In business, it is essential to understand how to analyze data to make sound decisions. One tool that can be used for this purpose is measure system analysis (MSA). MSA is a statistical method used to evaluate the accuracy and precision of measurements. It can be used for any measurement, including chemical, physical, or mechanical measures.
MSA can be used to determine if a measurement system is adequate for its intended purpose. It can also be used to compare different measurement systems or to compare different operators using the same measurement system. When performed correctly, MSA can help improve the quality of measurements and reduce variability.
Why do we need to make sure that our Measurement System is sound?
Simply put, we want to make sure that any variation comes from the actual product or service we are measuring. If we have high variation due to the way we measure, we can not have confidence in any baseline or improvement measures.
How Measure System Analysis Is Used
Several types of MSA studies can be performed, each with its specific purpose. Some common types of MSA studies include:
-Gage repeatability and reproducibility (R&R) studies: These studies assess the variability of measurements made by a single operator using a single measurement system. They also assess the variability of measurements made by multiple operators using the same measurement system.
-Bias studies: Bias studies are used to assess systematic error in a measurement system. Systematic error can occur when there is a flaw in the design of the measurement system or when operator error is not taken into account.
-Precision studies: Precision studies are used to assess the random error in a measurement system. Random error occurs when there is variation in the measurements that cannot be attributed to a specific cause.
-Accuracy studies: Accuracy studies assess systematic and random errors in a measurement system.
-Linearity studies: Linearity studies assess the relationship between readings from a measurement system and valid values. This type of study is often used when calibrating new measuring devices.
Steps to Conduct an MSA
There are three steps in conducting an MSA: 1) planning and design, 2) data collection, and 3) data analysis.
The first step is to determine the purpose of the MSA and identify the user requirements. The second step is to collect data using the measurement system under study. This data must be collected in a way that allows for replication to be used in statistical analysis. The third step is to analyze the data using statistical methods, such as analysis of variance (ANOVA) or regression analysis, to identify sources of error in the measurement system.
Measure system analysis is a powerful tool that can improve measurement systems’ accuracy. By identifying sources of error, MSA can lead to improved product quality and decreased costs. If you want to enhance your measuring systems, consider conducting an MSA.
