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.

Less instrumentation. More insight. Physics-informed virtual sensors are shifting condition monitoring from isolated pilots ...

Scientists from Malaysia and Thailand have developed a novel machine-learning model for predicting the maintenance needs of large-scale solar PV plants. According to a recently published scientific ...

The waste collection industry generated $69 billion in revenue in 2024, accounting for over two-thirds of the total US waste and recycling revenue. Logistics is the cornerstone of this industry, given ...

Predictive maintenance can help manufacturers save on costs by spotting equipment issues early. Companies like Aquant and Gecko Robotics provide AI-powered tools that inform maintenance decisions.

In the era of Industry 4.0, manufacturing is no longer defined solely by mechanical precision; it’s now driven by data, connectivity, and intelligence. Yet downtime remains one of the most persistent ...

Honeywell’s HALO machine learning system predicted pressure disturbances and cycle delays with 12-minute notice, enabling operators to take preventive action before shutdowns occurred. The ...

Post Doc Fellow: AI and Data Systems in Nuclear/Particle Physics, Stellenbosch University In most industries, maintenance is a waiting game. Things are fixed when they break. But in the 21st century, ...