Evaluating AR-Based Repair Guidance for Faster and More Accurate Maintenance Work
DOI:
https://doi.org/10.22399/ijcesen.5544Keywords:
Augmented Reality, Maintenance, Repair Guidance, Industrial Systems, Human FactorsAbstract
The use of Augmented Reality (AR) has become one of the groundbreaking technologies in the field of industrial maintenance, providing novel ideas of enhancing repair tasks via efficiency and precision. In this paper, the author provides an extensive examination of AR-based repair guidance systems and their effect on maintenance performance in the specifics of time to task completion and the decreased number of errors. More time and errors are made in traditional methods of maintenance, as they are extremely human-based and expert-based, with less real-time support provided. This type of maintenance leads to more downtimes. On the contrary, AR systems offer interactive guidance, context-aware information, overlaying digital information directly on physical equipment to help technicians work more efficiently. The review analyzes the basic concepts of AR, diverse categories of AR-based maintenance systems, and how they are used in the industrial setting. It also reviews research articles providing empirical evidence of a substantial increase in the speed of maintenance process, the accuracy of the procedure, and training efficiency with the AR-based guidance. The paper will also include discussion of other key human factors like cognitive load, ergonomics as well as user acceptance and technical issues that include accuracy of tracking, system integration and cost of implementation. The future of the AR in providing predictive and intelligent maintenance systems is also examined, with regards to the emerging trends that include the use of AR with Artificial Intelligence (AI), Internet of Things (IoT), and digital twins. Altogether, the results reveal that AR-based guidance in repairs can have great benefits on the maintenance processes, but more research and development are needed to eliminate the current limitations and make it possible to apply the guidance to large-scale industrial use.
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