Background, Introduction, Benefits and Objective
Process managers, technicians, lab technicians and developers require suitable measurement devices to measure values to evaluate processes, to determine the characteristic properties of products, to inspect incoming goods and to carryout tests. Often, operators – after calibrating the measurement devices – are inclined to trust the measurement results, and often trust digital devices more than analogous measurement processes. The measurement method frequently involves scatter, which renders the measurement inaccurate.

This scatter, amongst other things, is determined through measurement system analysis (MSA).

Measurement system analysis is a procedure that makes it possible to determine whether the measuring device is capable of performing the measurement task in question under the existing conditions (including personnel). To make statements on the measuring device’s scatter, on accuracy, on precision, etc., repetitions are carried out by various persons on the same parts and various parts. Based on the measurement data obtained, meaningful graphs are produced and measurement system capability indices are determined, which allows for a rapid judgement ofthe measurement system.

Consequences of unsuitable measurement systems
A suitable measurement system creates confidence in the data obtained. This is a fundamental requirement for the characterization of processes and products, which are generally subject to specific customer requirements (target value and tolerances).

A measurement system with an excessively high scatter often yields incorrect measurement values. Consequently, this ultimately means that good parts are defined as rejects and bad parts are delivered to the customer.

A measurement system analysis generally leads to the recognition that the measurement system must be improved. Such an improvement often leads to a clear fall in the rejection rate with no need to change the production process.

The Training
The training on the measurement system analysis first of all explains the benefits and the background using simple practical examples. The consequences of using bad measurement devices are clearly demonstrated. Further practical examples are used to explain and describe terms such as tolerance, resolution, accuracy, linearity and stability. Software-assisted calculation and interpretation of measurement capability indices will be practiced. Finally, measurement system analysis for destructive testing is discussed and also extended for so-called categorical (attributive or qualitative) data.

The three types of a measurement system analysis for variable data – according to the requirements of the automotive industry – are discussed and calculated using data from practical examples: Type 1, type 2 and type 3.