Slashing unnecessary maintenance visits by 50% at an oil and gas customer through data-driven insights.
Challenge
The customer was over maintaining their seawater and freshwater pumps, resulting in unnecessary site visits to check equipment health and escalating maintenance costs. They had previously attempted to find a solution with other vendors but were unsuccessful in gaining meaningful insights from their data. Staff were also skeptical that valuable information could be extracted from their existing data.
Solution
Arundo's data science team analyzed the customer's data and identified patterns indicative of pumps operating outside of normal parameters. By correlating these patterns across the fleet and applying anomaly detection models, engineers were able to determine which pumps were most likely in need of maintenance and estimate their remaining useful life (RUL). An "at a glance" dashboard was created, allowing engineers to quickly and easily identify pumps requiring attention.
Impact
The implementation of Arundo’s solution led to a 50% reduction in unnecessary maintenance visits, resulting in significant cost savings for the customer.
