To implement the structural transformation in the coal regions, extensive construction measures are necessary in the affected regions. As part of the Off-Highway-Twins-2 project, individual construction measures are being monitored over a period of three years. It will be investigated whether and how the numerous data sources available at modern construction sites can be used to implement the individual measures as efficiently as possible.
The goal of the Off-Highway-Twins-2 project is to fuse available machine and geodata into digital twins of infrastructure objects and mobile working machines. With the help of these digital twins, environmental and operational data are derived and transferred to cloud data services for acquisition, planning, construction, operation and maintenance.
Problem definition, need for innovation
The work associated with the life cycle of infrastructure objects requires a reliable data basis. Public authorities provide a wide range of (geo)data for this purpose. The challenge is to develop suitable additional data sources in order to raise the quality of official data (actuality, area coverage, detail, accuracy, semantics) to a qualitative level that can be used for work processes in the acquisition, planning, construction, operation and maintenance of infrastructure objects.
Project objective (incl. data reference, innovations)
By fusing (geo)data from the cloud with sensor and telemetry data from machines, current, area-wide, detailed, accurate, semantic models of infrastructure objects and their surroundings - the off-highway twins - are to be derived in real time by means of modeling, sensor data fusion and artificial intelligence, kept up-to-date over the entire life cycle of the corresponding infrastructure objects and integrated into established and new work processes.
Implementation (central activities)
Based on an analysis of various application scenarios from the construction and municipal sectors, off-highway twins are specified, made available via an IoT infrastructure and made usable by means of CDE integration. Edge components and cloud services fuse sensor data and cloud (geo) data into information about infrastructure objects and their surroundings. The result will be evaluated in 4 pilot projects.
Expected results and impacts
The information provided via Off-Highway Twins creates transparency about the (transport) infrastructure of entire regions over the entire life cycle. Optimal planning, early fault detection and targeted maintenance reduce time and costs and increase the quality of our infrastructure - with reduced energy use and emissions. This also applies in particular to less developed areas such as the lignite mining regions.
Subject matter of FLUIDON's work
In cooperation with ifas, FLUIDON realizes real-time capable digital twins of the considered working machines in order to close the information and data gap that exists due to the lack of sensors. For this purpose, realistic simulation models of the machine are implemented and, in the further course, fed with the available control and measurement signals from the control system in parallel to the operation of the machine. In order to meet the requirements of the digital twins in terms of performance, availability and connectivity (both to the machine controller and to other cloud applications), they are integrated into the FLUIDON | Cube simulation environment. In this way, all other state variables for construction process planning and control can be provided directly by the digital twin.
Three institutes of RWTH Aachen University and five companies from the region have joined forces to carry out Off-Highway-Twins-2.
- Institut für fluidtechnische Antriebe und Systeme (ifas)
- Institut für Mensch-Maschine-Interaktion (MMI)
- Institut für Baumanagement, Digitales Bauen und Robotik im Bauwesen (ICoM)
- STRABAG AG
- albert.Ing GmbH
- FLUIDON Gesellschaft für Fluidtechnik mbH
- Meastream GmbH
- IQstruct Engineering GmbH