MSA which means Measurement System Analysis is an important part of the Production Process. It is used to ascertain the correctness of the readings taken by the different instruments under different conditions.
If you don't conduct gauge studies, you don't know the capability of your gauges or the people who use them. Every measurement is suspect! You must know the uncertainty of your measurement system when making acceptance decisions and for Statistical Process Control.
We collect data for various reasons. In all cases, the data is analyzed and decisions are made. The effectiveness of the decisions depends upon the quality of the data. The existence of variation in data is inevitable, and all precautions must be taken to reduce it as much as possible. In a manufacturing process, as well as in a service process, the output is affected by various factors at various levels. Output is then measured according to some pre-established methods, a measurement system which has nothing to do with the process. This measurement process is used to generate numerical values of the subject of interest. Therefore, a measurement is defined as: "The assignment of numerical values to things to represent the relations among them with certain properties."
When data is collected, its values are affected by two independent processes. The first is the manufacturing or service process. The second is the measurement system process. The possibility of variation that can creep into the data from the measurement system can make the data unreliable for decision making purposes. Therefore, steps must be taken to reduce the variations in the measurement system as much as possible. Variation in a set of measurements is caused by people collecting the data, methods used to collect data, the data collection environment, measurement equipment used and the object of interest. The interaction between these components and their effect on the numerical values generated as data are to be evaluated to improve the measurement system. A major portion of the work of managing a measurement system is directed towards monitoring and controlling variation from that system.
If the magnitude of variation from the measurement system is not acceptable, then the system must be modified or replaced.
If we improve the manufacturing or service process without this knowledge, then we are tampering with the
process and wasting valuable resources.
A proactive approach to eliminate such waste can be accomplished through MSA.
Measurement system errors can be classified into five categories - bias, repeatability, reproducibility, stability and linearity.
One of the objectives of a measurement system study is to obtain information relative to the amount and types of measurement variation associated with a measurement system when it interacts with its environment. This information is valuable, since for the average production process, it is far more practical to recognize repeatability and calibration bias and establish reasonable limits for these, than to provide extremely accurate gauges with very high repeatability.
Applications of MSA:
A criterion to accept new measuring equipment.
A comparison of one measuring device against another.
A basis for evaluating a gauge suspected of being deficient.
A comparison for measuring equipment before and after repair.
A required component for calculating process variation, and the acceptability level for a production process.
Estimating percentage variation in the process data due to measuring equipment.
MSA studies are of the following types: