Predge and Schweizerische Südostbahn AG collaborate in a strategic digitalization effort
Predge AB and Schweizerische Südostbahn AG (SOB) have started a collaboration to jointly assess the needs, practices and challenges for data driven maintenance of railway infrastructure. Predge is currently developing an operational predictive decision support for track geometry using a digital platform and provisioned as SaaS. SOB is at the same time assessing their needs and practices for the maintenance of linear assets to understand the needed capabilities of a solution integrating multiple data sources like measurement vehicles, on-board-monitoring, reference data, and maintenance actions. The collaboration will therefore enable an in-depth exchange of knowledge and experiences in the maintenance of linear assets and predictive decision support.
Safety and efficiency of a transport system for both freight and personal travel depend on high quality and availability of tracks. With the increased desire of policy makers to use railway infrastructure for transport, understanding track conditions and their evolution in the future become essential and an optimized approach to operation and maintenance need to be in place. The ongoing digitalization in the railway sector is an enabling factor for the integration of data for advanced predictive decision making and the optimization of maintenance actions in both time and place.
Development based on research conducted within JVTC
Predge offers a digital platform for fully automated or user-driven decision making, integrating multiple data sources for timely prescription of actions to be taken in the field. The ongoing development is based on research conducted within JVTC*. Data from measurement vehicles, on-board monitoring devices, reference data from the field, historic and planned maintenance action, and traffic information (historic and scheduled) will be used by the analytics and AI algorithms. These algorithms are developed using a combination of state-of-the-art machine learning methods and domain knowledge.
“We are proud and humbled to be part of SOB’s digitalization journey. We are convinced that Predge’s experience and knowledge in analyzing and predicting linear asset degradation, together with SOB’s deep know-how and understanding of track maintenance, will affect the efficiency and costs, and thereby strengthen SOB’s business. The results achieved so far are above expectations. We look forward to a long-term and continued rewarding collaboration with SOB.”, Says Bengt Jonsson, CEO at Predge.
During the collaboration Predge and SOB will assess the analytics results for maintenance of railway infrastructure in relation to field observations and expert knowledge to understand the quality of the analytics and to identify the remaining challenges to provide an online decision support tool. Predge and SOB will therefore work tightly together during the collaboration.
“We are glad to have found a technology partner experienced in predictive maintenance, who shares its data science experience in exchange for our practical understanding. A productive collaboration is somenting we´re looking forward to. We hope it will foster our Onboard Monitoring activities and bring new results to the world of railway in Switzerland, and eventually even further.”, says Daniel Siegenthaler, Head of Technology and Maintenance at Schweizerische Südostbahn AG (SOB).
* Luleå Railway Research Centre (JVTC) is a nonprofit research center within Luleå University of Technology (LTU) with focus on development of operation and maintenance within the railway sector.