Industry 4.0 is believed to introduce new smart digital tools which transform manufacturing processes but affect production personnel’s work practice. Operators and maintenance personnel running the everyday operations need to learn and handle new routines and systems while maintaining production efficiency. Operators today are challenged when they must handle unexpected stops caused by machine failures and the following error recovery process of automated production systems. With complex digital tools and integrated production systems the error recovery process becomes complex because there is no one-size-fits-all solution and a lack of intelligent and automated restart systems. Even if there are defined routines for industrial work and structures for managing digital technologies, it is not adapted to the individuals’ cognitive processes neither to their workplace learning. Altogether it puts high pressure on operators’ knowledge and skills of restarting machines and systems caused by errors. The aim is to explore operators and maintenance personnel cognition and skills and how their roles vary in relevant aspects of situational awareness and workplace learning. In an on-going case we studied two industrial companies that produce similar components but are working differently with production and maintenance. Through nine interviews we investigate the differences between the companies, their current work practices, and future changes. With application of a situation awarenessmodel, we capture cognition and learning including task/system factors, perception and decision making, and individual factors. Perspectives of workplace learning and knowledge sharing between personnel and relations to the systems use are applied. Results indicate that rule-based behaviours are key for both operators and maintenance personnel. These behaviours are supported by the systems and routines, but complicated errors make the systems and routines prove inadequate. In conclusion, to design appropriate digital support tools both operators and maintenance personnel behaviour need to be supported, however they need to be supported differently since their function behaviours such as routines, system use and communication vary. In addition, future skills and competences needed forsupporting complex system tasks include knowledge of computational models and simulation, knowledge of the machines and how they interrelate with systems, and logic reasoning and robotic programming of automated production systems.