In addition, recent advancements in collaborative robots have enabled a deeper interaction potential by incorporating real-time feedback features. Applications range from task performance monitoring to interactive risk assessment via non-invasive wearable sensors [10] and augmented reality headsets [11]. Thus, a human-robot collaborative system (HRCS) is a semi-automated setting that integrates the accuracy and repeatability skills of robots with the dexterity and cognitive capabilities of humans within a shared workspace. HRCSs are set to change the traditional separate vision of humans and robots in manufacturing shop floors towards a synergistic relationship [3,12]. For instance, long-standing challenges in the automotive industry, such as the installation of wire harnesses [13,14] or the assembly of engine blocks [15,16], are being addressed by organizations in real-world environments through the shared manipulation of critical components that collaborative systems seamlessly facilitate. The implementation of HRCS is, nowadays, largely justified by the enhancement of physical ergonomics, where manual and mechanical labor are divided according to their potential advantages in terms of productivity [1]. Ergonomics is focused on understanding this type of interaction between humans and the elements composing a system while making them compatible with the needs, abilities, and limitations of human operators [17]. In this regard, an anthropocentric approach beyond physical wellbeing (i.e., cognitive and organizational ergonomics) has become necessary for the new roles that human operators are adopting when leading or following avant-garde robotic agents, as shared work responsibilities have not been properly explored nor determined in the literature [18,19]. Furthermore, even if collaborative robots provide some degree of physical protection to human operators, their effect on cognitive ergonomics should be a problem of special importance for both academic and industry practitioners [20, 21, 22]. Effective decision-making is a complex cognitive process which requires an optimal allocation of mental resources; otherwise, humans could experience undesired levels of cognitive workload or spare mental capacity that might lead to diminished performance or unsafe behavior [8,18]. Moreover, having a towering number of task elements might be cognitively overwhelming for human operators if an unstructured work design strategy is established in HRCS. This is especially true as the assignment of activities among humans and robots is not yet a straightforward procedure despite their individual well-defined skills [23]. The main objective of this article is to determine the effects that different work design strategies in HRCS have on the cognitive workload of human operators. Its research novelty comes from the study of human beings in the leader-follower work role dichotomy emerging in current industrial environments by (1) identifying the structural composition of HRCS and their most used work design strategies within manufacturing applications and (2) assessing the cognitive response that human operators exhibit through different collaborative scenarios while enforcing subjective and objective measuring instruments. The presented work is organized as follows: Section 2 presents a detailed review of HRCS work design's latest praxis and topics related to its evaluation of safety and cognitive ergonomics. Afterward, the hypotheses, experimental setting, and data analysis approach are explained in Section 3. Moreover, in Section 4, the description of subjective and objective results on cognitive ergonomics is provided. Finally, an overall analysis and closing remarks are shown in Sections 4 and 5, respectively.