Measurement System Analysis (MSA)
Measurement System Analysis often referred to as MSA, is an objective method that analyses the amount of variation caused by the measurement system. MSA aims to ensure that a measurement system delivers reliable results with repeatability and reproducibility. The first step in assessing a system is to understand this process and determine whether it will satisfy our AIAG MSA 4th edition requirements.
- It involves assessing the effect of the measurement system on the measured value in quantifiable terms
- The emphasis is on the impact of equipment and personnel
- MSA is also an essential component of Six Sigma methodologies and other quality management systems. The numerical values of the system's statistical properties are determined and compared to accepted standards. MSA evaluates the equipment, operations, procedures, software, and personnel that influence the assignment of a number to a measurement characteristic.
- A measurement system analysis study is designed to ensure that your measurement system - gages, methods, and procedures - are stable and capable of measuring data before you begin to improve your process. Measurement procedures and systems must provide:
- i) Adequate resolution
- ii) Unbiased results
- iii) A slight variation compared with specified tolerances
MSA Pro Software
A complete solution for gage management is to perform MSA studies, including bias, calibration & verification, Gage R & R, and lastly, stability studies for variable and attribute gages.
We have Private Training available for more than 5 people from an organization. This training is provided at your location.
- Understanding Core Tools: Measurement System Analysis (MSA)
- Measurement Systems Analysis (MSA), including Advanced Analysis (ANOVA)
- Aerospace Risk Management and Analysis Series Setting Up for Process Capability and MSA
- Understanding Core Tools: (APQP/PPAP, DFMEA & DVP&R, PFMEA/Control Plan, SPC, and MSA)
- Understanding Core Tools (APQP/PPAP, DFMEA, DVP&R, SPC, and MSA) Following the AIAG FMEA 4th Edition Methodology