## 5 Discussion
### Summary of Results
The last sub-task, the actual forming process, also showed that operators constantly monitored deviations from the goal state (i.e., achieving a sufficient target geometry of the work piece). Thereby, operators attended to those information sources that have proven to be the most error-prone throughout the entire process (i.e., clamping device) and those that show the development of the final forming result (i.e., the machine tool actually forming the work piece). Three anomalies were detected within this sub-task that led to a specific diagnosis, problem solving, and resolution within the team. However, for some of the detected anomalies, the causes were not identified during the diagnosis process. One of the reasons for this could be due to a lack of experience. For example, in the present study, the operators detected a serious wedging between the machine tool and clamping device during the forming of the work piece. This was a novel situation for all operators, meaning that the collision occurred on a point that had previously been classified as non-critical. Because the causes could not be eliminated immediately, it was more important for the team to address the \"symptoms\", i.e., solve the wedging, in order to finish the forming task and avoid lasting damaged. Hence, in such (novel) situations, an identification of causes is probably postponed to the future. However, the debriefing of the forming process was not part of the present investigation. In sum, the present investigation shows how regular process monitoring and, if necessary, subsequent diagnosis, problem solving, and resolution processes work during the supervision of complex and dynamic production systems (as proposed by [20,29]). However, as the supervision of complex and dynamic production systems is based on the composition of the respective team, some components of the analyzed process are concealed to the applied research methods. 1.2 The Impact of Different Psychological Concepts on Anomaly Resolution and Resulting Cognitive Support Possibilities  
The analysis of gaze behavior, as well as interview data, allowed for a clear role allocation between the three operators that took part in our study. Gaze and interview data discriminated between individual tasks and tasks that were shared between two or all three operators. This is in line with the proposed framework, as it highlights individual and team processes equally. More specifically, all operators were reported during the interview to have domain-specific knowledge (see, e.g., [32,33]), which is a central characteristic of experts and leads to associated responsibilities within the team and operating process. This means that operator 1 is mainly responsible for controlling the speed and trajectory of the robot, as well as avoiding collisions of the robot with the work table and clamping device; operator 2 focuses on the physical forming of the work piece and the clamping device settings; and operator 3 takes the overall responsibility for the forming process. This individual expertise enables the operators to run mental simulations and spot anomalies (see, e.g., [39]) as well as to anticipate situations and evaluate situations globally (see, e.g., [20]), which has also been found in the present study. For example, operator 1 anticipated the trajectory of the machine tool guided by the robot. This was evident by gaze behavior that did not focus on the machine tool itself but preceded its position at the work piece (see Figure 5). Hence, the work piece received much more attention than the machine tool by operator 1. Due to the expert knowledge of operator 1, they can successfully perceive and integrate information from the work piece, control panel, and robot behavior to project or anticipate their status in the near future. Operator 2 anticipated the physical formation of the work piece using their experience and knowledge by integrating relevant information of the work pieces' material, the machine tool, and the applied forces.