Towards the modelling of defect generation in human-robot collaborative assembly

The development of suitable defect generation models is crucial in both academia and industry having the dual purpose of predicting defects occurring in manufacturing processes and planning eligible effective quality controls. In manual assembly processes, much research focused on developing approaches to predict operator-generated defects. Today, collaborative robotics is gaining increasing attention in smart factories by contributing to the reduction of operators' physical and cognitive workload and thus enabling improved productivity. The present study proposes a preliminary investigation on defect generation models in a human-robot collaborative environment aiming to compare quality performances achieved in purely manual assembly.