Decision-Making Framework for Implementing Safer Human-Robot Collaboration Workstations: System Dynamics Modeling

Abstract

Human-Robot Collaboration (HRC) systems are often implemented seeking for reducing risk of Work-related Musculoskeletal Disorders (WMSD) development and increasing productivity. The challenge is to successfully implement an industrial HRC to manage those factors, considering that non-linear behaviors of complex systems can produce counterintuitive effects. Therefore, the aim of this study was to design a decision-making framework considering the key ergonomic methods and using a computational model for simulations. It considered the main systemic influences when implementing a collaborative robot (cobot) into a production system and simulated scenarios of productivity and WMSD risk. In order to verify whether the computational model for simulating scenarios would be useful in the framework, a case study in a manual assembly workstation was conducted. The results show that both cycle time and WMSD risk depend on the Level of Collaboration (LoC). The proposed framework helps deciding which cobot to implement in a context of industrial assembly process. System dynamics were used to understand the actual behavior of all factors and to predict scenarios. Finally, the framework presented a clear roadmap for the future development of an industrial HRC system, drastically reducing risk management in decision-making.

The Relationships of Human-Cobot Interaction Fluency with Job Performance and Job Satisfaction among Cobot Operators—The Moderating Role of Workload

“…Regarding human contribution-oriented fluency , [ 4 , 10 ] point out that the variability and reliability of human behavior affect human–robot interaction in terms of safety, quality, and productivity. Similarly, [ 27 ] claim that the operator supports the technical system and production requirements, and [ 9 ] even argue that the human component influences the performance of the human-robot team more than the technological one.…”

“…The human emotions-oriented fluency is based on the assumption that people interact with robots as they do with co-workers [ 10 ] or people [ 42 ] rather than tools due to their willingness to apply social characteristics to technology [ 43 ]. Precisely, this perspective reflects the cognitive-affective states evoked in humans during collaborating with a robot.…”

“…Collaborative robots (cobots) are designed for mutual and direct interaction with humans [ 8 ]. Because they are equipped with safety assurance mechanisms [ 9 ], cobots assist operators by delivering and handling objects [ 10 ] in a fenceless and confinement-free environment. Direct human-robot interaction aims at incorporating the unique advantages of humans [ 11 ] and collaborative robots [ 12 ] by combining the skills and abilities of both parties to achieve a common goal [ 13 ] in a temporospatial overlap [ 14 ].…”

“…Specifically, although the research on the positive impact of cobots on workers’ experiences has been prolific, the assumption that collaborative technology is exclusively advantageous would be biased. Although many studies suggest that cobots support humans in terms of physical and mental load [ 1 , 9 , 10 , 18 ], there are other empirical investigations showing that cobots increase workload [ 7 , 9 , 10 , 15 , 28 ]. The conflicting pattern of findings indicates that there is still a need to explore workload [ 22 , 24 ] as an essential individual factor in human-robot interaction [ 9 ].…”

The Efficiency of Collaborative Assembling Cells

“…In addition, according to research, the implementation of collaborative robots significantly reduces the risk of developing occupational diseases. For example, the paper [6] is devoted to the system for evaluating the productivity of a collaborative cell for the assembly of electronic components and the risk of occupational diseases. It was made due to the frequent absence of workers due to absenteeism caused by occupational diseases of the musculoskeletal system.…”