Description du projet
Recourir à l’apprentissage automatique pour faire passer la fabrication additive à un nouveau niveau de traitement
L’expansion rapide de l’industrie de l’architecture, de l’ingénierie et de la construction (AECI) dans le monde entraîne une production importante de déchets, une forte consommation d’énergie et une lourde pollution de l’environnement. Le pacte vert pour l’Europe incite le secteur de l’AECI à réduire au minimum l’utilisation de matériaux et la production de déchets. La fabrication additive (FA) est un processus flexible et automatisé qui permet de produire des objets à géométrie complexe, réduisant ainsi le temps de production. Le projet ADDOPTML, financé par l’UE, développera un processus complet de conception et de fabrication de structures civiles basé sur l’apprentissage automatique. Il encouragera les synergies entre des experts universitaires pluridisciplinaires et des PME de Belgique, de Chypre, d’Allemagne, de Grèce, d’Italie, de Jordanie, des Pays-Bas et d’Espagne. Il s’appuiera sur l’avancement des technologies de FA, y compris les consommables recyclés, pour répondre à la pénurie d’unités hospitalières pendant la pandémie de COVID-19.
Objectif
Additive Manufacturing (AM) has attracted the interest of industry due to its potential for flexible and automated production of complex geometry objects, combined with minimizing the time required to develop new products. According to recent analysis, the market for AM products is projected to grow annually by 18%. Although AM technologies are an integral part of digitized industrial production and of the 4th industrial revolution, Architectural, Engineering & Construction Industry (AECI) is reluctant to adopt them in design and construction. While AECI has been a pillar industry since 80's, its scale and impact on the global economy expands continuously. This development is also associated with important drawbacks, including large contribution to waste production, huge energy consumption and severe environmental pollution. The recent Green New Deal for Europe sets as primary objective the reform of heavy industry, including AECI, which accounts for 40% of the energy consumed on the continent. The main tools for achieving this objective are to minimize both materials used and amount of AECI waste. The principal aim of ADDOPTML network is to create and validate a holistic machine learning aided, optimum design-manufacturing process of civil structures by developing strong synergies among a multi-disciplinary team of academic experts and SMEs from Belgium, Bulgaria, Cyprus, Germany, Greece, Italy, Jordan and Spain. This will be achieved by taking advantage of ongoing progress in AM technologies including recycled consumables, thus contributing to the European challenge to become the world's first climate-neutral bloc by 2050. As a primary application, an integrated structural design framework based on AM optimized structural elements for transitional structures will be developed, to address the shortage of hospital units faced by many countries as coronavirus pandemic continues to sweep the World and to develop novel human shelter structure for post-disaster housing.
Champ scientifique
- medical and health scienceshealth sciencespublic healthepidemiologypandemics
- social sciencespolitical sciencespolitical transitionsrevolutions
- medical and health scienceshealth sciencesinfectious diseasesRNA virusescoronaviruses
- engineering and technologymechanical engineeringmanufacturing engineeringadditive manufacturing
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Mots‑clés
Programme(s)
Régime de financement
MSCA-RISE - Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE)Coordinateur
157 80 ATHINA
Grèce