Augmented reality (AR) and digital twins are transforming factory and plant maintenance operations, enabling efficiency, cost savings, and improved safety. AR allows instant access to operating procedures, technical documentation, and system data by overlaying digital information onto technicians' views of physical assets. Paired with digital twin simulations of machines and production lines, AR powers more predictive and proactive maintenance strategies.
AR interfaces are intuitive, hands-free tools that connect field technicians with back-end analytics and machine learning infrastructure to guide maintenance tasks. Technicians wearing AR headsets can view holographic step-by-step work instructions overlaid directly on the equipment they are servicing without flipping through paper manuals. They can also access real-time sensor data from machines and quickly diagnose problems aided by remote expertise. AR visualizations help technicians rapidly locate parts, tools, and materials to speed repairs.
Digital twin technology mirrors physical industrial machinery's real-time status and performance in a virtual environment. Machine learning algorithms analyze real-time and historical operating data from equipment sensors to create precise digital models. Plant managers tap into these dynamic digital twins to identify anomalies, emerging maintenance issues, and potential failures before they cause costly downtime.
By pairing AR tools with predictive insights from digital twins, industrial companies can evolve maintenance strategies to be more efficient, automated, and optimized. Technicians have the hands-free visual interactivity needed for complex tasks, while managers gain better visibility and control over maintenance operations.
For example, an automotive plant leveraged AR instructions built from a digital twin simulation of a new production line to enable 30% faster changeovers between model production runs. Technicians used workflow checklists projected onto equipment by AR headsets to ensure each changeover step was sequenced properly. The AR tool taps into the line’s digital twin data to retrieve custom instructions tailored to each model changeover.
Power plants are using similar AR-digital twin integration to enable predictive maintenance. Digital twins analyze sensors, temperature, vibration, and other data to discover potential equipment faults and preemptively trigger maintenance tasks before failures cause downtime. Technicians then perform these predictive repairs directed by AR overlays that provide relevant maintenance history and procedures for the flagged machine components.
The immersive collaboration possible with AR also fosters remote expert support and just-in-time training capabilities. Experienced technicians can annotate what remote workers see in AR to guide repairs and upgrades. Annotations can highlight parts, indicate motion paths showing how to disassemble equipment, or draw arrows to direct attention to obscured button locations.
Maintenance teams benefit from AR visualization overlays for digital twin simulation data to comprehend machine failures more intuitively. Visualizing where heat concentrations grow over time within a motor casing or showing wear growth on a nearly obscured gear system conveys degradation models from digital twins more impactfully.
As companies connect growing volumes of industrial equipment to the Internet of Things, AR, and digital twin technologies will become integral tools to glean insights and drive efficiencies. Gartner research predicts that by 2026, 70% of enterprises will accelerate innovation with digital twins powered by AR and virtual reality (VR), up from under 10% in 2019. The combination of skill-guiding AR overlays for technicians and prognostics from simulations will provide the augmented intelligence needed to keep plant machinery running optimally.