Industry 4.0 is expected to deliver significant productivity gain taking advantage of Internet of things (IoT). Smart solutions, enhanced by IoT, are constantly driving revolutionary approaches in multiple domains. Smart factories are one domain where intelligent integrated robotic systems will revolutionize manufacturing, resulting in a complex ecosystem, where humans, robots and machinery are combined. In this setting, human safety requirements are of paramount importance. This paper focuses on symbiotic human–robot collaboration systems (HRC), where human safety requirements are essential. Hence, it aims to explore and prioritize human safety requirement dependencies, as well as their dependencies with other critical requirements of smart factory operation, as effectiveness and performance. Toward this end, the proposed approach is based on SysML to represent the requirements dependencies and pairwise comparisons, a fundamental decision-making method, to quantify the importance of these dependencies. This model-driven approach is used as the primary medium for conveying traceability among human safety requirements as well as traceability from safety requirements to effectiveness and performance requirements in the system model. The analysis is based on the operational requirements identified in the European project HORSE, which aims to develop a methodological/technical framework for easy adaptation of robotic solutions from small-/medium-sized enterprises. Validation of the results is also performed to further elaborate on human safety requirement dependency exploration. The outcomes of this paper may be beneficial for symbiotic HRC systems in the early design stage. As the system is being developed with an emphasis on human safety, all these requirements that have been assessed with highly prioritized dependencies should be taken into account, whereas those with negligible ones have to be ignored since they do not significantly affect the rest of the process. Since operational requirements may be conflicted and incompatible, this approach may be very useful for other systems as well during the system design phase to find the appropriate solution satisfying the majority of the requirements, giving a priority to the ones with highly ranked dependencies and hence facilitating the implementation phase and afterward the production line. The outcomes may be used as a step in developing a model-driven approach which should be able to support the manufacturing process, facilitating the integration of systems and software modeling, which is increasingly important for robotic systems in smart factories incorporating HRC.