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RISUncertainty-Aware Digital Twins: Robust Model Predictive Control Using Time-Series Deep Quantile Learning
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Abstract. Digital twins, virtual replicas of physical systems that enable real-time monitoring, model updates, predictions, and decision-making, present novel avenues for proactive control strategies for autonomous systems. ...
A Digital Twin Framework Utilizing Machine Learning for Robust Predictive Maintenance: Enhancing Tire Health Monitoring
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: We introduce a novel digital twin (DT) framework for the predictive maintenance of long-term physical systems. Using monitoring tire health as an application, we show how the DT framework can be used to enhance automotive ...
A Digital Twin Framework Utilizing Machine Learning for Robust Predictive Maintenance: Enhancing Tire Health Monitoring
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: We introduce a novel digital twin (DT) framework for the predictive maintenance of long-term physical systems. Using monitoring tire health as an application, we show how the DT framework can be used to enhance automotive ...
A Machine Learning–Based Tire Life Prediction Framework for Increasing Life of Commercial Vehicle Tires
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: In the commercial freight industry, tire retreading decisions are often conservative due to limited knowledge of a tire’s remaining service life. This practice leads to increased costs and material waste. This paper proposes ...