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Start-Up Launches AI-Driven Engine Shop Planning System
Ensuring capacity for engine shop visits has not been a challenge during most of the pandemic, but engine work
KeepFlying Onboards Play Airlines as a customer
Discover how Aviation Data Science & Explainable AI can augment streams of historic and dynamic data to visualize the Revenue Potential of your Assets over its Remaining Useful Life (RUL) and simulate Asset Hangar & Shop Visit profitability using Discrete Optimization models.
A Digital Financial Twin transforms the quality and economic value of your Asset's Historic & Dynamic Maintenance, Airworthiness, Operational & Cost data into commercial insights by simulating decision driven scenarios.
Visualize the commercial impact of your decisions by building your Digital FinTwin®.
Lessors, Airlines & Asset Management Companies can forecast the Revenue Potential of their Aircraft, Engines and Components through asset-specific data models (e.g. A320, B737, ATR72 data models; CFM56, V2500, GEnx, PW1100 data models) that augment a blend of historic airworthiness data and dynamic operational parameters to support Machine Learning driven simulations of Maintenance Costs & Projected Revenue based on Lessee Profiles & Jurisdictional Risks.
MROs can forecast and visualize the Revenue Potential and Profitability of Hangar and Engine Shop Visits through asset-specific Explainable AI models (e.g. A320, B737, ATR72 data models; CFM56, V2500, GEnx, PW1100 data models) that augment historic shop visit data and blend it with the incoming Asset Operational profiles (Utilization, Environment, Severity, LLP statuses, Thrust Rating & Min. Average Thrust Derate) by simulating dynamic demand forecasts in conjunction with an AI driven Dynamic Capacity Planning framework. Visualize the commercial impact of any decision instantaneously.
Asset Financiers can forecast and visualize revenue potential over RUL in conjunction with credit risk models and jurisdictional risk models of potential lessees prior to making placement decisions.Asset parameters as a factor of potential lessee operational characteristics (Environment, Stage Length, Thrust Rating etc.,) are the baseline over which the financial and risk models are configured.
APPROACH
APPROACH
Wrangle your historic and dynamic Asset data through our advanced Machine Learning models to cleanse and transform your data into usable and exchangeable ATA (Spec 2400, Spec 2500) formats. The transformed data is the baseline for insights generation
Apply Configurable Finance and Risk Models against your Asset Loans, Leases & placements to forecast commercial viability of trades as a factor of the Asset’s Remaining Useful Life (RUL) using the transformed data. Credit and Jurisdictional Risk models of potential lessees augment the models to run accurate forecasts.
Simulate Asset lifecycle using ML powered smart models that support what-if-scenario frameworks to gain maximum value of your Asset’s Remaining Useful Life (RUL). As an MRO, visualize the risks and profitability of an Asset’s Maintenance Visit in advance.
If you are Aircraft or Engine Operator, Lessor, MRO, Financier or any entity with a commercial or legal interest in an Aviation Asset, contact us to understand how KeepFlying® can deploy your Asset or MRO’s Digital FinTwin® Unleash the power of Data Science on your Aircraft & Engine Assets to generate commercial insights over their RUL.
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