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Due to the increasing trends of individualization and variant diversity, cobotic production systems are becoming more important. However, cobots are hardly used in small and medium-sized enterprises (SME) because of a lack in expertise, experience or resources. In order to be able to assess whether the use of a cobot is reasonable, there are already many methods in research with different focuses such as ergonomics, productivity or economic efficiency. However, many methods are not targeted for use by SME, thus still require the involvement of experts, and often only consider economic efficiency without consideration of human-centered aspects. Furthermore, these are mostly not integrated into commonly used process planning tools. This work provides an overview of methods for automated analysis of assembly processes in HRC. We present a method for HRC process analysis with an individual weighting of fatigue, time, costs and safety that can be set depending on an application-specific focus defined by the user. It allows non-experts to perform a process analysis based on the individual weighting and a digital twin of the workstation. An evaluation method developed for this purpose calculates the benefit of a cobot in the analyzed process depending on the preset focus. To keep the effort low, the method includes a workflow to easily create a digital twin of the workplace with sufficient accuracy. In addition to the pre-estimation of the human-cobot process, the method allows an easy planning of collaborative production processes, which is why we suggest a conceptual integration into a process planning and control framework. The proposed approach is demonstrated in an use case by analyzing the potential for introduction of collaborative robots for the production of currently manually assembled solar inverters. [ABSTRACT FROM AUTHOR]

A significant shift from traditional lines to reconfigurable and reprogrammable robotic cells has occurred in Industry 4.0. Collaborative robots can be used for automating several tasks for improving Human-Machine Interface (HMI). The ability of a robot carrying out different tasks is proportional to the tools that it can use, thus it is crucial that robots are equipped with systems enabling efficient tool changing. Therefore, in this paper an automatic tool changer system is proposed. Based on Finite Element Analysis (FEA) of the design and the specifications, a 3D printed prototype was made and tested on a UR 10 Collaborative Robot. [ABSTRACT FROM AUTHOR]

From drug delivery in hospitals to transportation of goods in warehouses, mobile robotic platforms have a wide variety of applications in industry today. The integration of mobile platforms with a manipulator opens up the possibility of more practical applications. However, this also introduces a new problem regarding the localisation accuracy of the platform, which in turn affects the accuracy of the manipulation. This paper details a comparative study of different strategies for improving the accuracy of pick and place tasks using a mobile robotic platform with an integrated arm. These strategies include fine positioning, LiDAR feedback and vision system feedback. [ABSTRACT FROM AUTHOR]

The growing variety of products brings various workpieces, which have complex welding seams that cannot be welded by current welding robots fixed in the welding stations or carried by the gantry. Therefore, this paper proposes a mobile collaborative welding system composed of an AGV (Automated Guided Vehicle) and a 6-DOF (Six-Degree-of-Freedom) collaborative robot. Considering the complex welding seams, a mobile collaborative welding method is proposed. The collaborative welding method includes three steps, i.e., welding seam acquisition, welding seam classification and segmentation, and welding task allocation. The authors present a new approach to acquire the spatial position characteristics of welding seams based on the human-machine collaboration. According to the spatial position characteristics of the welding seams, the welding type identification and classification segmentation can be obtained. Finally, the welding tasks of the robot and AGV can be allocated. [ABSTRACT FROM AUTHOR]

Collaborative robots and personalised human-automation load balancing strategies may be able to empower workers with cognitive disabilities to carry out complex assembly tasks. To design such assembly cells, it is necessary to investigate the human factors associated with this user group in relation to the technology proposed. We present a qualitative pilot user study in which an assembly worker with cognitive disabilities and multidisciplinary experts meet a collaborative robot in the context of routine assembly jobs. We draw requirements for the design of such cells and we contrast them with design requirements for regular workforce. [ABSTRACT FROM AUTHOR]

Collaborative human-robot multi-component systems intended for industrial processes are designed and implemented to meet requirements of productivity in the process and safety in the workplace. If these systems are to gain broad adoption and acceptance in the workplace, it is also essential that they provide the best possible user experience (UX) for the collaborating human worker. This paper reports data from an early-stage qualitative user study with two distinct groups of potential users of collaborative robots in industry: professionals from industry and students in vocational training. Attitudes towards such systems are analyzed, and key concerns and expectations are identified. [ABSTRACT FROM AUTHOR]

The ‘water leak test’ in an automotive final assembly line is often a significant cost factor due to its labour intensive nature. This is particularly the case for premium car manufacturers as each vehicle is watered and manually inspected for leakage. This paper delivers an approach that optimises the efficiency and capability of the test process by using a new automated in-line inspection system whereby thermographic images are taken by a lightweight robot system and then processed to locate the leak. Such optimisation allows the collaboration of robots and manual labour which in turn enhances the capability of the process station. [ABSTRACT FROM AUTHOR]