Inclusive manufacturing: A contribution to assembly processes with human-machine reciprocal learning

This study explores the potential synergy between neurodiversity and advanced technology within Industry 5.0, focusing on the integration of neurodiverse individuals in the workforce through Human-Machine Collaboration and Reciprocal Learning (RL). A cognitive load (CL) assessment procedure is developed using fuzzy logic inference across the dimensions of attention, memory, language, math, logic, and reading. A case study evaluates the effectiveness of RL in assisting assembly tasks. Different error-handling scenarios are compared. Experimental results show how RL can reduce the CL while improving assembly tasks efficiency, underscoring the value of intelligent systems in inclusive manufacturing, enhancing productivity and facilitating the integration of neurodiverse workers.