Enhancing Manufacturing Engineering Higher Education Through Mixed Reality and Gaussian Splatting: Preliminary Experimental Results

Abstract

The integration of Mixed Reality (MR) technologies into higher manufacturing-engineering education can contribute to face the challenges of providing hands-on training with real manufacturing systems. This paper explores the potential of MR combined with Gaussian Splatting (GS) to create high-fidelity digital replicas of industrial machinery (e.g., lathes, milling machines, etc.), enhancing students’ understanding of manufacturing processes. GS is emerging as a breakthrough technique for real-time rendering of objects and environments. By delineating the scene as the realisation of an object in a defined temporal state, GS methodology represents a 3D high-fidelity digital scene as a collection of 3D Gaussian ellipsoids characterised by position, geometry, shape, colour and opacity. The integration of MR with GS allows trainees to engage with realistic virtual models, simulating a physical presence in a machining workshop. The capacity to digitally manipulate and analyse individual objects enhances the learning experience, addressing logistical and safety constraints by providing a risk-free and accessible training environment. A lathe is used as a case study, and the GS-based digital scene is compared with conventional CAD-based model in terms of qualitative performance