Of course, metrology will also play a major role in the digital factory. It is probably even more important than before. The reduction of batch sizes, the individualisation of products and the use of innovative manufacturing processes such as additive manufacturing pose new challenges to the metrology, as the inspection of random samples is often no longer sufficient. The metrology solutions are excellently suited to ensure process stability in addition to product inspection and compliance with tolerance limits.
The metrology as part of QS will establish itself as a partner of production, not as its controller. This has been the wish for a long time, but certainly not the reality everywhere. If the metrology is established directly on the shop floor, existing process and organisational boundaries will disappear, which will improve the direct dialogue between production and QA. The metrology provides early and thus directly implementable information and thus reduces "wrong and right" rejects.
Digitalisation is THE driver of change, as the technical innovations make the outlined possibilities possible in the first place and, on the other hand, also require radical rethinking. Digitalisation increases customer individualisation, thus reducing batch sizes and often making the subsequent testing of individual parts as random samples pointless. More flexible production facilities - e.g. flexible booking of current orders to currently free capacities - require more flexible measuring solutions. Measuring programmes must be created in such a way that they can be quickly transported to other machines and adapted if necessary without jeopardising the comparability of the measuring results.
Of course, new technologies such as optical sensors or computer tomography solutions also provide new impulses in metrology. Whereas "in the past" it was mainly a matter of identifying the relevant pain points of a component for further processing, gigantic amounts of data can now first be collected and then processed at will. The art is soon no longer to find and measure points, but to find the correct, relevant parameters from the measured, huge amounts of data and, above all, to interpret them. And here, too, the new possibilities - AI and machine learning - will play an essential role in the future. We see these technologies as a "finding machine" for the measurement technician; if the technology identifies and selects outliers and potential problems, the measurement technician can concentrate on analysis, interpretation and feedback.
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