Predictive maintenance techniques powered by artificial intelligence (AI) are helping enterprises across industries to find patterns that can avoid machine failures.

Unlike AI, traditional business intelligence systems are not designed to handle huge volumes of industrial Internet of Things (IoT) data, says data analytics company GlobalData.

“Predictive maintenance is a key cost-saving digital strategy for any enterprise. AI-powered predictive maintenance can help enterprises save money and time on maintenance and machine downtime while extending the life of heavy equipment,” says GlobalData disruptive tech analyst Venkata Naveen.

The Innovation Explorer Database of GlobalData’s Disruptor Intelligence Center reveals how predictive maintenance is increasingly becoming crucial across the value chains of various industries such as automotive, manufacturing, oil and gas, mining, power and aerospace.

In terms of manufacturing, Mitsubishi Electric has developed AI-based diagnostic technology that harnesses machine learning algorithms to analyse the sensor data of machines and generate a model of the machine’s transition between different operational states.

The model is then used to set optimal conditions for detecting abnormalities of a machine during each operational state, enabling operators to gauge signs of machinery failure before actual breakdowns.

In terms of mining, Agnico Eagle Mines has partnered with Montreal’s Newtrax Technologies to predict mobile equipment maintenance issues before they happen using AI algorithms to the IoT sensors data.

Newtrax helped Agnico Eagle to analyse an engine that has shown signs of a potential issue, which helped the mining company to save $63 610 in repairs and replacement of the engine.

Instead of developing a digital predictive maintenance system from scratch, enterprises are partnering with startups in the space to deploy their predictive AI solutions off-the-shelf.

“One of the critical challenges for predictive maintenance is streamlining the flow of data from machines to a central system with a low level of latency and high security, which can be overcome given the advancements in fifth-generation connectivity and cybersecurity.

"Despite the stumbling blocks, predictive maintenance is a vital part of an enterprise’s digital transformation strategy,” says Naveen.