Identifying the potential of human-robot collaboration in automotive assembly lines using a standardised work description

Teiwes, Johannes; Bänziger, Timo; Kunz, Andreas; Wegener, Konrad

doi:10.1109/iconac.2016.7604898

Cited by 25 publications

(7 citation statements)

References 17 publications

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“…However, the physical properties of components were not discussed, and the tasks categorization was limited to cable harnessing. Another methodology was presented by (Teiwes et al, 2016), assigning a score to various assembly tasks identified in MTM methods for automation. The scores were based on experimentation and were limited in application.…”

Section: Literature Reviewmentioning

confidence: 99%

Complexity-based task allocation in human-robot collaborative assembly

Malik

Bilberg

2019

121

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Purpose Over the past years, collaborative robots have been introduced as a new generation of industrial robotics working alongside humans to share the workload. These robots have the potential to enable human–robot collaboration (HRC) for flexible automation. However, the deployment of these robots in industrial environments, particularly in assembly, still comprises several challenges, of which one is skills-based tasks distribution between humans and robots. With ever-decreasing product life cycles and high-mix low volume production, the skills-based task distribution is to become a frequent activity. This paper aims to present a methodology for tasks distribution between human and robot in assembly work by complexity-based tasks classification. Design/methodology/approach The assessment method of assembly tasks is based on the physical features of the components and associated task description. The attributes that can influence assembly complexity for automation are presented. Physical experimentation with a collaborative robot and work with several industrial cases helped to formulate the presented method. Findings The method will differentiate the tasks with higher complexity of handling, mounting, human safety and part feeding from low-complexity tasks, thereby simplifying collaborative automation in HRC scenario. Such structured method for tasks distribution in HRC can significantly reduce deployment and changeover times. Originality/value Assembly attributes affecting HRC automation are identified. The methodology is presented for evaluating tasks for assigning to the robot and creating a work–load balance forming a human–robot work team. Finally, an assessment tool for simplified industrial deployment.

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Section: Literature Reviewmentioning

confidence: 99%

Complexity-based task allocation in human-robot collaborative assembly

Malik

Bilberg

2019

121

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“…On the other hand, human-robot interaction in the general sense is a study of robotic systems for use by or with humans which concern with understanding, designing, and evaluating robots [36]. In physical human-robot interaction, human safety is the main concern and must be considered when evaluating robot setups in a workspace [37]. This interaction is related to a form of communication whether the robots and humans are positioned near to each other or not.…”

Section: New Era Of Industrial Robotsmentioning

confidence: 99%

Computer Simulation of Human-Robot Collaboration in the Context of Industry Revolution 4.0

Rizal¹

2020

Becoming Human With Humanoid - From Physical Interaction to Social Intelligence

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The essential role of robot simulation for industrial robots, in particular the collaborative robots is presented in this chapter. We begin by discussing the robot utilization in the industry which includes mobile robots, arm robots, and humanoid robots. The author emphasizes the application of collaborative robots in regard to industry revolution 4.0. Then, we present how the collaborative robot utilization in the industry can be achieved through computer simulation by means of virtual robots in simulated environments. The robot simulation presented here is based on open dynamic engine (ODE) using anyKode Marilou. The author surveys on the use of dynamic simulations in application of collaborative robots toward industry 4.0. Due to the challenging problems which related to humanoid robots for collaborative robots and behavior in human-robot collaboration, the use of robot simulation may open the opportunities in collaborative robotic research in the context of industry 4.0. As developing a real collaborative robot is still expensive and time-consuming, while accessing commercial collaborative robots is relatively limited; thus, the development of robot simulation can be an option for collaborative robotic research and education purposes.

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“…Vice versa, with RF ¼ 0 and CF ¼ 0, no task can be performed by the robot and in collaboration, respectively. To estimate the potential of robot deployment to single stations of an assembly line, Teiwes et al (2016) develop a procedure to estimate the automation potential of a given line balance and apply their study to an automotive assembly line. Using their scoring system, they find that the majority of stations reach low (around 20%) or medium potential (around 40%) for deployment of collaborative robots.…”

Section: Problem Settingmentioning

confidence: 99%

Balancing of assembly lines with collaborative robots

Weckenborg

Kieckhäfer

Müller

et al. 2019

Bus Res

113

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Motivated by recent developments to deploy collaborative robots in industrial production systems, we investigate the assembly line balancing problem with collaborative robots. The problem is characterized by the possibility that human and robots can simultaneously execute tasks at the same workpiece either in parallel or in collaboration. For this novel problem type, we present a mixed-integer programming formulation for balancing and scheduling of assembly lines with collaborative robots. The model decides on both the assignment of collaborative robots to stations and the distribution of workload to workers and robotic partners, aiming to minimize the cycle time. Given the high problem complexity, a hybrid genetic algorithm is presented as a solution procedure. Based on extensive computational experiments, the algorithm reveals promising results in both computational time and solution quality. Moreover, the results indicate that substantial productivity gains can be utilized by deploying collaborative robots in manual assembly lines. This holds especially true for a high average number of robots and tasks to be assigned to every station as well as a high portion of tasks that can be executed by the robot and in collaboration.

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Identifying the potential of human-robot collaboration in automotive assembly lines using a standardised work description

Cited by 25 publications

References 17 publications

Complexity-based task allocation in human-robot collaborative assembly

Complexity-based task allocation in human-robot collaborative assembly

Computer Simulation of Human-Robot Collaboration in the Context of Industry Revolution 4.0

Balancing of assembly lines with collaborative robots

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