The University of Bremen has developed an AI-supported status monitoring system for port vehicles together with Hamburger Hafen und Logistik AG (HHLA) Container Terminal Tollerort GmbH.
The joint research project ‘AI-Based Damage and Wear Detection System for Cloud-Based Condition Monitoring of Hybrid Container Vehicles’ is funded by the German Federal Ministry for Economic Affairs and Climate Protection (BMWK).
The condition monitoring system was developed jointly by the industrial partners ANEDO GmbH, Kessler & CO GmbH & Co. KG, SEGNO Industrie Automation GmbH, HHLA Container Terminal Tollerort GmbH, and the ITEM research institute (Institute for Theoretical Electrical Engineering and Microelectronics – Applied Electronics and Software Systems department) at the University of Bremen.
The system uses modern technologies such as edge computing, the Internet of Things (IoT), data analysis, and machine learning to monitor the technical condition of straddle carriers in real time and take preventive maintenance measures.
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According to HHLA, this condition-monitoring solution for mobile machinery offers several benefits. These include continuous monitoring for early fault detection, predictive maintenance, efficient resource use, improved safety, and reduced costs.
“Thousands of containers are moved between the various transport modes in the Port of Hamburg every day,” explained Thomas Sauck, Head of the Ground Handling Equipment department at Hamburger Hafen und Logistik AG’s (HHLA) Tollerort Terminal.
“The efficiency of these handling processes is a top priority for HHLA. This is why we use the most advanced technology for the maintenance and servicing of our equipment to ensure smooth and efficient operations.”
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“The introduction of advanced condition monitoring technologies for our wheel drives in the straddle carrier is an important step towards optimizing the use of our products and increasing customer satisfaction,” said Daniel Oltmanns, Software Manager at Kessler & Co.
