MARMA: A Mobile Augmented Reality Maintenance Assistant for Fast-Track Repair Procedures in the Context of Industry 4.0
Open Access
Abstract
The integration of exponential technologies in the traditional manufacturing processes constitutes a noteworthy trend of the past two decades, aiming to reshape the industrial environment. This kind of digital transformation, which is driven by the Industry 4.0 initiative, not only affects the individual manufacturing assets, but the involved human workforce, as well. Since human operators should be placed in the centre of this revolution, they ought to be endowed with new tools and through-engineering solutions that improve their efficiency. In addition, vivid visualization techniques must be utilized, in order to support them during their daily operations in an auxiliary and comprehensive way. Towards this end, we describe a user-centered methodology, which utilizes augmented reality (AR) and computer vision (CV) techniques, supporting low-skilled operators in the maintenance procedures. The described mobile augmented reality maintenance assistant (MARMA) makes use of the handheld’s camera and locates the asset on the shop floor and generates AR maintenance instructions. We evaluate the performance of MARMA in a real use case scenario, using an automotive industrial asset provided by a collaborative manufacturer. During the evaluation procedure, manufacturer experts confirmed its contribution as an application that can effectively support the maintenance engineers.Keywords
This publication has 47 references indexed in Scilit:
- A systematic review of augmented reality applications in maintenanceRobotics and Computer-Integrated Manufacturing, 2018
- Methodological Proposal for Use of Virtual Reality VR and Augmented Reality AR in the Formation of Professional Skills in Industrial Maintenance and Industrial Safety2017
- Demand Analysis for an Augmented Reality based Assembly Training2017
- A review of using Augmented Reality in Education from 2011 to 20162016
- You Only Look Once: Unified, Real-Time Object Detection2016
- Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative ReviewSensors, 2016
- A Cloud-based Approach for Maintenance of Machine Tools and Equipment Based on Shop-floor MonitoringProcedia CIRP, 2016
- Modeling cost benefit analysis of inspection in a production lineInternational Journal of Production Economics, 2014
- Color-Based Monocular Visuoinertial 3-D Pose Estimation of a Volant RobotIEEE Transactions on Instrumentation and Measurement, 2010
- Learning to track colored objects with log-polar visionMechatronics, 2004