SAS Predictive Asset Maintenance reduces downtime, revenue losses

Oil and gas companies, utilities, manufacturers see profits grow, safety increase when maintenance is optimised

For capital-intensive industries like high-tech manufacturing, oil and gas production and fleet management, even a short downtime caused by asset failure means huge revenue losses. Predictive analytics from SAS helps companies that depend on assets like production equipment pinpoint the best times to conduct routine maintenance and avoid costly disruptions. Companies such as Saudi Aramco, POSCO and Ryder already recognise the business benefits of asset optimisation with SAS, the leader in business analytics software and services.

Recent enhancements to SAS Predictive Asset Maintenance software offer expanded visual data exploration, a powerful knowledge repository and auditable work-order tracking. This means companies can extend the life of expensive assets without increasing the likelihood of equipment failures.

“At Shell Upstream Americas, Deepwater in New Orleans, Shell is using the SAS Predictive Asset Maintenance solution to address some of our most sophisticated surveillance challenges in the Gulf of Mexico,” said Brian Wans, Shell project manager. “Implementation of SAS Predictive Asset Maintenance offers Shell a competitive advantage by predicting and explaining performance anomalies in ultradeep water production lift systems, allowing Shell to make better, more informed decisions that positively impact Shell by limiting equipment damage, increasing runtime, and reducing production deferrals.”

Traditional and time-consuming manual asset monitoring primarily supports only reactive maintenance. SAS Predictive Asset Maintenance analyses millions of data points to uncover patterns that point to future asset failure. Using SAS, companies gain competitive advantage by maximising resources to meet operational and profit goals and comply with safety and environmental mandates.

“The evolution of reliability engineering has driven the need for highly analytical solutions that exceed traditional asset management systems,” said Reinhard Hoene, senior product manager at SAS. “With early and detailed data, engineers have more options for problem resolution – allowing them to choose a course that is optimal for the company and its customers.”

SAS Predictive Asset Maintenance combines powerful data integration, visualisation, descriptive and predictive analytics and business intelligence to create an unbiased, big-picture view of asset performance. These capabilities improve uptimes while optimising maintenance costs and asset life cycles by predicting events that cause outages. Future asset or process failures are easier to solve because prior mitigation efforts are recorded in a centralised knowledge repository, facilitating speedy root cause analysis.


SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions, SAS helps customers at more than 55,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world THE POWER TO KNOW.