Today's blog deals with the question what role quality assurance (QA) and especially metrology will play in the digital factory. What is changing as a result of digitalization and which technologies will be in demand in the future? - Prof. Dr. Heiko Wenzel-Schinzer, CDO of the WENZEL Group gives the answer.

Of course metrology will also play a major role in the digital factory. Probably it is 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 set new challenges for metrology, as the testing of random samples is often no longer sufficient. Metrology solutions are ideally suited to ensure process stability in addition to product testing and compliance with tolerance limits.

Metrology as part of QA will establish itself as a partner of production, not as its controller. This has been the wish for a long time, but it is certainly not reality everywhere. If metrology is established directly on the shop floor, existing process and organizational limits will disappear, which will improve the direct dialogue between production and QA. Metrology provides early and thus directly applicable information and thus reduces "wrong and right" rejects.

Digitization is THE driver of change, since technical innovations only make the outlined possibilities possible and on the other hand require a radical rethinking. Digitization increases customer individualization, thus reducing batch sizes and thus often makes the subsequent inspection of individual parts as random samples meaningless. More flexible production facilities - e.g. the flexible booking of current orders to currently free capacities - require more flexible measurement solutions. Measuring programs must be created in such a way that they can be quickly transported to other machines and, if necessary, adapted without risking the comparability of the measuring results.

Of course, new technologies such as optical sensors or computed tomography solutions also provide new impulses in measurement technology. Whereas "in the past" it was primarily a matter of identifying the relevant pain points of a component for further processing, now gigantic amounts of data can first be collected and then processed as required. The task is soon no longer to find and measure points, but to find the right, relevant parameters from the measured, huge amounts of data and, above all, to interpret them. And here, the new possibilities - AI and machine learning - will play an essential role in the future. We see these technologies as a "find machine" for the measurement technician. If the technology identifies and selects outliers and possible problems, the measurement technician can concentrate on analysis, interpretation and feedback.

Sincerely yours,
Prof. Dr. Heiko Wenzel-Schinzer, CDO