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

• Published in: Robotics and computer-integrated manufacturing Vol. 59; pp. 305 - 316
• Main Authors: Roldán, Juan Jesús, Crespo, Elena, Martín-Barrio, Andrés, Peña-Tapia, Elena, Barrientos, Antonio
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.10.2019; Elsevier BV
• Subjects: Algorithms; Assemblies; Assembly; Cloud computing; Data analysis; Industrial applications; Industry 4.0; Information management; Mining industry; Operators; Process mining; Toys; Training; Training system; Virtual reality; Process mining; Training system; Industry 4.0; Assemblies; Virtual reality
• ISSN: 0736-5845; 1879-2537; 1879-2537
• DOI: 10.1016/j.rcim.2019.05.004

•An immersive training system for industrial operators in complex assemblies is developed.•It uses virtual reality to reproduce the work environment and process mining to collect and store the knowledge of operators.•The experiments show that its performance is equal or better than a paper guide in all the assemblies.•The user evaluations of the system are better in terms of mental demand, perception, learning, results and performance. Industry 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.