Lessons from adopting robotic in-line quality inspection in the Swedish manufacturing industry

Azamfirei, Victor; Granlund, Anna; Lagrosen, Yvonne

doi:10.1016/j.procs.2022.12.234

Cited by 5 publications

(2 citation statements)

References 23 publications

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“…The application of intelligent technologies to automate industrial processes and thereby to make them more efficient and safe was characteristic of Industry 4.0. Extending the principles of Industry 4.0, Industry 5.0 was marked by a transition to a strong user-centered perspective on technology use (see Psarommatis et al, 2023a ; Azamfirei et al, 2023a ; Konstantinidis et al, 2022b for an overview). Unlike ordinary industrial tools, robots are supposed to perform their given tasks autonomously in a shared environment with human workers.…”

Section: Introductionmentioning

confidence: 99%

“…On the one hand, some technological requirements need to be met: Robots should be capable of localizing themselves with respect to their surroundings. To ensure a comfortable and safe HRI, robots need to adapt to the dynamics of a shared environment (see Konstantinidis et al, 2022a ; Azamfirei et al, 2023a ), which are determined by humans’ activities, intentions, and needs. On the other hand, the humans’ perspective needs to be taken into consideration: Robots should meet potential users’ expectations and needs to evoke positive perceptions (see Bernotat and Eyssel, 2017b ; Bernotat and Eyssel, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

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Remember me - user-centered implementation of working memory architectures on an industrial robot

Bernotat,

Landolfi,

Pasquali

et al. 2023

Front. Robot. AI

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The present research is innovative as we followed a user-centered approach to implement and train two working memory architectures on an industrial RB-KAIROS + robot: GRU, a state-of-the-art architecture, and WorkMATe, a biologically-inspired alternative. Although user-centered approaches are essential to create a comfortable and safe HRI, they are still rare in industrial settings. Closing this research gap, we conducted two online user studies with large heterogeneous samples. The major aim of these studies was to evaluate the RB-KAIROS + robot’s appearance, movements, and perceived memory functions before (User Study 1) and after the implementation and training of robot working memory (User Study 2). In User Study 1, we furthermore explored participants’ ideas about robot memory and what aspects of the robot’s movements participants found positive and what aspects they would change. The effects of participants’ demographic background and attitudes were controlled for. In User Study 1, participants’ overall evaluations of the robot were moderate. Participant age and negative attitudes toward robots led to more negative robot evaluations. According to exploratory analyses, these effects were driven by perceived low experience with robots. Participants expressed clear ideas of robot memory and precise suggestions for a safe, efficient, and comfortable robot navigation which are valuable for further research and development. In User Study 2, the implementation of WorkMATe and GRU led to more positive evaluations of perceived robot memory, but not of robot appearance and movements. Participants’ robot evaluations were driven by their positive views of robots. Our results demonstrate that considering potential users’ views can greatly contribute to an efficient and positively perceived robot navigation, while users’ experience with robots is crucial for a positive HRI.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Remember me - user-centered implementation of working memory architectures on an industrial robot

Bernotat,

Landolfi,

Pasquali

et al. 2023

Front. Robot. AI

View full text Add to dashboard Cite

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Contribution of Industry 4.0 Technologies in Adopting Metrology 4.0 in Manufacturing Industries

Nzumile,

Mahabi,

Taifa

2024

Management and Industrial Engineering

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Exploiting image quality measure for automatic trajectory generation in robot-aided visual quality inspection

Jafari-Tabrizi,

Gruber,

Gams

2024

Int J Adv Manuf Technol

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Currently, the standard method of programming industrial robots is to perform it manually, which is cumbersome and time-consuming. Thus, it can be a burden for the flexibility of inspection systems when a new component with a different design needs to be inspected. Therefore, developing a way to automate the task of generating a robotic trajectory offers a substantial improvement in the field of automated manufacturing and quality inspection. This paper proposes and evaluates a methodology for automatizing the process of scanning a 3D surface for the purpose of quality inspection using only visual feedback. The paper is divided into three sub-tasks in the same general setting: (1) autonomously finding the optimal distance of the camera on the robot’s end-effector from the surface, (2) autonomously generating a trajectory to scan an unknown surface, and (3) autonomous localization and scan of a surface with a known shape, but with an unknown position. The novelty of this work lies in the application that only uses visual feedback, through the image focus measure, for determination and optimization of the motion. This reduces the complexity and the cost of such a setup. The methods developed have been tested in simulation and in real-world experiments and it was possible to obtain a precision in the optimal pose of the robot under 1 mm in translational, and 0.1$$^\circ $$ ∘ in angular directions. It took less than 50 iterations to generate a trajectory for scanning an unknown free-form surface. Finally, with less than 30 iterations during the experiments it was possible to localize the position of the surface. Overall, the results of the proposed methodologies show that they can bring substantial improvement to the task of automatic motion generation for visual quality inspection.

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Lessons from adopting robotic in-line quality inspection in the Swedish manufacturing industry

Cited by 5 publications

References 23 publications

Remember me - user-centered implementation of working memory architectures on an industrial robot

Remember me - user-centered implementation of working memory architectures on an industrial robot

Contribution of Industry 4.0 Technologies in Adopting Metrology 4.0 in Manufacturing Industries

Exploiting image quality measure for automatic trajectory generation in robot-aided visual quality inspection

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