The Nokia difference
We live in a customer-driven, on-demand economy. Shipments of goods have become smaller, more frequent, and widely distributed. Demand is more volatile with wider seasonal swings, creating uncertainty for logistics providers and pressure for freight companies to deliver more in less time. Customer tolerance for services downtime is lower than ever before. Businesses have to do more, faster, with fewer resources, and Nokia’s machine learning operations analytics can make it happen.
Optimize transport networks
Optimized and more predictable operations are essential to transport networks. Rail velocity must be maintained, dangerous conditions like flooding predicted, and cargo condition tracked. Nokia solutions include Water Events Prediction, an advanced analytics solution that understands how severe weather will generate water flows into culverts and across rail tracks, predicting risk of derailment up to 72 hours in advance.
If assets are down, business is lost. Nokia asset analytics goes beyond predictive maintenance with real-time optimization of maintenance and repair schedules to extend the life of assets and minimize downtime.
Nokia uses reinforcement learning for hub operations analytics to optimize throughput continuously and align capacity with demand. Hub operations software optimizes for multiple constraints such as service level by product, available workforce, and system capacity. Arrivals and departures are tracked in real time, spatio-temporal queueing of products throughout the hub is maintained, and goods are dynamically reassigned to transport.
Operations analytics optimizes operations for: