Modeling and optimization of manufacturing systems considering human-machine interoperability and the active aging workforce

The general trend of markets forced industry to shift from mass production to mass customization; therefore, they need to improve their flexibility to keep their productivity. Industry 4.0, especially collaborative robots (cobots) that collaborate with workers in a shared space, could bring flexibility to manufacturing systems. However, although it has been several years since cobots were introduced to industries, the first focus of researchers has been on the robotic and programming aspects of them. Therefore, the implementation of cobots is a new topic that has concerned researchers. Beside this, the Industry 5.0 paradigm places emphasis on being human at the center of production, and at the same time, the average age of workers in the European Union has increased in recent years. These coincidences could bring some unexpected challenges and opportunities for industries that need more investigation. This PhD dissertation investigates the implementation of cobots in production systems to understand how this implementation affects production systems, with a particular focus on assembly systems. After an extensive literature analysis, new approaches and optimisations are proposed to integrate collaboration scenarios into assembly systems, along with safety speed limitations and personalized ergonomic indexes. Distinctively, a combination of all collaboration scenarios is considered with the objective of analysing the effectiveness of the implementation of cobots in assembly systems and improving workers' ergonomics in the working environment. In addition, to validate the proposed model, a database was created by performing a real-life case study in both manual and collaborative environments, and the fatigue level and posture ergonomic index (REBA) of each task were measured precisely. The outcome of this research can be instructive for production system managers and practitioners when deciding on investments in collaborative systems.