Sustainable future enabled by AI: DaCapo's real-world applications in circular economy
By AIMEN Centro Tecnológico
The main objective of DaCapo is to develop new digital tools and services for boosting the CE principles across the entire value chain. These tools and services are focused on AI-based systems and product/process Digital Twins in the different phases of the product lifecycle. This will be demonstrated in three use cases (aeronautics, smartphones industry, and warehousing) in which AI tools like generative models or space optimisation algorithms are going to be applied in real companies to boost their R strategies and competitiveness:
During the last few years, the increasing awareness and urgency to take more substantial actions have clarified visions, strategies, and policies, which put a lot of emphasis on the environment and sustainability as key goals and improvement areas. GKN Aerospace Engine Systems, which manufactures and sells advanced aerospace technologies and components for jet engines and space launchers, will be focused on repairing, giving alternative manufacturing, and repairing paths within the process, and learning how Digital Product Passport and Data Spaces will be part of a CE-Decision Support System.
Fairphone will further improve its market leadership by strengthening its product’s current Unique Selling Points (USPs) by optimising them with generative AI tools that can be used to generate CAD designs and help with material selection based on functional and sustainability requirements. Besides that, the Digital Product Passport would not only be a tool that can be utilised to meet regulatory requirements, but it would facilitate preventive maintenance through real-time diagnosis, improving after-sales and end-of-life due to accurate asset tracking, and be a user-facing ‘marketing tool’ that can be used to communicate the intricacies of Fairphone’s unique visibility in their (more and more) fair(er) supply chain.
Pesmel supplies automatic warehouses and in-mill logistics systems to the paper, steel, and tire industries. The optimisation of warehouse layout designs will be addressed through generative AI tools considering specific design features previously generated in the Digital Twin e.g., the number of modules and dimensions of the warehouse, as well as Circular Economy related KPIs such as modularity and reusability presented in the Digital Product Passport. Following this approach, new
AI-based eco-designs will be generated considering user requirements and specifications, design features and constraints, and the overall sustainability and circularity of the process. Besides that, Reinforcement Learning (RL) methods will address the optimization of movements and speed of devices within the warehouse, with the aim of minimising the number of operations to be executed to save energy and reduce mechanical wear, extending the lifetime of the equipment.
The overall goal for these use cases in DaCapo is to develop methods and tools for data-based analyses, predictions, and decision support that will have a positive impact on sustainability and circular economy. Digital technologies and capabilities will become even more important to make improvements to internal efficiency, enabling the adoption of new technologies based on data analytics, AI and ML to maximally exploit the manufacturing data economy.
