of using a data-based procedure is largely determined by the quality of
measurement data used. If the data
quality is low, the benefit of the procedure of the measurement data is
perceived to be low. Similarly, if the
quality of the data is high, the benefit is likely to be high also.
The quality of measurement data is defined by statistical properties of multiple measurements obtained from a measurement system operating under stable conditions.
This course focuses on Measurement Systems Analysis (MSA). MSA is a scientific and objective method of analyzing the validity of a measurement system. It is a “tool” which quantifies Repeatability, Reproducibility and all variation associated with a measurement process. Potential sources of variation include gages, standards, procedures, software, environmental components, as well as others.
the measurement system is also a process, it is subject to variation of its
Measurement systems analysis (MSA) serves to determine the accuracy
and variation of a measurement system. If a measurement system is prone to
large variation, it can falsely indicate that the product or process it is
measuring has too much variation. This can lead to wrong judgment and valuable
time wasted trying to find the source of nonexistent problems.
For the measurement data to be accurate, the
measurement system must be accurate.
To control the measurement system variation, you must first identify the sources of the variation, then you must either eliminate or reduce the various causes.
The training will use examples
representing processes within the organization to facilitate learning and
transfer of knowledge.
should be able to interpret and deploy MSA upon completion of this training.
They will be able to:
This training is recommended for all personnel involved in ongoing measurement control and calibration activities. It is also suitable for personnel responsible to approve the use of new monitoring and measuring equipment prior to use.