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���ϲ����� is developing a cutting-edge data integration tool for real-time vehicle performance assessment. The concept called Digital Twin is based on linked data, and it will take predictive maintenance to the next level.

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These days, ���ϲ����� collects an immense amount of data. And not only data from connected vehicles but also from its manufacturing operations. In fact, the information that ���ϲ����� collects doubles in size every two years.

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All of this information is invaluable when analysing performance and quality in designing even better vehicles, but it falls short when assessing performance in real time. ���ϲ�����’s response to that problem is to adopt cutting-edge data integration technology.

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How data integration technology works

The technology is not unlike that which we use every day when we are entering terms into internet search engines. Countless information is identified, correlated and linked in milliseconds before being presented to the user as results.

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In this context, data concepts need to be named and defined, with their relationship to each other established. For example, brakes would consist of several data concepts that together constitute the term ‘brakes’. These concepts are collected in ‘knowledge graphs’, which are the realm of inter-related data concepts.

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Stefan Telhammar, Integration Services, ���ϲ����� IT, uses a simple metaphor to explain the idea further.

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“It could be compared to a Formula 1 race,” he says. “The team has ample data on past performance but it needs to make qualified decisions during the race to determine the best times for pitstops.”