Development of a Metaverse-Based Training Tool Using Failure Modes, Effects, and Criticality Analysis: FMECA-VR-0.1 Prototype Applied to a Wind Farm

This study presents the development of an immersive training platform based on the Metaverse concept, aimed at enhancing the training of maintenance personnel in foundational reliability and maintenance engineering methodologies. The proposed tool, FMECA-VR-0.1 (Failure Modes, Effects and Criticality Analysis – Virtual Reliabil-ity-0.1), integrates two key techniques—Qualitative Risk Criticality Matrix (QRCM) and Failure Modes, Effects and Criticality Analysis (FMECA)—to support the optimi-zation of maintenance plans for physical assets. The project is structured in two phas-es: the conceptual design of the tool based on the Maintenance Management Model (MMM) developed by INGEMAN, and the development of an immersive digital pro-totype within a virtual reality environment. The training environment allows users to explore and practice reliability techniques in a realistic and safe virtual setting. A case study was conducted on a wind turbine from the Valle de los Vientos Wind Farm in Chile. Results indicate that virtual environments significantly improve training out-comes by reducing learning time, minimizing human errors, and enhancing reliability and maintainability indicators. The FMECA-VR-0.1 tool represents a milestone in the digital transformation of technical training in maintenance, offering an adaptable so-lution for various industrial contexts. Its immersive approach, combined with engi-neering-based analysis, reinforces human capabilities and contributes to the lifecycle optimization of key maintenance processes.