Artificial Intelligence, Machine Learning & Predictive Maintenance
Predictive maintenance is a major focus theme at the upcoming HANNOVER MESSE 2020. Many of the show’s exhibitors are providers of AI-powered software solutions that predict faults and prevent costly unplanned shutdowns in connected manufacturing plants and systems.
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Predictive maintenance is a major focus theme at the upcoming HANNOVER MESSE 2020. Many of the show's exhibitors are providers of AI-powered software solutions that predict faults and prevent costly unplanned shutdowns in connected manufacturing plants and systems.
"Every minute of every hour that a production line or facility is shut down owing to technical problems is a major cost burden. That's where AI-based predictive maintenance comes into play," explained Hubertus von Monschaw, Deutsche Messe's Global Director Digital Ecosystems for HANNOVER MESSE. "If the machines in question are able to talk to one another and exchange data with one another, then potential problems can be detected relatively quickly by running background AI-based software that is able to identify anomalies and other normally unforeseeable faults. The key is that the problems and anomalies are detected as early on as possible so as to avoid outages."
But that's not all. Predictive maintenance is also a very useful way of interconnecting digital value chains. Once the predictive maintenance system knows the exact point in the future at which a particular machine will need to be shut down for maintenance, it can, for instance, automatically initiate the associated logistics processes. This ensures that all the relevant work and parts ordering processes are properly coordinated.
A good example of this is Datawatch, which Altair Engineering will be showcasing in Hall 17. Datawatch can be integrated into existing infrastructure and addresses predictive maintenance in three steps: data preparation, generation of data models, and real-time prediction. The platform brings together users with diverse skills and backgrounds from diverse disciplines. Another example is Data Lighthouse, a Hamburg-based software development company that will be presenting an array of innovations in Hall 16. Data Lighthouse will show how industrial firms can leverage its cloud-based Data Grid solution to monitor their production plants in real time and predict their behavior. The solution uses digital twinning and mobile end devices to enable users to continuously monitor the condition of their production facilities. And last but not least, Saarbrücken-based consulting and software firm Scheer GmbH will be presenting a lineup of AI-based solutions in Hall 17. Among them will be Predictive Intelligence, a software application powered by self-learning algorithms. The application enables users to reduce production rejects, predictively plan maintenance runs and reduce plant energy consumption.
In a very real sense, predictive maintenance goes hand-in-hand with machine learning because in order to be able to reliably detect potential faults, a predictive maintenance system needs to have prior knowledge of all possible fault situations. By "teaching" the maintenance system about all the various possible fault situations, AI-based machine learning software enables it to detect specific faults in real-time and initiate remedial action. HANNOVER MESSE 2020 will therefore have a very strong focus on machine learning.
A1 Digital Deutschland , for example, will be using its stand in Hall 15 to profile its offering as the partner of choice for AI projects. Visitors to the stand will be able to discuss their planned applications with A1 Digital's AI specialists and gain a better understanding of their machine learning and AI requirements. Chip maker Intel will also be in Hall 15 (Stand E76), where it will be presenting its solutions for machine learning, focusing on technologies like Intel® DL Boost for AI and edge computing. These technologies revolve around storing AI-relevant data on end devices – embedded IoT components, smartphones, tablets etc. This accelerates data exchange between AI systems and end devices.
Also highly relevant in this regard is the Hall 16 showcase of UK-based technology firm Senseye . With its Senseye cloud and machine learning-based software, users can automatically predict machine outages and take countermeasures. The software can be used on any machine. For example, Siemens has implemented Senseye in its Mindsphere IoT operating system. Senseye uses integrated sensors to connect and monitor plants and systems.
A key hub for information and expertise on predictive maintenance at HANNOVER MESSE is the Predictive Maintenance group pavilion in Hall 16. The pavilion will feature displays by multiple providers, including softgate , Neuron Soundware , FuehlerSysteme eNET International , Treon , SensiML , Shiratech Solutions , Zeppelin Power Systems and BIBA (Bremen Institute for Production und Logistics) .
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