“TeamViewer” announced the new model “TeamViewer IoT” software that analyzes “big data” and learns independently, thus expanding the “IoT” solutions and offering a way to use artificial intelligence in maintenance.
Until now, “TeamViewer” customers in the “IoT” field have been able to read sensors, set alarms, and connect directly to a wide range of devices. Now a smart extension in the field of maintenance forecasting is added. This helps to reduce downtime and therefore cost savings.
In the past, machines have been repaired after they have been damaged (Reactive Maintenance). For some time now, the machines have been maintained in a constant cycle, regardless of whether they are defective or not (preventive maintenance). Only recently has forecasting been used, mainly based on clean data sets with fixed rules.
“TeamViewer” goes a step further and offers “AI-supported” analysis for the resulting data; machine learning algorithms can thus be used to identify previously unknown patterns and diagnose impending machine failures at an early stage. The need to spot impending failures is obvious: every hour of unplanned downtime costs an average of $250,000.
“Our goal is to create a unique library of anonymous machine data and thus provide each customer with a “Maintenance Forecast” library with access to existing knowledge. Our customers can reduce their downtime from day one, and with each additional day the algorithm learns to improve by calculating specific parameters, making predictable maintenance even more accurate. The maintenance department is responsible for up to 60 percent of operating costs. Our ambition is to reduce this cost element by analyzing the data of the “AI”-based device“,
explains Lukas Baur, Vice President “IoT” of “TeamViewer”.
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