TECNALIA works in conjunction with ZEUKO on a solution for predicting cracks and failures in STS port cranes

5 March 2021
Zeuko y TECNALIA mantenimiento predictivo grúas STS

TECNALIA reduces the risk of accidents and achieves greater efficiency through predictive maintenance. 

Zeuko, a company that specialises in port cranes, industrial cranes, lifting systems and special machinery, is developing a solution with TECNALIA for detecting, monitoring and predicting cracks and structural failures in STS port cranes.

The project, which is geared towards predictive maintenance, increases safety for people and the entire environment where cranes operate, reducing the risk of accidents caused by structural fatigue and minimising the need for periodic inspections. At the same time, it makes these assets more efficient through predictive maintenance that improves their availability, avoids costs due to unplanned breakdowns, and prolongs their life.

Zeuko seeks to respond to an unresolved need in these types of cranes, which are used for loading and unloading containers in ports in increasingly demanding conditions. This demand, coupled with their long life and the repetitive tasks they perform, entails a fatigue that will in turn result in increasing breakdowns as it spreads to internal structures and components.

In order to create a predictive maintenance tool for these structures that can detect and prevent damage, and to validate its effectiveness in relevant operating environments through a prototype, TECNALIA focused on understanding their state of health.

Monitoring technologies, and diagnostic and prognostic services

There are two parts to the solution: the crane-side elements that enable data collection, pre-processing using artificial intelligence and sending, and a virtual environment where the information is processed and fault prognosis and diagnosis services are integrated.

During the technical development phase, TECNALIA analysed different monitoring technologies for locating failures, defined the methodology, and selected the critical areas, locations for sensor, and the structural failure modes. TECNALIA also applied machine learning techniques to the data collected to develop diagnostic and prognostic services capable of detecting and predicting failures, and integrate all developments onto a predictive maintenance platform.

TECNALIA provided its technological capacity and knowledge of innovation processes in the industrial field, thereby making a decisive contribution to the conceptual dimension of the project and the architecture of the solution.

Further information

The Zeuko team brought its specialisation in these structures to this project, together with its extensive experience of port cranes. It established an analysis methodology to identify the critical areas of cranes that can be monitored based on the breakdown of multiple factors related to the probability, detectability and severity of failures.

The development of this predictive maintenance tool for STS and shipyard port cranes is a very ambitious challenge. It involves comprehensively analysing structures, combining instrumentation technologies, advanced analytics, artificial intelligence-based models and software modules.

The new solution will allow Zeuko to respond to the needs of the market, creating a specific new maintenance line that will boost its business and consolidate its internationalisation.