approaches used for both attribute and variable measurement systems
- Identify the sources of measurement systems error