Predictive Maintenance

Digital Twins for Industrial Robots: Architecture, Modeling Choices, and the Path to Predictive Maintenance

A digital twin for an industrial robot is a high-fidelity simulation that mirrors the physical machine, enabling predictive maintenance by detecting deviations and simulating fault conditions. The most practical approach combines physics-based modeling for generating synthetic fault data with data-driven machine learning for real-time monitoring, overcoming the challenge of scarce real-world fault data.