Produced by Wired Brand Lab with IBM | In industries reliant on heavy assets, unexpected challenges like machinery failures are common. How can businesses predict and prevent these issues? Discover how IBM Maximo on AWS empowers companies to shift from reactive to predictive maintenance, harnessing AI-driven alerts to help detect anomalies and swiftly address challenges.

An approach is provided to automate predictive vehicle maintenance. In the approach, a vehicle's information handling system receives vehicle data transmissions from a number of other vehicles in geographic proximity to the vehicle. Both the vehicle and the other vehicles correspond to various vehicle types that are used to identify those other vehicles that are similar to the vehicle. The sets of received vehicle data transmissions that are received to similar vehicles are analyzed with respect to a plurality of vehicle maintenance data corresponding to the vehicle. The analysis of the vehicle data transmissions resulting in predictive vehicle maintenance recommendations pertaining to the first vehicle.

Today, many assets across multiple industries are becoming more instrumented and connected to enterprise platforms to provide additional insight into their health and operation. IDC estimates that Internet of Things (IoT) investment will reach $1.12 trillion in 2023. One important area for many industrial organizations that are focused in using [...]

An approach to enabling predictive maintenance for industrial assets was published on SAS Voices by Sanjeev Heda