Why are uncertainties important

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Type A refers to random effects that can be calculated through standard deviations of repeated measurements. These sources of uncertainty have to do with repeatability and reproducibility.

Type A sources can be improved by analyzing and improving your measurement processes. Type B sources refer to uncertainties which do not come from analyzing repeated measurements. These are typically provided on the certificates of calibration for the reference materials you use to calibrate the equipment, or are given by the equipment manufacturer in the manual or on product spec sheets. So, why do uncertainties matter?

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Zobia Hamid Follow. Introduction to the guide of uncertainty in measurement. Calculating Uncertainties. Fair Test. Evolution of atomic theory. As being explained in the previous post, traceability is one of the fundamental concept in metrology. Traceability is a property of measurement results that can be related to an international reference value via an unbroken chain of comparison with stated uncertainty for each comparison result.

For dimensional measurement, the reference value is the definition of metre. When a measurement result is traceable, the results can be considered reliable and trustable and can be compared to other results having their uncertainty statement as well. Figure 2 shows the traceability chain to the definition of metre for dimensional measurement. In figure 2, the definition of the metre is at the top and it is where the traceability chain stops. The definition is nominal so that there is no uncertainty associated with it.

The traceability chain is established via calibration , that is the process to link between a bottom level and top level in the chain. The explanation of figure 2 is as follows from the top to bottom. The rest of traceability chain will be general laboratory levels until shop floor levels. The calibrated CMM can then be used to calibrate other optical non-contact measuring instruments.

Measurement uncertainty is very important for decision making in pre-production phase. Figure 3 illustrates the importance in pre-production decision making. In figure 3, a process capability test for a production machine in this case milling machine is carried out to verify whether the machine can produce parts according to their specification tolerance.

Process capability is carried out by producing a small batch of the designed parts, for example a production of 50 pieces. After the 50 parts are made, all of these parts are then measured with a measuring system, let say a CMM. In other words, measurement uncertainties have a significant effect to the value of calculated process capability indices.

Then, managements will decide to purchase more expensive production machines. In fact, the machine under evaluation is actually capable of producing the parts, but since the measurement is not correct, the final process capability indices are incorrect as well, leading to a wrong management decision. The role of measurement uncertainty in post-production phase is in quality control process for conformance test between a part and its tolerance.

Figure 4 shows the illustration on how measurement uncertainties affect the tolerance zone by reducing the allowable tolerance zone and hence making the acceptance zone to be narrow meaning, the conformance decision becomes more stringent than what has been specified in the tolerance specification.

In figure 5, the tolerance specification of a part is shown. These two limits determine how much deviations from nominal on a part can still be accepted. There are two phases shown in figure 5, design phase green line and verification phase brown line.