The 5R Network, Cervera network in Robotic technologies for intelligent manufacturing, has as its mission to establish a collaborative network, equipped with the necessary technology, tools and infrastructures to act as a driving force for the development and introduction of new robotic technologies in the industrial fabric.
The 5R network was born from the decision of the technology centers that make it up to create a common synergistic project that allows strengthening their capacities and generating applied knowledge in order to increase the competitiveness of the Spanish business sector and position itself as an international benchmark in this field.
The strategic plan of the 5R network is based on the development of five Pilot Factories in which different demonstrators created from robotic technologies are deployed.
- Develop a scientific-technical strengthening plan for the participating centers to position ourselves as the benchmark R&D network in the development and application of robotic technologies in perception, interaction and cognition for smart manufacturing.
- Promote the introduction in the manufacturing sector of new paradigms of flexible and collaborative robotics supported by artificial intelligence.
- Increase business technology transfer and accelerate technological innovation.
- Improve the capacities of the Spanish industry in relation to robotic technologies.
- Have results validation environments that can be translated into high-level publications.
- Facilitate participation in international consortia.
- Engaging relevant stakeholders to create and convey a positive vision of robotics technology.
- Bringing robotic technologies closer to society, not creating false expectations and demonstrating the possibilities they offer.
- Technology development in multisectorial validation scenarios.
- Realistic infrastructures to experiment and validate developments and solutions of the industrial fabric.
- Offer the educational community technologies and solutions in the field of robotics.
- Offer the scientific community the possibility of validating theories and concepts in industrial settings.
- Facilitate the work of the media to disseminate advances in the field of robotics.
- Differentiating infrastructures that facilitate participation in international programs.
Cervera Technology Centers 2020
“Cervera Centre of Excellence”
CARTIF total budget: 780,925 €
CARTIF Grant: 780,925 €
Duration: january 2021 – december 2023
Roberto Medina Aparicio
Divison of Industrial and Digital Systems
Industrial solutions projects:
DAMPERDOOR looks to develop a competitive system and of high benefits for sliding doors in furniture sector. These features aim for a self-controlled closure, independent of the excessive force that a user may bring to the closing action, thus avoiding shocks and with the ability to complete the travel to a full and accurate closure.
“Intelligent Visual Computing for products/processes in the agri-food sector” is an industrial research project framed in the field of computer vision (digital enabler of Industry 4.0) associated with the agrifood sector.
The Intrusion-G4 project seeks new technologies to overcome the challenge of increasing the degree of security of the intrusion detection sensors currently available on the market.
The TRREX project (Extended Range Robot Enabling Technologies for the Flexible Factory) investigates and develops technologies that contribute to the deployment of mobile industrial robots for the factories of the future. These systems will increase the flexibility of the plants and allow the optimization of industrial processes, improving their productivity.
NUMASTA allows the development of a new generation of FRP sandwich panels for its application in the wastewater treatment sector. The distinguishing characteristic is presented in its core, based on a polyurethane foam, manufactured using formulations designed “à la carte” through a manufacturing process in a single stage where the curing process of the leathers and the foaming of the core take place in a synchronous
i-Visart, “New artificial vision methodologies for the visual inspection of highly reflective and textured surfaces”.
It is an industrial research project framed in the field of computer vision (digital enabler of industry 4.0) associated with the industrial sector.
CARTIF, has designed and developed a new module based on AR for smart glasses based on the recognition of QR markers to launch the experiences of AR, particularized for three technological pilots: Risk identification, Management of machine maintenance and Machine status monitoring
A new intelligent system has been developed for manual assembly positions in the industry. This system aims to minimize assembly errors by operators by validating operations, providing information and guiding the operator in real time through a man-machine interface based on Augmented Reality
Nowadays in hot and cold lamination of “long” elements only the detection of punctual defects are made, not longitudinal defects. Therefore, the technological leap and the differentiating key of future products is to detect both, punctual and longitudinal defects on the production of flat steel in the rolling process, either the cold or hot process.
MARCA provides the maintenance operator with tools that facilitate access to content, communications and technologies necessary for the guidance, support and registration of maintenance work. It is based on technologies of augmented reality, mobility and communication, as well as a knowledge base for incident management.
INCEPTION develops new methods and tools for automated 3D modelling and analysis of European cultural assets proposing advancements on hardware and software, as well as new approaches for Cultural Heritage 3D data inclusive access and exploitation by means of the so called INCEPTION-Platform.
The aim of MODINTECO project is to develop prototypes of Automatic Tool Changers for milling machines, modular and adaptable, intelligent and autonomous, universal..
The purpose of the CALYPSO project is that the inspection process can be enriched by automatic pattern recognition techniques.