A novel human-centered methodology for assessing manual-to-collaborative safe conversion of workstations

• The paper presents a novel method to assess the potential for transitioning manual tasks to collaborative ones. • The method combines physical and cognitive ergonomics , health and safety metrics, operational efficiency, and technical aspects. • Real-world applications of this method in various manufacturing sectors show its relevance and applicability in industry . The Industry 5.0 paradigm places workers’ well-being and safety at the core of the production processes. Despite its objectives, the current industry still faces several challenges. Examples of these challenges include global market pressures for customized products, along with the significant occurrence of Work-Related Musculoskeletal Disorders and the ageing workforce. These challenges underscore the persistent need for human-centered solutions, allowing adaptations that align with humans’ physical and cognitive constraints. Collaborative robots offer a promising solution, with the potential to enhance workers’ well-being, while maintaining safety, productivity, and production process flexibility. This study introduces a novel methodology designed to assess the feasibility of converting manual tasks into collaborative ones. During the development of the methodology, a focus group approach was used, comprising 6 experts in the field of Ergonomics & Human Factors and Robotics. The proposed methodology is suitable for the identification of tasks appropriate for joint execution by humans and robots, thereby augmenting the effectiveness of the robotic solution. This methodology incorporates a set of indicators (physical and cognitive ergonomics, health and safety, and operational efficiency) and technical requirements. The results of the focus group allowed the improvement of the suggested methodology. For its testing, we applied across 13 manual workstations in 5 companies from different manufacturing sectors (civil construction, cutlery, furniture, and automotive fabric manufacturing). Results show that it is possible to comprehensively identify manual workstations/tasks with good and high potential to convert into collaborative systems. This methodology seems to constitute a relevant approach to support the conceptualization of collaborative workstations.