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Robotic Automation
The Infosys Aerospace and Defense practice integrates robotic automation in assembly stations, maintenance hangars, and logistics facilities. We establish a digital backbone for implementation of automation solutions, including robots, drones, self-driving vehicles, and additive manufacturing. Vertical integration (from sensors to the shop floor and enterprise) and horizontal integration across the product lifecycle (from design, engineering and manufacturing to supply chain operations) synchronizes processes as well as information flows for 'smart' manufacturing.
Our robotic automation solutions enhance manufacturing by ensuring positional accuracy, addressing tolerance levels of measurements, and facilitating quality inspection of metallic and composite components. Automation boosts Maintenance, Repair and Overhaul (MRO) service efficiency by reducing Mean Time To Repair (MTTR) of critical assets and simplifying surface inspection in the event of aircraft damage. Further, automated systems for assembling aircraft structures minimize tooling requirements and reduce turnaround times while ensuring industrial safety.
Infosys develops deep learning models that detect features / objects and identify damages such as surface cracks, missing components, and erosion / distortion of structural parts. We combine deep learning with computer vision techniques to train algorithms for inspection and reporting of damaged/defective components in color-coded formats.
Our autonomous golf cart platform for in-campus movement capitalizes on autonomous navigation, path planning, lane discipline, obstacle detection, and localization and mapping technologies. Our autonomous vehicle diagnostic framework supports Vehicle to Vehicle (V2V), Vehicle to Network (V2N), Vehicle to Infrastructure (V2I), and Vehicle to Pedestrian (V2P) communication, which drives superior collision avoidance systems.
White paper: Infosys develops engineering services framework for 3D printing
Our tool identifies candidate aircraft parts for additive manufacturing. A proof of concept demonstrates technical feasibility and profitability.
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