By: Yochai Schwieger
French company Dassault Systèmes unveiled at the Paris Air Show a new capability to develop a complete aircraft — from initial design through manufacturing and maintenance — using its newly launched 3D UNIV+RSES platform. In a demo featuring experts from Airbus, the U.S.-based NIAR aviation research institute, and Belgian aerospace manufacturer SABCA, Dassault showcased an end-to-end development and maintenance process conducted entirely in a digital environment — without building a single physical component at the early stage.
The development process — from engineering design to maintenance simulations and failure prediction — was executed entirely in a virtual environment using a precise digital twin of the aircraft. This twin allows for testing design ideas, detecting faults, performing aerodynamic simulations, structural analyses, wear predictions, usage scenarios, maintenance planning, and even technician training and drills. The digital model also incorporates the production process itself — simulating assembly lines, shop floor logistics, parts flow, and quality control.
Assembly line configuration, division of labor between robots and humans, bottleneck analysis, and production timelines — all of these are evaluated in advance within the virtual environment. This enables optimization not only of the aircraft itself, but also of how to manufacture it — even before a factory is built, a budget is approved, or a single part is produced. The approach dramatically reduces risk, cuts costs, and shortens the time from concept to deployment. The result: production can begin only after every system has already been thoroughly optimized — without wasting resources on trial and error. It’s a paradigm shift: from engineering that is tested in the field, to engineering that is implemented only after it has been proven.
Dassault Systèmes placed strong emphasis on its presence at this year’s air show, aiming to position itself as a key enabler of the European defense industry’s upcoming growth. “Europe’s defense systems are on the verge of an industrial leap forward, and we see digital twins as a critical component for accelerating innovation and maintaining operational readiness,” said a company representative during a press briefing. Dassault aims to play a central role in Europe’s rapid defense buildup. The company says its platform supports the creation of digital twins for aircraft, satellites, drones, and even ground combat systems such as armored vehicles — integrating design, manufacturing, training, and maintenance.
The Next Generation of Digital PLM Platforms
The UNIV+RSES platform, launched in early 2025, marks a new evolution in the company’s longstanding 3DEXPERIENCE system. While 3DEXPERIENCE has served for over a decade as a PLM (Product Lifecycle Management) platform in the aerospace, engineering, and automotive industries, UNIV+RSES adds a new layer: real-time data analytics, generative AI, and immersive XR experience. It’s an integrative layer that expands the use of digital twins beyond just design and engineering — into maintenance, training, diagnostics, supply chain optimization, and global team collaboration.
A Digital Twin That Evolves with the Product
The main difference in 3DEXPERIENCE UNIV+RSES lies in its intelligent, living, and real-time-updated digital twin. Whereas traditional digital twins reflected static models, the UNIV+RSES twin evolves alongside the physical system, continuously learning and updating via sensor data, usage patterns, and predictive maintenance algorithms. The twin not only mirrors reality — it predicts failures, recommends solutions, simulates future scenarios, and presents actionable data to teams.
For example, a hydraulic systems technician can put on XR glasses and view the digital twin of an aircraft’s landing gear. During training, they’ll see visual highlights of high-wear areas and rehearse recurring malfunction scenarios. But when the aircraft returns from a flight and sensors detect unusual vibrations in the right wheel, the digital twin updates in real-time, highlights the suspected area, and guides the technician to the precise location — before they even touch the aircraft.
Collaboration with Apple
During a Techtime visit to Dassault Systèmes’ headquarters in Paris, the company showcased a new system born out of collaboration with Apple Vision Pro. In summer 2025, the 3DLive app will launch, allowing users to project a digital twin from UNIV+RSES into their real-world space — in high resolution and with multi-user interaction. The advantage of Vision Pro over other XR devices lies in its accurate eye-tracking, hands-free control, and natural experience, enabling engineers, technicians, and designers to “step into” the product and interact with it as if it were real.
Vector-Based Digital Analysis
UNIV+RSES integrates a Generative AI suite that not only analyzes existing models, but actively generates new content — designs, scenarios, maintenance procedures, and operational suggestions. One of its key tools, VecAssess, allows for the analysis of digital twins in a vector space, identifying anomalies, optimization opportunities, or emerging failures before they become evident in the physical world.
VecAssess is based on the concept of vector space analysis — a mathematical approach that represents component and process attributes as numeric arrays. Each engineering component, such as a valve or piston, is represented as a vector: a data sequence including properties such as weight, material, operating temperature, maintenance frequency, usage time, and more. This creates a digital fingerprint for each part, enabling the AI to compare hundreds of thousands of vectors to detect anomalies, identify recurring patterns, or predict failures. This is similar to the vector space used in large language models (LLMs), where ideas and words are also represented as vectors to uncover semantic relationships. Here, the vector space serves not only as a representation tool, but as a foundation for inference, forecasting, and autonomous decision-making within the system.