How do conducive forms of interaction contribute to the mastery of CPPS requirements?
© RTG 2323
Doctoral Researcher
NameDipl.-Ing. Sebastian Lorenz
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Research Training Group 2323
Research Training Group 2323
Visiting address:
Institutsgebäude S7A
Raum / Room 205
Georg-Schumann-Str. 7a
01187 Dresden
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Supervisor: Prof. Thomas Herlitzius |
Co-Supervisor: Prof. Susanne Narciss |
Research Topic
The introduction of Cyber-Physical Production Systems (CPPS) in agriculture changes the work profiles of operators. As CPPS (e.g., the highly automated “Feldschwarm”) are operating automatically in many situations, direct control tasks of operators decrease whereas monitoring and planning activities increase. Supervising such agricultural CPPS might lead to more inhomogeneous and infrequent workloads, as problems where operators have to intervene cannot be scheduled. Tackling human-friendly work conditions is all the more important as the operator has to fill the gap between the automation capabilities and dynamic requirements of real field-based missions. In particular, the complexity, novelty and lack of transparency of the highly automated machines and their embedded technology challenge the operators' competency perception which may impact their confidence and self-efficacy toward operation tasks.
The operation of CPPS in agriculture will include intervention scenarios, where the automation capability of the machine(s) will be exceeded and the operator has to intervene by the means of diagnosis, decision-making and manual control activities. In such situations the CPPS can only provide limited information on the cause that led to the automation capability exceedance. The CPPS might also be able to compute a range of solutions that can be presented to the operator. Providing information about the data basis these cause analyses and solution recommendations have been computed upon, as well as contextual information influences whether the operator will feel competent to take over the control in critical incidents such as abrupt control reallocation situations.
However, in the agricultural sector operator qualification tends to be low, and many operators did not go through formal training at all. And even if they did, current training programs cannot possibly equip operators with the competencies required to deal with a highly automated CPPS. This is reflected in findings showing that today only a fraction of the agricultural machines’ potential is being used. This gap between possible and actual productivity is expected to increase with the increasing complexity of machines. Therefore, interfaces should provide on-the-job training to optimize operators’ interaction with the system. However, designing such interfaces requires an assessment of the operators’ current competencies as well as the competencies required to enhance productivity in complex CPPS.
Therefore, the thesis systematically assesses operator competencies in mobile agricultural systems, analyzes current trends of higher automation and digitalization, and uses these trends to derive specific competency requirements to increase system performance in these scenarios. Based on this conceptual work, interface concepts are developed and evaluated in order to contribute scientific evidence and applicable knowledge to the question of how human-machine interfaces can be designed to promote operators’ perceived competencies in managing critical incidents with the CPPS.