Background: In the current digital transformation, also known as Industry 4.0, automation, artificial intelligence, and internet of things are promising to lead to higher product quality, system efficiency and safety. However, workers have largely been neglected in the process, leading to suboptimal outcomes in the smart factory. Objective: This project demonstrates how human performance models can be added to industrial system models to improve the design of the industrial system and manufacturing processes along with the product design. Methods: For the use case, a critical process in the production of a new airplane was selected for the study. This process requires the highest quality assurance and is normally performed manually. Robot assistance was being considered as a way to improve quality and efficiency by the system architects. A human performance simulation model focused on worker fatigue was developed, taking into account characteristics of the workers, robots, and tasks. Two different automation scenarios (fully manual, semi-automated), with different worker characteristics such as skill, age, motivation, etc. were studied. Results: Using historical production line data in the fully manual scenario, and simulated data for the semi-automated scenario, global fatigue scores and graphical visualization were generated by the model for each scenario, allowing the system architects to understand the effects of the future production system on workers, including errors, time lost, costs and overall resilience of the system. In Industry 5.0, a human-centered approach will ensure that Industry of the Future optimizes product quality and system efficiency while ensuring worker wellbeing.