Digitisation of measurement and metrology

Digital transformation is everywhere, including in metrology. Not only does metrology play a role in the digitization of many processes in industry and society, metrology itself is also digitizing.


The importance of metrology in digitisation

The rapid advancement of digital technologies is having a major impact on society. More and more measurement systems and measuring instruments are producing smart data. Added to that, many industries – from energy to healthcare – are experimenting with AI solutions. Artificial Intelligence makes it possible to process large amounts of data and create predictive models from which important conclusions can be drawn.

It is therefore crucial for measurements to be accurate and data to be interpreted properly. The data structure and AI itself need to work to certain quality standards. This is where metrology plays an important role. In the transition from the old situation to the new digitised one, measurements must be just as reliable and traceable, or even more so, so that everyone can rely on their results.

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Erik van de Graaf
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The digitisation of metrology

In addition to the digitisation of processes and systems, metrology itself is also digitising. For example, digital innovations enable us to make much more accurate measurements. At the same time, AI makes automatic self-calibration possible, while the increased use of sensors impacts metrological traceability.

This requires metrology to be adapted to the digital age. Consider, for example, the extension or redefinition of units of the SI system. Since 2022, there have been scientific terms for numbers that denote the largest values (ronna, quetta) as well as the smallest ones (ronto, quecto) in existence.

Measurement challenges in times of digitisation

The use of advanced algorithms, artificial intelligence and other innovative technologies is having a major impact on measurement methods and instrument calibration. To maximise the benefits of new techniques, we must be able to rely on the data and models from which they are derived. The requirements for data to be considered reliable are becoming more stringent. However, analysing large streams of data and drawing the right conclusions from them also presents challenges. We work with fellow institutes, knowledge institutions and industry to find the right solutions.

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How VSL can help

A lot can go wrong when integrating digital technologies into processes, systems or facilities. For example, the vast quantity of data generated every day requires proper implementation and interpretation. VSL removes obstacles by ensuring the reliability and traceability of measurements and measuring equipment. We can also help ensure that measurement data are analysed and interpreted correctly.

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