Ensuring inspection performance is not a trivial design problem, because inspection is a complex and difficult task that tends to be error-prone, whether performed by human or by automated machines. Due to economical or technological reasons, human inspectors are responsible for inspection functions in many cases. Humans, however, are rarely perfect. A system of manual inspection was found to be approximately 80-90% effective, thus allowing non-confirming parts to be processed (Harris & Chaney, 1969; Drury, 1975). As the attributes of interest or the variety of products increases, the complexity of an inspection task increases. The inspection system becomes less effective because of the sensory and cognitive limitations of human inspectors. Any means that can support or aid the human inspectors is necessary to compensate for inspection difficulty.
Augmented reality offers a new approach in designing an inspection system as a means to augment the cognitive capability of inspectors. To realize the potential benefits of AR, however the design of AR-aided inspection requires a through understanding of the inspection process as well as AR technology. The cognitive demands of inspection and the capabilities of AR to aid inspectors need to be evaluated to decide when and how to use AR for a dimensional inspection.
The objectives of this study are to improve the performance of a dimensional inspection task by using AR and to develop guidelines in designing an AR-aided inspection system. The performance of four inspection methods (i.e., manual, 2D-aided, 3D-aided, and AR-aided inspections) was compared in terms of inspection time and measurement accuracy. The results suggest that AR might be an effective tool that reduces inspection time. However, the measuring accuracy was basically the same across all inspection methods. The questionnaire results showed that the AR and 3D-aided inspection conditions are preferred over the manual and 2D-aided inspection. Based on the results, four design guidelines were formed in using AR technology for a dimensional inspection. / Ph. D.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/26326 |
| Date | 03 April 2002 |
| Creators | Chung, Kyung Ho |
| Contributors | Industrial and Systems Engineering, Williges, Robert C., Shewchuk, John P., Pesante-Santana, Jose A., Kleiner, Brian M., Hix, Deborah S. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
| Relation | AR.pdf |
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