Scientists have developed a machine-learning model – utilizing K-Means and long short-term memory techniques – that aims to overcome ‘fault detection and classification’ in the operation and ...

Researchers combined a low-cost IoT monitoring prototype with a Bayesian-optimized XGBoost model that achieved the highest ...

A hybrid framework that turns voltage and current measurements into resistance-based statistical features enabled Random ...

Predictive maintenance is widely considered to be the obvious next step for any business with high-capital assets looking to harness machine learning to minimize equipment maintenance costs.

Boost asset ROI with AI-driven predictive maintenance, cloud-native APM, IIoT and digital twins that cut downtime, optimize costs and extend equipment lifeDublin, Oct. (GLOBE NEWSWIRE) -- "Asset ...

Overview: AI detects early signs of machine faults through sensor data and helps prevent unexpected breakdowns.Predictive maintenance helps factories reduce dow ...

The global predictive maintenance market is projected to grow from USD 9.71 billion in 2026 to USD 16.74 billion by 2031, at an 11.5% CAGR. Growth is driven by industrial IoT, AI, machine learning, ...

Equipment maintenance is essential for avoiding unplanned downtime and preserving quality standards in multiple industries such as power generation, oil & gas and manufacturing. In the past and in ...

Traditional vibration analysis falls short for slow-speed machinery. Augury’s AI-powered platform uses high-frequency ultrasound to deliver real-time diagnostics and predictive insights for low-RPM ...

What is predictive maintenance (PdM)? It’s the application of instrumentation and intelligence to help determine the condition of equipment and whether maintenance should be performed to avoid ...

For the industrial manufacturers, unplanned downtime continues to be a major concern. ARC estimates that unplanned downtime costs the industrial and manufacturing sector over a trillion dollars a year ...