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RiDTwin: XR-First Operator Support and Maintenance for Textile Manufacturing with AR, VR and an Intelligent Virtual Assistant

Author

Listed:
  • André Costa

    (IPVC-Instituto Politécnico de Viana do Castelo, 4900-347 Viana do Castelo, Portugal)

  • João Miranda

    (IPVC-Instituto Politécnico de Viana do Castelo, 4900-347 Viana do Castelo, Portugal)

  • João Mirra

    (IPVC-Instituto Politécnico de Viana do Castelo, 4900-347 Viana do Castelo, Portugal)

  • Nuno Dinis

    (Riopele, 4770-405 Pousada de Saramagos, Portugal)

  • Luís Romero

    (IPVC-Instituto Politécnico de Viana do Castelo, 4900-347 Viana do Castelo, Portugal)

  • Pedro Miguel Faria

    (IPVC-Instituto Politécnico de Viana do Castelo, 4900-347 Viana do Castelo, Portugal)

Abstract

This article presents an integrated approach that combines Virtual Reality (VR), Augmented Reality (AR), and an Intelligent Virtual Assistant (IVA) to support training, on-the-job assistance, and maintenance in a textile manufacturing environment. The solution spans three systems: RioRV, a Unity-based VR platform for immersive, step-by-step procedure rehearsal, instructional videos, and simplified 3D animations; RiAR, a mobile AR application for assisted maintenance and access to real-time and historical machine data using marker-based (VuMark) identification; and Ria, a web-based IVA that delivers document-grounded answers, operational queries over a secure plant API, short-horizon forecasting, and a narrow set of guarded remote actions. The architecture prioritizes human-centered Industry 5.0 principles—safety, usability, and resilience—by enabling operators to learn procedures in VR, execute tasks with AR overlays and maintenance media at the workstation, and obtain concise, source-cited guidance via the IVA without leaving immersion. In the case study with a spinning section at RIOPELE, the convergence of VR, AR, and IVA reduced reliance on bulky manuals, shortened time-to-information for machine status, and established a feedback loop in which training and operational experience continuously enrich the knowledge base.

Suggested Citation

  • André Costa & João Miranda & João Mirra & Nuno Dinis & Luís Romero & Pedro Miguel Faria, 2026. "RiDTwin: XR-First Operator Support and Maintenance for Textile Manufacturing with AR, VR and an Intelligent Virtual Assistant," Future Internet, MDPI, vol. 18(6), pages 1-33, June.
  • Handle: RePEc:gam:jftint:v:18:y:2026:i:6:p:330-:d:1969785
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