"“Industrial businesses have an incredible advantage given the massive amount of asset data they have at their fingertips,” said Nick Farrant, senior vice president of portfolio and industries for Uptake. “When you take a digitally driven company like Rolls-Royce that continuously raises the bar for customer excellence, and help them put their data to work, the outcomes are undisputable"."
"Industrial AI and IoT software leader, Uptake, and Rolls-Royce, one of the world’s leading industrial technology companies, have joined forces to extend Rolls-Royce’s digital ecosystem. Complementing the company’s in-house data science expertise in its R2 Data Labs, an acceleration hub for data innovation, Uptake will demonstrate how its capabilities can help Rolls-Royce implement a data-science-first approach to optimizing the performance of its Trent engine fleet, the market-leading engine family for widebody aircraft. Rolls-Royce’s TotalCare® service enables customers to maximize the availability of their engines while allowing Rolls-Royce to focus on the most efficient management of the fleet. Working with Uptake to analyze a number of disparate datasets will arm Rolls-Royce with new insights to deliver on its TotalCare® promise to airlines around the world by improving the uptime and availability of their Trent engine fleet. Built on a foundation of data science and machine learning, Uptake develops solutions that help industrial companies digitally transform their business. The company’s latest release of its Asset Performance Management application, Uptake APM, incorporates the Asset Strategy Library (ASL), the world’s most comprehensive database of industrial content including equipment types, failure mechanisms and maintenance tasks. This rich combination of deep operational and equipment knowledge with predictive analytics provides unparalleled visibility into, and insights surrounding, the entire asset environment, whether assets are connected or not."
"database of industrial content including equipment types, failure mechanisms and maintenance tasks"
Proof of concept; results not yet available