Augmented Reality (AR), is one of the most promising technology for technical manuals in the context of Industry 4.0. However, the implementation of AR documentation in industry is still challenging because specific standards and guidelines are missing. In this work, we propose a novel methodology for the conversion of existing “traditional” documentation, and for the authoring of new manuals in AR in compliance to Industry 4.0 principles. The methodology is based on the optimization of text usage with the ASD Simplified Technical English, the conversion of text instructions into 2D graphic symbols, and the structuring of the content through the combination of Darwin Information Typing Architecture (DITA) and Information Mapping (IM). We tested the proposed approach with a case study of a maintenance manual of hydraulic breakers. We validated it with a user test collecting subjective feedbacks of 22 users. The results of this experiment confirm that the manual obtained using our methodology is clearer than other templates.

Towards Augmented Reality manuals for Industry 4.0: a methodology

SCURATI, GIULIA WALLY;Francesco Ferrise;Monica Bordegoni
2019-01-01

Abstract

Augmented Reality (AR), is one of the most promising technology for technical manuals in the context of Industry 4.0. However, the implementation of AR documentation in industry is still challenging because specific standards and guidelines are missing. In this work, we propose a novel methodology for the conversion of existing “traditional” documentation, and for the authoring of new manuals in AR in compliance to Industry 4.0 principles. The methodology is based on the optimization of text usage with the ASD Simplified Technical English, the conversion of text instructions into 2D graphic symbols, and the structuring of the content through the combination of Darwin Information Typing Architecture (DITA) and Information Mapping (IM). We tested the proposed approach with a case study of a maintenance manual of hydraulic breakers. We validated it with a user test collecting subjective feedbacks of 22 users. The results of this experiment confirm that the manual obtained using our methodology is clearer than other templates.
2019
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1066023
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