The role of AI in optimizing industrial production
The use of smart technologies like artificial intelligence, machine learning and virtual and augmented reality is already rather standard in many commercial settings, including eCommerce, gaming and healthcare. Now it's industry's turn to get smart. Manufacturers of industrial plant and solutions will be showcasing their smart technologies under the "Industrial Intelligence" banner at HANNOVER MESSE 2019.06 Dec. 2018
Hannover. "At this point in history, all businesses need to transform to survive." It's hard to find a more apt expression of the importance of Industry 4.0 than this frank statement by Cağlayan Arkan, General Manager, Manufacturing & Resources Industry at Microsoft. HANNOVER MESSE has been driving Industry 4.0 forward for many years, and in April 2019 will put the spotlight on several key aspects of it: artificial intelligence, machine learning, VR and AR. "The growing digital integration of production machinery and the development of smart system components are generating vast amounts of data which can now be used as the basis for the use of innovative technologies like machine learning, digital twinning, VR and AR," explains Arno Reich, Global Director Digital Factory for HANNOVER MESSE. "This April we will have many exhibitors who will be showcasing AI-based solutions."
One of the exhibitors in the AI space is Microsoft . "At Microsoft, we help manufacturers lead with digital to develop new capabilities that draw better insight out of data and convert it to intelligent action," says Arkan. "We empower scenarios such as intelligent supply chain, product-as-a-service, and factory of the future, building on what artificial intelligence, mixed reality, additive manufacturing, digital twins, blockchain and other advanced technologies have to offer today."
AI technologies – or, more precisely, machine learning and deep learning technologies – are rapidly making their way into factories in the manufacturing industry, where they are making short work of solutions which up until fairly recently were either technically or commercially unfeasible. An example of this is the recognition of patterns and correlations based on unstructured data, such as images, videos and sound, in combination with structured data from the machines in question. This kind of linking of data has the benefit of dramatically reducing the work involved in identifying faults and problems. Learning systems are thus destined to play a key role in driving continuous improvement in industrial manufacturing. There are, however, a few obstacles to overcome before that can happen. For one thing, it is often very difficult to get legacy IT systems and AI technologies to "play together nicely". This is partly because new AI-based technologies have very particular technical and organizational requirements, and partly because legacy IT systems are often outdated owing to years of underinvestment. "This 'two-speed IT' approach is often a major barrier to the introduction of AI systems, not to mention other innovations such as IoT and blockchain," says Ralf Bucksch, Technical Executive Watson IoT Europe at IBM . "That is why the IBM showcase at HANNOVER MESSE 2019 will deal with both aspects: the potential of these new technologies and the initial steps that need to be taken to realize that potential."
These views are shared by Rainer Glatz, director of the Electrical Automation and Software & Digitalization associations within the German Engineering Federation (VDMA) : "In many cases the use of AI in industrial settings is still in its infancy. Examples include predictive maintenance and a large number of other applications in production optimization, highly parameterized systems, intelligent industrial image processing and history-based vendor evaluation." Some may be in their early stages, but these technologies show that industry is continuing along its digital transformation trajectory. "Gone are the days when IT and software were used only as tools to support existing internal business processes. Increasingly, companies are using them as a basis for developing their own intelligent products and services and hence for futureproofing their businesses," explained Glatz.
With new AI technologies, as indeed with all technologies, it is important to get the cost-benefit ratio right. "Machine learning and VR/AR are already state-of-the-art on the cloud layer, but due to the big amount of data, most manufacturing scenarios need those technologies to run on the edge layer close to the machines in the shop floor," explains Dr. Cesim Demir, CTO, Automotive and Manufacturing Solutions Huawei West European OpenLab. "This means that the requirements for the edge layer are increasing with concurrent cost pressure for devices. The challenge is to define the balance between low equipment costs and provision of high functionality in terms of computing power on the edge devices. Many companies are investing into Digital Transformation and Industry 4.0 because of the expected benefits and not just for the sake of investment. We are focusing on those problem areas to provide the right solutions for our customers."
At HANNOVER MESSE 2019, displays of applications for Industry 4.0 and solutions for the cloud, industrial security, AI, machine learning, digital twins, VR, AR, and big data management will be clustered in halls 5, 6, 7 and 8 at the Digital Factory show.
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