Toward the end of 2017, Russia’s S7 Airlines agreed that Pratt & Whitney would support PW1100G-JMs on 30 Airbus A320neo and A321neo-family aircraft under a 12-year EngineWise agreement.
Eva Azoulay, Pratt’s vice president of engine services, explains that EngineWise is an evolution of services Pratt previously offered, plus additional services. ”We are unifying our services portfolio and introducing new offerings to support customers’ evolving needs,” Azoulay says. Pratt is investing heavily in both technology and infrastructure to improve its engine support.
EngineWise uses analytics and real-time intelligence to predict and prevent engine disruptions. Pratt is aiming to expand the service to provide smarter, more straightforward solutions, and to improve communications, collaboration, transparency and connectivity with engine operators. That matters because no matter how clever analytics are, they do no good unless operators trust and use them.
The EngineWise program applies to all Pratt commercial engines, but Azoulay says a greater proportion of new engines are under flight-hour agreements. “Operators recognize the knowledge and value that the OEM can provide during early operations.”
The engine-maker has been collaborating with a number of other firms that have expertise in real-time monitoring, predictive analytics, business intelligence and data integration. And its parent United Technologies is making a heavy internal investment. “UTC is investing $300 million over the next five years in its new United Technologies Digital Accelerator business,” Azoulay notes. “This investment is the next step in the company’s digital transformation and underscores our commitment to leading in the digital era.”
The Pratt exec says Digital Accelerator will transform Pratt’s products and services by using the Internet of Things and data to generate more value for customers. For example, the Digital Accelerator team is currently working with Pratt on eFAST, for enhanced flight data acquisition storage and transmission, to improve visualization of full-flight data.