SIGNAL 3: Improving Shelf Life of Fleets Through Predictive Maintenance
Time is money. For freight rails and trucks, responsible for the movement of commercial goods from one place to other, even more so. But machines do not schedule a reminder before breaking down. GE estimates that the rail industry alone loses upward of $400 million per year because of maintenance failures and their resulting downtime.
Enter data science and embedded systems. Integrating a predictive maintenance pipeline into the transportation and logistics industry could counteract the problem by providing real-time updates about the overall health of the vehicle. The sensors installed over the vehicles ensure accurate data collection making it easier to anticipate an internal failure and address the situation ASAP. Predictive maintenance also helps logistics companies by:
1. revealing how fuel efficiency can be increased.
For example, the University of Nebraska-Lincoln research revealed that constantly monitoring and optimizing one single commercial truck’s tire pressure could save $2,400 in fuel consumption per year.
2. plan on the road repairs, thereby eliminating the need for centralised hubs:
Real-time updates on weather and traffic allow them to be better prepared.
Advances in IoT and processing power can thus improve productivity and efficiency of fleets through educated optimizations with data.
