for Aerospace & Automotive
Quantum computing promises to unlock new advances in fluid dynamics, autonomous driving, supply chain optimization and traffic management. According to McKinsey, even a 2-5% increase in productivity would create $10 billion to $25 billion in value for the industry each year.
Disruptions are common in the transportation industry, particularly among airlines. Since large logistics networks are closely interconnected — one plane may fly multiple routes in a single day — a small disruption in one place can lead to costly losses across the entire network. In fact, irregular operations (IROPs) can cost airlines as much as 8% of their revenue. Airline operators are often forced to weigh multiple competing considerations when rescheduling flights such as time, costs, further delays, and passenger compensation. The result is a complex multi-factor combinatorial optimization problem that needs to be solved in real-time.
Complex combinatorial optimization problems are typically difficult to solve on classical computers, even approximately. However, our Generator-Enhanced Optimization (GEO) approach has a demonstrated ability to provide an advantage for complex optimization problems. It does so by using quantum or quantum-inspired generative machine learning models to learn from and improve upon the results generated by best-in-class classical solvers. In doing so, it can support the real-time optimization and re-routing of planes and other logistics networks while accounting for numerous parameters.Learn more about GEO
A selection of aerospace and automotive quantum use cases.
At over 200mph, tires degrade quickly: a typical Indy 500 race includes around five tire changes per car. A key part of race strategy for teams like Andretti Autosport is knowing when to take a pit stop — a problem similar to predictive maintenance problems faced by automotive manufacturers.
Since spring 2022, we’ve worked with Andretti Autosport to upgrade their analytics infrastructure and build quantum-ready machine learning models for race strategy. This includes models for tire degradation analysis and fuel savings optimization that translate directly to automotive and OEM use cases
Orquestra® Benefits for Aerospace and Automotive
Orchestration Across Environments
Leverage the quantum and other heterogenous classical compute resources best suited for your tasks, without getting locked into any one hardware platform. Deploy across hybrid backends at enterprise scale.
Data Management & Velocity
Store, retrieve, and analyze large datasets. Streamline data management from ingestion to export to accelerate data velocity.
Keep what works now. Integrate existing and future solutions with a framework optimized for extensibility, interoperability, and innovation.
Workflow Development and Deployment
One unified platform to go from research to development to deployment with extensible, scalable, modular workflows.
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