ShipXpress, cloud-based supply chain software solutions, in a recent official announcement enters into an agreement with SparkCognition the cognitive security analytics company.

The partnership between these firms will integrates ShipXpress’ software solutions with SparkCognition’s sophisticated Machine Learning platform to detect problems and predict failures for railcars. The offering allows rail shippers to better manage their railcars by accurately forecasting which railcars have the highest likelihood of making a trip without any need for maintenance along the way. This will bring about cost and time efficiency by scheduling maintenance before cars are bad ordered and avoiding railcars which may breakdown during individual trips.

“Together, we aim to change the way the railway industry deals with logistics and prognostics issues by enabling heightened efficiency and increasing effectiveness," says Raghu Misra, CTO of ShipXpress.

SparkCognition’s predictive algorithms automatically build models for each railcar based on the railcar’s history, mileage, previous routes, the distance being traveled, the time of year, seasonal environmental conditions, the speed of the train, and the load percentage of each individual railcar.

“With our automated-model building capabilities, we are democratizing the use of Analog Big Data in large-scale industrial prognostics applications, such as those relevant for the railcar industry,” states Usman Shuja, Vice President of Market Development at SparkCognition. “Effectively, we are delivering next-generation AI and Machine Learning technology that solves high-value problems for our customers today.”