Providing early notice of maintenance issues
When a commercial passenger airplane goes out of service, the money begins to leak. There’s the lost revenue from a giant capital asset idling on the tarmac, the unplanned maintenance hours, and the last minute
rerouting of flight crews and passengers. Likewise, when there’s an issue on an electrical grid or pipeline, a sprawling port or a plant, identifying the affected area, ordering replacement parts on the fly
and placating customers inconvenienced by the problem can tax maintenance staff, strain budgets and lead to inefficient procurement planning.
“Milliseconds are often critical,” says Eduardo Bustamante, COO and CIO of Port of Cartagena, one of the busiest ports in the Americas. Any downtime puts enormous value at stake. The challenge, however, is that
with more than 50 industrial cranes moving shipments from more than 14,000 containers, anticipating where a breakdown may occur is very difficult.
To make that problem easier to solve, some companies with remote and hard-to-reach operations are turning to cognitive solutions. These systems, especially when combined with cloud and sensor technologies, provide
real-time monitoring and predictive analytics that allow managers to track wear-and-tear and schedule downtime and parts in a far more cost-effective manner.
An aerospace company, for instance, is using the enhanced search and analytics capabilities of its cognitive system to improve supply chain visibility and reduce cycle time, saving millions of dollars on critical
parts deliveries. The system lets aircraft technicians search through reams of maintenance records and technical documentation. Now if a worker needs to know what’s causing high hydraulic oil temperatures, the
solution identifies historical cases with similar circumstances, finding patterns that point to the root cause of the overheating. The solution now saves the airline manufacturer $36 million a year.
Cognitive solutions can also help companies determine what skills and parts are needed to address maintenance needs. Because these systems are integrated with a company’s supply chain, they are able to check for
parts and fast-track orders. The self-learning nature of cognitive systems means they get smarter over time, drawing on an expanding network of information, such as enterprise resource planning (ERP) and customer
relationship management (CRM) data, maintenance records, customer calls and more.
At the Port of Cartagena, Bustamente and his team are using their cognitive platform to combine instant and historical views of their operations. The cognitive system they employed allows them to forecast equipment
failures and keep ahead of equipment degradation with needed maintenance. “As a container terminal transshipment hub, our port ships goods to almost 600 ports in 136 countries around the world,” said Bustamente.
“With cognitive capabilities, we gain immediate insight into the health and operations of our more than 47 rubber tire gantries and 180 trucks.” That helped them cut costs and allows Bustamente’s team to keep
vessels and cargo moving smoothly in and out of the port.