PREDISURF PROJECT
Currently, it is estimated that there is a defect rate of 20% in the production of galvanic processes. This type of surface treatment requires meticulous control and dosing of the necessary components and parameters. These issues are not easy to achieve for a single industrial coating company, even less so for an SME.
The main objective of the project is to develop a predictive digital tool for surface treatment processes in the industry. The aim is to build a predictive model of surface treatment lines based on mass and energy balances, and then integrate it into a virtual environment that constantly interacts with the physical environment.
The result will be continuous access to information on all process parameters, including those that are typically difficult to obtain, such as chemical composition. Additionally, the developed tools will be complemented by a computer vision package that correlates process conditions with the resulting surface treatments.
One of the project’s main achievements has been the development of a digital twin of the system—a virtual environment that accurately replicates the real plant’s physico-chemical conditions. This model enables real-time interaction with operational data, allowing for the simulation of chemical cycles and complex scenarios without interrupting production. Thanks to this tool, processes can be optimized before being physically implemented, reducing experimentation costs and minimizing mechanical risks. It also enables virtual validation of cycle programs and treatment times, providing valuable support to both the technical and chemical teams.
The integration of the digital twin with Industry 4.0 technologies has made it possible to monitor multiple process variables in real time, such as dwell times, energy and chemical consumption, pH, temperatures, or dosages, ensuring full traceability of production. This capability not only improves quality control but also lays the groundwork for predictive maintenance using artificial intelligence. All of these advancements have been incorporated into our software platform, strengthening our value proposition and delivering significant improvements in efficiency, resource consumption, and operational times.
The Predisurf project is led by Talento. Other companies, such as Surtech Engineering and Teknopar, as well as the CTME (Miranda de Ebro Technology Center) and CIDETEC, participate as subcontractors.
The Predisurf project has received funding from the Eurostars-3 Joint Program, with co-funding from the CDTI and the Horizon Europe Framework Program for Research and Innovation of the European Union.
