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Título

A training system for Industry 4.0 operators in complex assemblies based on virtual reality and process mining

AutorRoldán, Juan Jesús; Crespo, Elena; Martín-Barrio, Andrés; Peña-Tapia, Elena; Barrientos, Antonio CSIC ORCID
Palabras claveIndustry 4.0
Training system
Assemblies
Virtual reality
Process mining
Fecha de publicación10-may-2019
EditorPergamon Press
CitaciónRobotics and Computer-Integrated Manufacturing 59: 305-316 (2019)
ResumenIndustry 4.0 aims at integrating machines and operators through network connections and information management. It proposes the use of a set of technologies in industry, such as data analysis, Internet of Things, cloud computing, cooperative robots, and immersive technologies. This paper presents a training system for industrial operators in assembly tasks, which takes advantage of tools such as virtual reality and process mining. First, expert workers use an immersive interface to perform assemblies according to their experience. Then, process mining algorithms are applied to obtain assembly models from event logs. Finally, trainee workers use an improved immersive interface with hints to learn the assemblies that the expert workers introduced in the system. A toy example has been developed with building blocks and tests have been performed with a set of volunteers. The results show that the proposed training system, based on process mining and virtual reality, is competitive against conventional alternatives. Furthermore, user evaluations are better in terms of mental demand, perception, learning, results, and performance.
Versión del editorhttps://doi.org/10.1016/j.rcim.2019.05.004
URIhttp://hdl.handle.net/10261/216057
DOI10.1016/j.rcim.2019.05.004
ISSN0736-5845
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