AIMEN is a Non Profit association constituted by 110 companies, which supplies technological support to more than 400 companies dedicated to industrial or commercial activity related to metallurgy, automotive sector, civil construction, mechanics, shipbuilding, chemicals, foundry, machinery, ceramics, plastics, engineering, assembly and others. AIMEN promotes and undertakes research, as well as improves design, simulation and manufacturing technologies. Located in the Northwest of Spain, AIMEN is a highly-professionalized organisation with more than 200 employees specialised in Materials Science, Manufacturing Process Engineering, Control Engineering, and Laser Processing. Its mission is to improve competitiveness and technology know-how of Manufacturing Industry through the following activities: 1) R&D&i projects, 2) Monitoring technology evolution, 3) Acquisition and development of emergent technologies and 4) Promotion of technology innovation in the companies.
AIMEN has experience in R&D collaborative projects managing several National and European projects dealing with Real-Time process control, robotics, hardware design, software processing, and laser processing. In this project, AIMEN will contribute to LAY2FORM project with its competence in the field of monitoring and embedded control systems design. Its interdisciplinary team of engineers and physicists provides competencies in the fields of sensors design, embedded control and software processing.
AIMEN has active presence in the main European and National technology platforms and initiatives related with materials and manufacturing technologies, specifically in EFFRA (related to Factories of the Future PPP), EuRobotics (linked to SPARC PPP) and EU Platforms like EuMAT, ManuFUTURE or Photonics21.
Role in the Project
AIMEN will be participating in all WPs. In WP1, AIMEN will support INEGI in the project management and be involved in the dissemination/communication activities, while contributing to the common Exploitation Program.
WP2 AIMEN will participate in Task2.1, contributing to the provision of the FMEA, development plans and analysis of the results and interdependencies in WP3-5, enabling the definition of the system and part redesigned, mainly in what concerns the laser-based processes, in-line inspection solutions and the knowledge-based CAx system.
WP3 AIMEN will assume the development of the laser cutting processes for the tape cutting and final edge trimming operations, including the specifications of the respective laser modules to be integrated in the pre-industrial system prototype developed in WP2 and demonstrated in WP6. AIMEN will also support the development of the in-line inspection strategies to assess the quality of the blank at the preforming heating stage and of the final 3D part, providing the computer vision solution and supporting the training process of each inspection technique.
WP4 AIMEN will closely collaborate with RESCOLL, assuming the fabrication of different textures to be combined with the adhesive coating, for enhancement of the bond strength. AIMEN will also be in charge of the application of Laser and/or US for the intermediate (dis)similar bonding in the blank lay-up. AIMEN will provide the speckle image solution (hardware and software) to be used in the metal surface modification operations, and support V2I in the development of the in-line inspection strategies to assess the quality of the bonding spots at the lay-up station.
WP5 AIMEN will be focused on the development of the knowledge-based CAD/CAM system covering the full manufacturing chain, being be responsible for the development of the modular control architecture that extracts motion planning and process parameters directly from product design. AIMEN will support the definition of the communication standard, the self-adaptive system and the TRL5 test and demonstration of the different systems.
WP6 AIMEN will participate in all tasks focused in the testing and validation of the manufacturing system, particularly in what concerns all Laser-based process modules and the knowledge-based CAx system.
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