This is a Use Case developed in the context of the FAIR project. The overall objective of the project is to create a collaborative ecosystem to support a manufacturing company's adoption of the Industry 5.0 paradigm. This overall objective can be decomposed into the following three specific objectives: O1 – Definition of the collaborative ecosystem architecture The architecture of the collaborative ecosystem to define must enable the management of an IoE system allowing a human-centric approach to the manufacturing system, as well as the management of data required for mass personalization activities. The data managed by the ecosystem cover environmental, worker-related, and production system-related parameters. All these data will be collected through the associated IoE system. Other data managed by the ecosystem regard customers and marketing support. This data will be collected through the company CRM or through access to other internal and external sources (e.g., review systems or social networks). O2 – Definition of the component for mass personalization The mass personalization component to be defined aims to create highly personalized products tailored to customer preferences. To this end, it analyzes large amounts of data related to the customer's needs and desires, past behavior and relationships, as well as data related to product design, features and functionalities. By applying Artificial Intelligence techniques, the component will have to ensure the realization of unique, customer-specific products allowing the achievement of greater customer satisfaction and a competitive advantage for the company in the marketplace. At the same time, the realization of these products will have to take place at a scale comparable to mass production, with appropriate consideration of environmental sustainability, such as through the reduction of waste due to the realization of products that do not find interest in the market. O3 – Definition of the component for smart support to task execution The component for smart support to task execution to be defined first uses information coming from the IoE system to monitor environmental parameters as well as psychophysical parameters of workers. The goal is to exploit this information in assigning various tasks to workers in such a way as to optimize task execution without overloading certain workers too much, and making sure that the assigned tasks, and the corresponding risks they entail, are compatible with the worker's current psychophysical situation. Therefore, this aims to optimize task assignment by making it more cost-effective while fostering a safer work environment.