Dynamic Mixed Reality Assembly Guidance Using Optical Recognition Methods

Augmented (AR) and Mixed Reality (MR) technologies are enablers of the Industry 4.0 paradigm and are spreading at high speed in production. Main applications include design, training, and assembly guidance. The latter is a pressing concern, because assembly is the process that accounts for the bigge...

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Bibliographic Details
Published in:Applied sciences Vol. 13; no. 3; p. 1760
Main Authors: Maffei, Antonio, Dalle Mura, Michela, Monetti, Fabio Marco, Boffa, Eleonora
Format: Journal Article
Language:English
Published: Basel MDPI AG 2023
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ISSN:2076-3417, 2076-3417
Online Access:Get full text
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Summary:Augmented (AR) and Mixed Reality (MR) technologies are enablers of the Industry 4.0 paradigm and are spreading at high speed in production. Main applications include design, training, and assembly guidance. The latter is a pressing concern, because assembly is the process that accounts for the biggest portion of total cost within production. Teaching and guiding operators to assemble with minimal effort and error rates is pivotal. This work presents the development of a comprehensive MR application for guiding novice operators in following simple assembly instructions. The app follows innovative programming logic and component tracking in a dynamic environment, providing an immersive experience that includes different guidance aids. The application was tested by experienced and novice users, data were drawn from the performed experiments, and a questionnaire was submitted to collect the users’ perception. Results indicate that the MR application was easy to follow and even gave confidence to inexperienced subjects. The guidance support was perceived as useful by the users, though at times invasive in the field of view. Further development effort is required to draw from this work a complete and usable architecture for MR application in assembly, but this research forms the basis to achieve better, more consistent instructions for assembly guidance based on component tracking.
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ISSN:2076-3417
2076-3417
DOI:10.3390/app13031760