How Machine Learning Is Elevating Quality Control Standards
QA aims toward ensuring error-free goods, secure and efficient processes, and reduced material usage. Artificial intelligence (AI) technologies are increasingly assisting QA procedures, such as in terms of automation through closed-loop processes, evaluation of measurement data, and speeding of measuring operations. A panel of experts will address which AI systems are already in use in industry, which are already in existence, and what particular outcomes they are attaining in terms of efficiency and cost-effectiveness as part of the 2025 Control Quality Talks. In the framework of complete automation, it will also be investigated to what degree future AI systems will streamline quality assurance and open the door for error-free goods and procedures.
Distinguished Guests at the Expert Round Table:
Fraunhofer Institute for Manufacturing Engineering and Automation
„The aim of implementing AI should be to create real benefits and to integrate these into the CAQ system in a robust manner that simplifies the daily work of the software users – the focus must be on achieving the necessary maturity for real industrial added value for the masses. I am looking forward to the discussion. “
“AI can be put to good use in measuring technology, for example in order to support equipment operators via chatbots. A further example involves the intelligent optimisation of image quality in image processing or X-ray computer tomography. However, it’s very important to ensure that traceability of measurement results is not jeopardised as a result. AI must not alter measurement results. Utmost care is essential during project development.”
‘With AI, we can enable new applications and rethink workflows in measurement technology!’
„The use of artificial intelligence opens up a new dimension in quality assurance. in quality assurance. AI can be used to automate and objectify a large number of testing tasks that previously had to be carried out manually. But it can also be used as an assistance system for recording measurement data, planning measurement sequences or the virtual configuration of optical measurement and inspection systems, AI-based solutions also offer considerable potential for efficient quality assurance. “
„As developers, but also users, of AI-based quality assurance and assessment methods, we know both the challenges,
but also the enormous potential and benefits of these AI tools for our workflows. “
Exhibitors, expert visitors and guests will be able to gain extensive background information and further inspiration from this dialogue, because AI is clearly one of the key technology trends in quality assurance.
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