The central topics of the industry have rarely been so clearly defined: artificial intelligence, machine learning and digitalization. How the resulting developments and upheavals will change the most important export markets of the industry and what potentials they offer will be highlighted together with Thilo Brodtmann, managing director of the German engineering union named VDMA, and Achim Baier, CEO of Arconsis IT Solutions. As a distributer for used TRUMPF punching machines, press brakes and laser cutting systems, we, the I-H&S GmbH want to provide you with the most relevant information of today’s industry – today, we’ll take a closer look at the potential of ML.
Application bandwidth leads to opportunities for machine learning
Thilo Brodtmann reports on an enormous range of applications for machine and plant construction, which naturally play a major role for many different technologies. “Technology is certainly outstanding in the context of digitization. Here, the machine operators as suppliers and users of industry 4.0 technologies are in a key position. Also promising is machine learning as a part of artificial intelligence. In the past, spectacular breakthroughs have been achieved, and the implementation of machine learning in machine and plant construction is a disruption that can lead to major changes”, Brodtmann says. The result: machine learning fosters the future of company profits – a good reason for mechanical engineers to deal with it.
Machine learning as a catalyst for innovation
Since Industry 4.0 has now occupied a place in our heads for quite some time, the question arises as to why it needs to be observed in detail now. It’s a fact that ML research and related algorithms have reached an upgraded level which makes it possible to run even very complex AI problems on existing hardware. “The technological advances in the development of CPUs and GPUs, the immense performance of networking systems and the availability of computing power at all locations, at any time, whether in the cloud, on mobile devices or in IoT environments with embedded systems, enable the use of machine learning” Achim Baier, CEO of Arconsis IT Solutions, says. According to Baier, concepts, standards and best practice cases – created by IT giants and universities – put the icing on the cake and enable their integration into their own solution chains. In addition, those insights are increasingly enriched by information gathered in the context of Big Data initiatives.
Especially as a catalyst for innovation, ML reveals enormous potential. Machines are constantly collecting unmanageable data which often reveal untold treasures of knowledge. Automatic analysis and learning processes provide information ultimately leading to an improvement of existing and future tools, processes and procedures.