journal article·2020-05-24Open access

Digital Twin and Virtual Reality Based Methodology for Multi-Robot Manufacturing Cell Commissioning

Luis Pérez, Silvia Rodríguez-Jiménez, Nuria Rodríguez, Rubén Usamentiaga, Daniel F. García

Applied Sciences· Volume 10· Issue 10

Abstract

Intelligent automation, including robotics, is one of the current trends in the manufacturing industry in the context of “Industry 4.0”, where cyber-physical systems control the production at automated or semi-automated factories. Robots are perfect substitutes for a skilled workforce for some repeatable, general, and strategically-important tasks. However, this transformation is not always feasible and immediate, since certain technologies do not provide the required degree of flexibility. The introduction of collaborative robots in the industry permits the combination of the advantages of manual and automated production. In some processes, it is necessary to incorporate robots from different manufacturers, thus the design of these multi-robot systems is crucial to guarantee the maximum quality and efficiency. In this context, this paper presents a novel methodology for process automation design, enhanced implementation, and real-time monitoring in operation based on creating a digital twin of the manufacturing process with an immersive virtual reality interface to be used as a virtual testbed before the physical implementation. Moreover, it can be efficiently used for operator training, real-time monitoring, and feasibility studies of future optimizations. It has been validated in a use case which provides a solution for an assembly manufacturing process.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Digital Transformation in Industry · Flexible and Reconfigurable Manufacturing Systems · Manufacturing Process and Optimization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Fundación IDONIAL, Avda. Jardín Botánico 1345, 33203 Gijón (Asturias), Spain

Universidad de Oviedo, Campus de Viesques, 33204 Gijón (Asturias), Spain

Funding

Gobierno del Principado de Asturias

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