A Virtual Environment for Collaborative Inspection in Additive Manufacturing

TL;DR

The paper tackles the challenge of inspecting complex internal AM geometries by introducing a collaborative VR environment that enables multi-user exploration of volumetric CT data with real-time synchronization. Implemented in Unity using a client-server architecture (Photon PUN 2 and Photon Voice 2), it supports VR and spectator modes, with volumetric rendering via UnityVolumeRendering and VTK color maps, and avatars through Ready Player Me. Usability is validated against Nielsen's heuristics, complemented by qualitative feedback from six domain experts, highlighting features like cross-sections, axis slicing, region-of-interest cutouts, and annotations as core capabilities. Findings indicate significant benefits for team communication and inspection workflows in AM, while identifying practical challenges around data privacy, performance, and workflow integration; the work lays groundwork for future integration with AI, digital twins, and MR-based collaboration. Overall, the study presents a promising direction for remote, collaborative AM inspection with potential impact across medical, aerospace, energy, and consumer industries.

Abstract

Additive manufacturing (AM) techniques have been used to enhance the design and fabrication of complex components for various applications in the medical, aerospace, energy, and consumer products industries. A defining feature for many AM parts is the complex internal geometry enabled by the printing process. However, inspecting these internal structures requires volumetric imaging, i.e., X-ray CT, leading to the well-known challenge of visualizing complex 3D geometries using 2D desktop interfaces. Furthermore, existing tools are limited to single-user systems making it difficult to jointly discuss or share findings with a larger team, i.e., the designers, manufacturing experts, and evaluation team. In this work, we present a collaborative virtual reality (VR) for the exploration and inspection of AM parts. Geographically separated experts can virtually inspect and jointly discuss data. It also supports VR and non-VR users, who can be spectators in the VR environment. Various features for data exploration and inspection are developed and enhanced via real-time synchronization. We followed usability and interface verification guidelines using Nielsen's heuristics approach. Furthermore, we conducted exploratory and semi-structured interviews with domain experts to collect qualitative feedback. Results reveal potential benefits, applicability, and current limitations. The proposed collaborative VR environment provides a new basis and opens new research directions for virtual inspection and team collaboration in AM settings.

Figures (2)

• Figure 1: Interaction possibilities with the volumetric data of AM octet lattice structures from the third-person view (top) and first-person view (bottom): (a) the users can use a cross-section plane to explore the dataset from different angles, (b) they can use an axis slicing view to inspect it from a specific axis (axial, coronal, and sagittal), (c) they can explore the region of interest with cutout features, and (d) they can also draw annotations on the dataset.
• Figure 2: Overview of the collaborative VR environment for AM parts inspection. The users can connect to join in the virtual environment either in a remote or shared physical space. While our aim is focused on VR users, non-VR users can also connect in spectator mode. Interactions for data exploration and inspection are synchronized in real time between users. We use a client-server architecture for data and voice synchronization.