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VW Slovakia Optimizes Factory Vehicle Movement With RTLS

The solution, provided by Sewio, employs CEIT software and Decawave's RTLS tags and receivers to track the movement of each production vehicle, in order to manage how traffic flows in a complex and fluid assembly process.
By Claire Swedberg
Oct 21, 2018

Automotive company Volkswagen (VW) Slovakia has brought visibility and intelligence to its assembly site by deploying a real-time location system (RTLS) that enables it to understand the movements of forklifts and other manufacturing vehicles, and thereby better utilize its space and ensure safety. The solution, which was taken live in 2017, was provided by RTLS technology company Sewio, using Decawave ultra-wideband (UWB) technology to capture location data, as well as CEIT software to manage the data for real-time location and business analytics.

That data enables Volkswagen Slovakia not only to ensure the safety of production traffic in real time, but to plan future production for building-specific vehicles based on traffic-flow data. In the long term, VW Slovakia intends to create digital twins for each vehicle-manufacture process, based on the movements of three different kinds of onsite vehicles that transport goods around the plant for each assembly process.

VW Slovakia, located in Bratislava and owned by the Volkswagen Group, produced 360,000 cars at its 1.7 million-square-meter facility in 2017. The facility builds not only a large volume of vehicles, but also numerous models, ranging from SUVs to compact cars, at a single location. Beyond Volkswagen models, it also makes Audis, Porsches and Skodas, for instance. Adding complications, as much as 30 percent of the assembly warehouse area is variable, meaning any specific area could be transformed from an empty space to one that is fully blocked to vehicular traffic within a timeframe of just a few hours.

The factory required a solution that could enable it to identify traffic bottlenecks, as well as reconfigure or plan for future projects accordingly. Additionally, given the number of moving vehicles (both manually and automatically driven), the system had to be able to identify each vehicle within high-traffic density, and to measure when vehicles come within close proximity of each other.

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