MAIN TOPICS COVERED

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Experiments are expected to cover the following topics: 
 

TOPIC 1: AI-at-the-Edge – convergence between Data and AI continuum, Cloud, Edge, IoT technologies
AI is transforming various industries, including manufacturing, and the AI REDGIO 5.0 project aims to highlight its benefits when implemented at the Edge. By leveraging the edge-to-cloud continuum and modern cloud-to-edge frameworks, manufacturing enterprises can take advantage of low latency, minimal data transfer, and enhanced data sovereignty and privacy. Given the dynamic nature of AI at the Edge applications, ensuring high data quality is crucial. This necessitates innovative approaches for quality monitoring, such as data observation, which is incorporated into the AI REDGIO 5.0 reference architecture.The project seeks experiments that demonstrate real-life use cases requiring AI and data pipeline execution at the edge or utilizing hybrid cloud-edge infrastructures. These experiments should tackle data quality challenges and design the necessary AI and data pipelines for local execution in edge computing environments, like those specified by the AI-REDGIO Open Hardware. Applications of interest include predictive and prescriptive maintenance, automation, manufacturing operations planning, waste reduction, energy efficiency, and quality control. Examples might involve developing monitoring systems that efficiently transfer data to the cloud, utilizing edge hybrid architectures for data selection and model accuracy, and implementing machine learning models on AI-driven edge systems to optimize manufacturing processes. Reusing and eventually publishing AI models to the AI-on-Demand platform is also encouraged.


TOPIC 2: Industry 5.0 Human Centric and Sustainable-Circular Manufacturing, inspired by WISE principles
Sustainability, circularity, resilience: 
Industry 5.0 aims to go beyond the technical and economic objectives of Industry 4.0 by prioritizing human well-being, sustainability, circularity, and resilience. This next level of industrialization emphasizes the return of manpower to factories, distributed production, intelligent supply chains, and hyper-customization, all designed to deliver a tailored customer experience consistently.Selected experiments should explore how human-centered digitalization and Industry 5.0 can enhance the flexibility and adaptability of SME production processes, resulting in more resilient and sustainable systems. The focus is on demonstrating measurable benefits, such as improved worker well-being, safer workspaces, adaptability to adverse situations, and reduced environmental impact throughout the product lifecycle. Proposals should address AI for circular manufacturing, emphasizing real-world circularity challenges in the manufacturing sector. They should develop novel, reusable, and human-centric algorithms and tools, leveraging AI to improve data quality and create trustworthy AI models. GenAI models with human-in-the-loop, such as LLMs for manufacturing, should be employed to enhance decision-making and explainability of AI solutions. Applicants are encouraged to use the AI REDGIO 5.0 reference architecture for end-to-end solutions, providing clear business scenarios, realistic KPIs, and the commitment of manufacturing SMEs to measure the business benefits. The envisioned Industry 5.0 workplace promotes a collaborative intelligence-driven paradigm where humans and machines share physical spaces and work closely together, ensuring ethical, regulatory, psychological, and societal impacts are considered. The goal is to create a synergistic, human-centered co-working environment that benefits both industrial companies and workers.
Key human related aspects to be considered:
Experiments under Topic 2 must address one or more of the following WISE aspects

• Well-being, Comfort, and Acceptance: Examining the impact on mental well-being, self-esteem, frustration, feelings of usefulness, emotional dependence, human dignity, autonomy, oversight, and willingness to collaborate with machines.

• Inclusion and Special Categories of Workers: Assessing effects on older workers, novices, workers with cognitive or physical disabilities, social isolation, and risks of discrimination or bias.

• Safety of the Worker: Focusing on health and safety, risk of harm, and privacy concerns.

• Ergonomics and Improving Working Conditions: Analyzing impacts on stress and fatigue reduction, and effects on workers' skills.