Pratt & Whitney applies ‘Big Data’ to predict engine maintenance frequency and planning

Pratt & Whitney has developed a new modeling and predictive tool to enhance its maintenance service offerings and increase customer value. Expanding its data analytics capabilities, Pratt & Whitney’s Big Data project leverages its deep engine design understanding with broad operational, maintenance and environmental data, such as flight length and the environment in which the engine is operated, to determine the impact of these combined factors to refine the predictability of average time between heavy maintenance shop visits. Advanced predictive modeling, combined with innovative maintenance practices, will enable Pratt & Whitney to reduce unplanned engine removals and optimize engine time on wing. This benefits both customers, through improved operational availability, and Pratt & Whitney, through cost reductions across the life of its fleet management agreements. With more than 10,500 active, installed large commercial engines flying around the world, Pratt & Whitney has been collecting and studying enormous amounts of data from its engines for decades. By implementing predictive analytics, Pratt & Whitney can customize workscopes, provide early warning detection, and improve visibility into the overall health of an operator’s engine fleet.