A Framework for Automatic Generation of Augmented Reality Maintenance & Repair Instructions based on Convolutional Neural Networks
Dimitris Mourtzis, John Angelopoulos, Nikolaos Panopoulos
Abstract
In modern manufacturing world, MRO (Maintenance and Repair Operations) are the cornerstone for keeping industrial equipment in near-optimum condition. Successful completion of MRO has been benefited from Augmented Reality (AR), by considerably decreasing MTTR (Mean Time to Repair). To that end, AR delivers the digital tools that help on-the-field technicians to perform MRO easily and intuitively, however intense development is required for generating AR instructions. The latest advances in computer technologies, concretely in Convolutional Neural Networks, have enabled advanced computer vision. This research paper presents a framework for generating AR maintenance instructions, based on advanced computer vision and Convolutional Neural Networks (CNN). The applicability of the framework is tested in-vitro in a lab-based machine shop.