British aircraft engine maker Rolls-Royce has selected Vanguard Software to deliver advanced modeling and simulation software designed to help slash the cost of manufacturing engines and other aerospace products.
Rolls-Royce, formerly affiliated with the luxury car brand, is a leading manufacturer of engines for Boeing Co. and Airbus Group SE’s long-range jetliners. The London-based company selected Vanguard Software from a field of competitors for its unmatched prebuilt analytics and collaborative-modeling capabilities.
Specifically, Vanguard Software’s platform will allow hundreds of Rolls-Royce engineers and planners to model raw-material costs across an array of industrial componentry and under unlimited product-development and procurement scenarios. Additionally, the platform lets various Rolls-Royce teams share models collaboratively across business units and geographies.
“The goal here is to give their engineers the ability to dynamically calculate real-time cost estimates while still in the design phase of a next-generation engine,” said Rob Suggs, CEO of Cary, N.C.-based Vanguard. “That’s a potentially huge advantage because it allows makers to foresee the financial impact of design or materials changes, and ultimately to optimize engines for cost efficiency.”
Suggs said that Rolls-Royce, whose competitors in the aircraft engines domain include General Electric Co. and Airbus Group SE, should be able reduce modeling time by up to 90 percent, which will yield significant financial gains and competitive advantages. Prior to working with Vanguard, this was a very labor intensive and time consuming effort.
In addition to time savings, Suggs said that optimized materials and manufacturing processes should further lower the cost of building engines.
Separately, Vanguard recently revamped its flagship software platform. The new platform includes enhanced, advanced-analytic capabilities that combine powerful modeling and simulation tools with collaborative workflow. Suggs said this combination helps business users across an enterprise assess competing courses of action, compare risk-reward scenarios, test ideas virtually, and apply an exhaustive range of time-series and model-based forecast methods.