Name
Title | ||
|---|---|---|
Evaluating Prototype Augmented and Adaptive guidance system to support Industrial Plant Maintenance |
Abstract | ||
|---|---|---|
We evaluate AR for Plant maintenance by measuring how a prototype guidance system, tested under representative conditions, impacts performance. We are motivated to determine the cost-benefit of interactive guidance for hazardous, repetitive tasks and we observe an improvement of 21% efficiency, 50% accuracy and 19% reduced task load. AR has already been shown to deliver improvements in task performance, however, there is limited research exploring the integration of AR into complete task routines which presents a barrier to adoption. We apply mixed reality guidance via two within-group experiments. We measure efficiency and accuracy over a complete routine conducted under simulated conditions. Results compare AR versus Static and AR versus Adaptive. We conclude AR is best suited to demanding spatial translation and completion under pressure. We suggest AR offers potential in similar routines and propose further work to integrate in a live setting. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3447526.3472042 | PROCEEDINGS OF 23RD ACM INTERNATIONAL CONFERENCE ON MOBILE HUMAN-COMPUTER INTERACTION (MOBILEHCI 2021): MOBILE APART, MOBILE TOGETHER |
Keywords | DocType | Citations |
Mixed / Augmented Reality, Industrial Augmented Reality | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thomas Bale | 1 | 0 | 0.34 |
| Andrew Calway | 2 | 645 | 54.66 |
| Kirsten Cater | 3 | 163 | 18.41 |
| Chris Bevan | 4 | 23 | 4.53 |
| Robert Skilton | 5 | 0 | 0.34 |
| Tom Scott | 6 | 0 | 0.34 |