Artificial Intelligence and Big Data CSA for Process Industry Users, Business Development and Exploitation

Informacje na temat projektu

AI-CUBE

Identyfikator umowy o grant: 958402

DOI

10.3030/958402

Projekt został zamknięty

Data podpisania przez KE 6 Lipca 2020

Data rozpoczęcia 1 Września 2020

Data zakończenia 28 Lutego 2023

Finansowanie w ramach

• INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Advanced manufacturing and processing

Koszt całkowity

€ 597 806,25

Wkład UE

€ 597 806,25

Koordynowany przez

PNO INNOVATION SRL
Italy

Periodic Reporting for period 2 - AI-CUBE (Artificial Intelligence and Big Data CSA for Process Industry Users, Business Development and Exploitation)

Okres sprawozdawczy: 2021-09-01 do 2023-02-28

Podsumowanie kontekstu i ogólnych celów projektu

The AI-CUBE concept is a framework that maps and visualizes the use and penetration of artificial intelligence (AI) and big data (BD) technologies in the SPIRE sectors and macro-application-process areas. It is based on a tri-axial mapping system.

The Cube Concept comprises four key results that drive European process industries' assessment and adoption of AI and BD technologies. The first is a novel framework called AI and BD Maturity Level Assessment, which helps companies determine their level of implementation of these technologies and their Technology Maturity Level (TML).

The second result is the AI-CUBE tool, which serves as a mapping tool for individual industries or sectors to assess their level of advancement in AI and BD and identify areas that require further development.

The third result is a set of inspirational AI and BD Business Cases and the AI-CUBE Business Model Game, which industries can use to stimulate discussion and identify how AI and BD can improve their Business Models and Value Chains.

The fourth result is a roadmap and easy-to-read guidelines outlining the steps towards transferring AI and BD good practices from one SPIRE sector to another and developing technology solutions for AI and BD Business Cases of the future different SPIRE process industry sectors.

Prace wykonane od początku projektu do końca okresu sprawozdawczego oraz najważniejsze dotychczasowe rezultaty

The AI-CUBE project had two reporting periods (RP1 and RP2). In RP1, WP1, WP2, and to some extent, WP3 made significant advancements, while WP5 and WP6 progressed in Dissemination, Communication and Exploitation, and Project Management, respectively. WP1 produced three deliverables and laid the foundation for the rest of the project. WP2 developed a customized Maturity Level Assessment (MLA) framework for AI and BD in the process industry. WP3 explored the Compilation of AI & BD technology per application and sector. The project was granted a six-month extension for RP2 to maximize stakeholder engagement. WP3 built on the work from the previous RP and created an overview for several objectives. WP4 developed the AI-CUBE roadmap and guidelines and identified industrial synergies. WP5 and WP6 progressed efficiently, and all the project milestones were achieved.

Innowacyjność oraz oczekiwany potencjalny wpływ (w tym dotychczasowe znaczenie społeczno-gospodarcze i szersze implikacje społeczne projektu)

The AI-CUBE project aimed to maximize the potential of AI and BD in the European process industry. The project developed roadmaps to guide researchers, managers, and operators on enhancing digital technology development in SPIRE industry functions and processes. To achieve this goal, the AI-CUBE project set specific objectives, including creating a multi-dimensional AI and BD map, or "CUBE," that assessed the current state of play and level of penetration of these technologies in different organizational processes across SPIRE process industry sectors. The project also developed future AI and BD business cases, identified white spots in AI and BD solutions, defined data requirements and necessary skills, and determined RD&I requirements for future AI and BD business cases to emerge within the different process industry sectors. The project's main results included guidelines, the Business Model Game, and the Maturity Model, which were valuable resources for industries to improve their integration of AI and BD technologies, practices, and business models. Implementing these technologies could lead to better process control and optimization, energy savings, better research and development tools and results, and support transitioning to the Circular Economy, net-zero waste, and carbon-neutral processes. Overall, the AI-CUBE project has significant potential to impact the process industry.

The CUBE concept