INDUSTRY 4.0
without compromising security in the IT environment. Within its Industrial Internet of Tings
(IIoT) research, Siemens is focusing firstly on connectivity, addressing topics such as 5G, as well as interoperability through OPC UA; secondly, the field of edge computing and device and system management; and thirdly, perception, which includes all the sensing activities, sensor data fusion, smart sensing and also the quality of sensing data. Kegel made the distinction between
a measurement value – the kind plant machinery might at the moment collect – and data. Te difference is that data has context. A measurement value might not even have a timestamp, so once that number is processed in the control circuit, it’s useless. ‘Te minimum that you need to turn a measurement into data is a timestamp,’ Kegel said. ‘You need context information,’ he
continued. ‘Data is not valuable if you can’t understand it in the context of its environment. Tis context-relevant information has to accompany the data, otherwise they are pretty useless.’ Kegel said that putting context around
a primary device, such as an IoT sensor, requires a lot of standardisation work. ‘All these different IoT partners have to talk to each other,’ he said. ‘It requires more than just another fieldbus protocol; it really requires a semantic work ontology on top of this that is standardised.’ Te VDMA, ZVEI and Bitkom, along
with 20 partner companies, have formed an industrial twin association to help bring about standards. Te aim is to advance Industry 4.0 through the development of an open source digital twin, which will function as an interface between physical industrial products and the digital
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‘We are in the eye of the storm – the sensing side. Actuator networks are already available, but the sensing side is not developed as far as we thought’
aspects of Industry 4.0 applications. ‘In all honesty, automation people don’t know anything about semantics and ontologies, they have to learn this from the beginning,’ Kegel said. He said there’s plenty of technology available to create standards in these areas, and only with new standards will vendors that speak different languages be able to talk to each other on the level of data. ‘Tat, for me, is the biggest challenge the industry is facing: how can we actually get our arms around this international standard and do this very abstract new way of standardisation,’ he said. Who is best placed to do this
standardisation activity, Kegel asked? He said automation experts are stepping into new territories, and there are already standardisation bodies in these areas doing good work. ‘Tere’s still a tremendous amount of work to do, but there’s no shortcut, we need to do this standardisation,’ he added. In the DFKI article, Professor Wahlster
said: ‘AI is spearheading a second wave of digital manufacturing’, a point Dumitresco at It’s OWL made during the EMVA discussion. AI is needed to make sense of the huge amounts of data now available in manufacturing. Dumitresco also said that digital twins are helping to structure data according to
specific information sets. Scheiter agreed, saying that a digital twin is needed to solve complex tasks when setting up Industry 4.0 processes. He said: ‘We need [sensing] methods that ensure context plays an important role. Tat’s good news for imaging [and] good news for the industry, because that’s how we can bring in our [sensing] domain knowledge.’ Scheiter also said that business
innovations – companies working together in a cooperative way on a joint ecosystem – might be more important than advances in technology, although there’s still some way to go on this. Gaia-X is one project bringing
representatives together, in this case to build a European data infrastructure. Te goal is to create a secure, federated system that meets high standards of digital sovereignty while promoting innovation. Te project hopes to make an open, transparent digital ecosystem, where data and services can be made available, collated and shared. Kegel concluded that there are two
transformations happening: digitalisation and sustainability, which go hand-in-hand, as digital technologies are required for more sustainable manufacturing practices. ‘As a sensor provider, I’m confident that
we need not only Industry 4.0, but also Sensors 4.0, because the next generation of sensors – better integrated with better context information and everything integrated in a digital twin approach – is a game changer,’ he said. ‘I don’t think we need more disruptive
technology at the moment,’ he added. ‘We have so many things to do in the coming years to digitise [manufacturing] completely and to contribute to decarbonisation. If we really manage these two major trends in the future, we’ve done a good job.’ O
VISION YEARBOOK 2021/22 IMAGING AND MACHINE VISION EUROPE 7
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