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2023 | OriginalPaper | Buchkapitel

Machine Vision Systems for Collaborative Assembly Applications

verfasst von : Vladyslav Andrusyshyn, Vitalii Ivanov, Ján Pitel’, Kamil Židek, Peter Lazorik

Erschienen in: Advances in Design, Simulation and Manufacturing VI

Verlag: Springer Nature Switzerland

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Abstract

The collaboration of robots with workers in production is one of the most discussed topics within the framework of the Industry 4.0 concept. Collaborative production cells have increased flexibility and adaptability to production conditions because of combining the advantages of a human and a robot and expand the list of tasks that can be automated. However, the widespread adoption of collaborative robots in manufacturing is hampered by open questions about the safety of workers and ease of use. Machine vision systems allow collaborative robots to work more closely with the environment and endow them with basic cognitive functions. That is why this article is devoted to analyzing the use of machine vision systems in modern collaborative assembly cells. The authors analyzed scientific works in machine vision systems, described practical examples of their application, and catalogs of popular manufacturers to evaluate current propositions in machine vision systems. As a result, the main areas of application of machine vision systems were formed, their classification was presented, and recommendations for choosing an optimal machine vision system were proposed. In addition, the obtained recommendations were used in the practical case when analyzing the equipment of the collaborative assembly line of the SmartTechLab laboratory of the Faculty of Manufacturing Technologies of the Technical University in Kosice.

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Titel: Machine Vision Systems for Collaborative Assembly Applications
verfasst von: Vladyslav Andrusyshyn
Vitalii Ivanov
Ján Pitel’
Kamil Židek
Peter Lazorik
Verlag: Springer Nature Switzerland
Buch: Advances in Design, Simulation and Manufacturing VI
Print ISBN: 978-3-031-32766-7

Electronic ISBN: 978-3-031-32767-4

Copyright-Jahr: 2023
DOI: https://doi.org/10.1007/978-3-031-32767-4_2

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