The new module of the TeamViewer IoT software analyses big data and learns independently
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 an intelligent extension in the area of predictive maintenance is being added. This helps to reduce downtimes in particular and thus save costs.
In the past, machines were only repaired if they had already failed (Reactive Maintenance). For some time now, machines have been serviced in a fixed cycle, regardless of whether they are defective or not (preventive maintenance). And only recently has predictive maintenance been used, mostly on the basis of pure data sets with fixed rules.
TeamViewer goes a decisive step further here and offers AI-supported analysis of the resulting data. Machine learning algorithms can thus be used to detect previously unknown patterns and to diagnose impending machine failures at an early stage. The need to detect impending failures is obvious: every hour of unplanned downtime costs an average of $250,000.
Anonymised machine data
TeamViewer Vice President IoT Lukas Baur said the company’s goal is to build a unique library of anonymised machine data and thus provide each customer of Predictive Maintenance module with access to already existing knowledge.
“Our customers can reduce their downtime from day one, and with each additional day the algorithm learns to better estimate specific parameters, making predictive maintenance even more accurate. The maintenance department is responsible for up to 60 percent of operational expenditure. Our ambition is to reduce this cost item through an AI-based analysis of the device data,” explains TeamViewer Vice President IoT Lukas Baur
The new software module ML-Trainer supplies the machine learning algorithm with data that might have triggered alarms and learns to recognize specific patterns. As a result, alarms are no longer bound to rigid thresholds, but are subject to constantly optimized criteria. The downtimes, but also false alarms, can be significantly reduced in this way, and in the long term, because the artificial intelligence is constantly learning.
The TeamViewer predictive maintenance module can be easily integrated into existing TeamViewer IoT environments. The algorithm can already access sample data sets generated specifically for this module for various machine types, such as wind turbines and pumps, and only needs to learn about the characteristics of the respective machine.
TeamViewer making impact
TeamViewer is a leading global technology company that provides a connectivity platform to remotely access, control, manage, monitor, and repair devices of any kind – from laptops and mobile phones to industrial machines and robots.
Although TeamViewer is free of charge for private use, it has more than 500,000 subscribers and enables companies of all sizes and from all industries to digitalize their business-critical processes through seamless connectivity. Against the backdrop of global megatrends like device proliferation, automation and new work, TeamViewer proactively shapes digital transformation and continuously innovates in the fields of Augmented Reality, Internet of Things or Artificial Intelligence.
Since the company’s foundation in 2005, TeamViewer’s software has been installed on more than 2.2 billion devices around the world. The company is headquartered in Goppingen, Germany, and employs more than 1,000 people globally. In 2019, TeamViewer achieved billings of around EUR 325 million. TeamViewer AG (TMV) is listed at Frankfurt Stock Exchange and belongs to the MDAX.