Task Balancing Between Human and Robot in Mid-Heavy Assembly Tasks

Dianatfar, Morteza; Latokartano, Jyrki; Lanz, Minna

doi:10.1016/j.procir.2019.03.028

Cited by 33 publications

(6 citation statements)

References 14 publications

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“…Zhang et al [38] implemented adaptive schedule with changing human capability in a HRC assembly and the human utilization in their study was between 52% to 66%, which mean 34% to 48% of robot utilization. The task balancing model in mid-heavy HRC assembly that presented by Dianatfar et al [39] gave the human utilization which ranged from 53.34% to 56.85% that indicated that the robot utilization ranged from 43.15% to 46.66% based on different interaction level. Therefore, the result of human utilization in our study was considered acceptable in the implementation of HRC system especially the 1H:2R(F) collaboration mode (54.87%).…”

Section: Case Studymentioning

confidence: 99%

Genetic algorithm-based task allocation in multiple modes of human–robot collaboration systems with two cobots

Liau

Ryu

2022

Int J Adv Manuf Technol

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In this paper, we introduce a human-robot collaboration (HRC) mold assembly cell to cope with smallvolume mold production and reduce the risk of musculoskeletal disorders (MSDs) on a human worker during manual mold assembly operation. Besides, the wide variety of types and weights of the mold components motivated us to design an HRC system that consists of two robots. Therefore, we propose two collaboration modes for HRC systems using two robots and develop a task-allocation model to demonstrate the application of these collaboration modes in the mold assembly. The task-allocation model assigns a task based on the task characteristics and capability of agents in the collaboration cell. First, we decompose the assembly operation into functional actions to analyze the characteristics of tasks. Then, we obtain the agent assignment preference based on task characteristics and capability of agents using the analytic network process. Finally, we apply the genetic algorithm in the final task allocation to minimize assembly time, use of a less capable agent, and ergonomic risk. This paper contributes to expanding the HRC system with two robots in the mold assembly to allow the execution of a greater diversity of tasks and improve the assembly time and MSD risk level for the human worker.

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Section: Case Studymentioning

confidence: 99%

Genetic algorithm-based task allocation in multiple modes of human–robot collaboration systems with two cobots

Liau

Ryu

2022

Int J Adv Manuf Technol

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“…For instance, in [10], a multicriteria decision-making framework is employed for the automatic optimization of the workplace layout through the allocation of tasks to humans and robots. In [11], instead, a method for static task allocation based on task complexity, ergonomics, payload, and repeatability is proposed. In the static scheduling approach, the sequence of operations, and possibly the agent responsible for them, are fixed in advance according to the product to assemble and to suitable decision criteria.…”

Section: Related Workmentioning

confidence: 99%

Flexible scheduling and tactile communication for human–robot collaboration

Maderna

Pozzi

Zanchettin

et al. 2022

Robotics and Computer-Integrated Manufacturing

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“…The authors in [27,31,35] considered different possibilities for task execution, i.e., human or cobot, or both at the same time. Similarly, [36] considered three levels of interaction: shared workspace without shared task, shared workspace and shared task without physical interaction, and shared workspace with shared task, i.e., the handing-over of parts. The authors identified that an increase in the interaction level leads to a decrease to the operator assembly time, and therefore the effects of the collaboration.…”

Section: Literature Reviewmentioning

confidence: 99%

C-ALB (Collaborative Assembly Line Balancing): a new approach in cobot solutions

Boschetti

Faccio

Milanese

et al. 2021

Int J Adv Manuf Technol

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Collaborative robots can be a proper solution to improve the throughput of manual systems without reducing their flexibility. To effectively use cobots in productive systems, it is fundamental to develop a suitable task allocation model that considers collaboration. Hence, we present a model for collaborative assembly line balancing (C-ALB) which considers paralleling tasks and collaboration in the balancing resolution. Indexes that take into account both the product and process characteristics are defined to evaluate the quality of the proposed task allocation model and comparing it to others. The results confirm the influence of the product characteristics on the system performance, leading to the definition of a new paradigm for product design.

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Task Balancing Between Human and Robot in Mid-Heavy Assembly Tasks

Cited by 33 publications

References 14 publications

Genetic algorithm-based task allocation in multiple modes of human–robot collaboration systems with two cobots

Genetic algorithm-based task allocation in multiple modes of human–robot collaboration systems with two cobots

Flexible scheduling and tactile communication for human–robot collaboration

C-ALB (Collaborative Assembly Line Balancing): a new approach in cobot solutions

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