The conventional aviation industry approach to fleet management optimization services is to analyze accumulated data. When Dassault Aviation wanted to streamline maintenance processes and equipment design, it went a step further with the 3DEXPERIENCE platform.
When in service, each aircraft behaves differently and requires specific maintenance operations according to the events occurring throughout its operational life. Exponential amounts of complex data are generated from various information systems, whether from industrial partners or aircraft users: flight test, design, operational, manufacturing and open data found in repository databases. And a huge number data points per flight must be analyzed for each aircraft. But the full value of all of this heterogeneous data cannot be realized unless it is available in the context of its usage.
The collaborative 3DEXPERIENCE platform collects the most valuable Rafale usage data and projects it on a virtual model-based product referential. This virtual twin is an extension of the digital model of the plane, personalized and upgradeable, from design to manufacturing, maintenance and end of life. It’s the key to efficient digital maintenance, repair and overhaul (MRO). Consolidating the real-world data combined with those from the digital world allows Dassault Aviation to better manage its MRO contracts by identifying as early as possible the actions required to improve support. Reducing maintenance and forecasting associated resources means more planes in the air.
The company is also progressively enhancing the predictions of diagnostics of the planes, relying on the continuous feedback loop from the data being generated constantly. Maintenance engineers can define predictive maintenance algorithms with artificial intelligence (AI) technologies and machine learning to be able to identify weak signals before breakdowns occur. With predictive maintenance analytics, maintenance engineers can anticipate issues, increase accuracy and devise appropriate maintenance schedules, parts replacements and MRO processes quickly to meet aircraft rate availability objectives.
Data science and collaboration capabilities of the platform ensure that all of the stakeholders are better able to work together and make informed decisions based on data analytics insights. Dassault Aviation applies these insights to its innovations, particularly for predictive maintenance, pilot support, and ground assistance solutions. Order data, manuals, service information, parts availability, regulatory updates, maintenance procedures and more are available the moment they are needed, cutting costs by improving spare part supply chain resilience and reducing inventory.
The ability to monitor contract performance, derive lessons learned, and enrich predictive maintenance algorithms ensures excellence in the operational maintenance processes of the planes.