Manufacturing and Materials
Permanent URI for this collection
Browse
Browsing Manufacturing and Materials by Author "Ariansyah, Dedy"
Now showing 1 - 3 of 3
Results Per Page
Sort Options
Item Open Access A head mounted augmented reality design practise for maintenance assembly(Cranfield University, 2021-08-18 17:03) Ariansyah, DedyThis is the experimental data used to examine the impact of different AR HMD modalities on task performance, system usability, and user safetyItem Open Access Data: A Design Framework for Adaptive Digital Twins(Cranfield University, 2023-09-04 09:26) ahmet Erkoyuncu, John; Fernández del amo blanco, Iñigo; Ariansyah, Dedy; Bulka, Dominik; Vrabič, Rok; Roy, RajkumarThis paper develops a new DT design framework that uses ontologies to enable co-evolution with the CES by capturing data in terms of variety, velocity, and volume across the asset life-cycle. The framework has been tested successfully on a helicopter gearbox demonstrator and a mobile robotic system across their life cycles, illustrating DT adaptiveness without the data architecture needing to be modified. The data presented in this portal is related to the data that was generated in the validation process.Item Open Access Data: Fast Augmented Reality Authoring: Fast Creation of AR step-by-step Procedures for Maintenance Operations(Cranfield University, 2023-08-14 14:15) Palmarini, Riccardo; Fernandez Del Amo Blanco, Inigo; Ariansyah, Dedy; Khan, Samir; ahmet Erkoyuncu, John; Roy, RajkumarAugmented Reality (AR) has shown great potential for improving human performance in Maintenance, Repair, and Overhaul (MRO) operations. Whilst most studies are currently being carried out at an academic level, the research is still in its infancy due to limitations in three main aspects: limited hardware capabilities, the robustness of object recognition, and content-related issues. This article focuses on the last point, by proposing a new geometry-based method for creating a step-by-step AR procedure for maintenance activities. The Fast Augmented Reality Authoring (FARA) method assumes that AR can recognise and track all the objects in a maintenance environment when CAD models are available, to knowledge transfer to a non-expert maintainer. The novelty here lies in the fact that FARA is a human-centric method for authoring animation-based procedures with minimal programming skills and the manual effort required. FARA has been demonstrated, as a software unit, in an AR system composed of commercially available solutions and tested with over 30 participants. The results show an average time saving of 34.7% (min 24.7%; max 55.3%) and an error reduction of 68.6% when compared to the utilisation of traditional hard-copy manuals. Comparisons are also drawn from performances of similar AR applications to illustrate the benefits of procedures created utilising FARA.