Date of Award
Doctor of Engineering (DEng)
Materials and Infrastructure Systems
Manufacturing assembly is combining previously made components or subassemblies into a final finished product. The assembly process can be manual, hybrid, or fully automated. Human operators who are involved in assembly use their judgment to perform the process. They collaborate with the other work agents such as assembly machines, robots, smart technologies, and computer interfaces. The recent Industrial revolution, Industry 5.0, exploits human expertise in collaboration with efficient and accurate machines. Manufacturing facilities that feature Industry 5.0 work settings require higher expectations, higher accuracy, sustainability solutions, mass customization of products, more human involvement, and digital technologies in smart workstations. Given these features, the cognitive load exerted on human workers in this environment is continuously increasing, leading to the use of cognitive heuristics. Cognitive biases are getting more attention in the cognitive ergonomics field, to help understand the operational behavior of workers. Manufacturing facilities can integrate cognitive assistance systems to work in parallel with physical and sensorial assistance systems. Cognitive assistance systems help toward better work conditions for workers and better overall system performance. This research explores the impact of human thinking style and using a cognitive assistance system on workers' cognitive load, bias-related human performance, and user satisfaction. This research presents the design and experimental implementation of a research framework based on a well-established three-layer model for implementing Industry 5.0 in manufacturing. The research framework was designed to apply the dual-system theory and cognitive assistance in Assembly 5.0. Two experiments are presented to show the effectiveness of the proposed research framework. A cognitive assistance system was designed and compared to a benchmark system from LEGO ® Company. Subjective and objective measures were used to assess the thinking style, cognitive load, bias-related human performance, and user satisfaction in Assembly 5.0. As Industry 5.0 requires higher expectations, higher accuracy, smart workstations, and higher complexity, cognitive assistance systems can reduce the cognitive load and maintain the work efficiency and user satisfaction. Therefore, this work is important to industry to expand the use of cognitive ergonomic tools and employ them for A5.0 workers' benefits.
Hamarsheh, Dana Isam, "" (2023). Dissertation. 1000.