AI Solutions for Manufacturing
AI, quantum techniques and other Big ComputeTM could unlock new efficiencies across the value chain in manufacturing: from the design stage to factory operations and the supply chain. According to McKinsey, quantum technology could add over $500B in value by 2035 for the automotive sector alone.
Plant Scheduling Optimization with BMW & MIT
Every manufacturer operating on a global scale is faced with a difficult optimization problem: how do they schedule their workers to achieve production targets while minimizing labor costs? This is a hard problem due to the wide range of possible configurations and the high number of constraints, including varying production rates between shops, a discrete set of shift schedules, and the need to prevent overflows and shortages in the buffers between steps in the manufacturing process.
Zapata is collaborating with BMW and MIT to apply quantum-inspired techniques to the plant scheduling optimization problem. Using our computational workflow platform, Orquestra®, we ran about one million optimization runs cycling through dozens of different categories of algorithms, problem configurations and optimizer solutions to benchmark their performance against each other. We identified the best algorithm to solve each problem configuration, whether it was quantum or classical.
In the end, we identified several instances where our Generator-Enhanced Optimization (GEO) technique could outperform traditional classical solvers. GEO uses quantum or quantum-inspired generative machine learning models to learn from and improve upon the results generated by classical solvers. It can be applied as a solution for many optimization problems relevant to manufacturing beyond plant scheduling.Learn More about GEO
Applications for Manufacturing
Supply Chain and Logistics
Supply Chain and Logistics
Computational Fluid Dynamics Simulation
Model computational fluid dynamics for new designs with enhanced accuracy using quantum simulation.
Product Design Process Optimization
Build design process optimization models capable of balancing multiple objectives for product functionalities with safety, reliability and cost, and solve it with GEO.
Manufacturing Process Optimization
Optimize the scheduling of machine processes and employee shifts using quantum or quantum-inspired techniques.
Factory Floor Automation
Leverage GEO to optimize the timing of automated processes on the factory floor.
Apply variational quantum classifier algorithm or other classical or quantum classifiers to proactively predict when machines will need maintenance.
Generate synthetic data with generative models to better train anomaly detection algorithms for quality control processes.
Supply Chain Optimization
Apply GEO to optimize transportation networks to reduce costs and delivery times and select suppliers and vendors optimized for product quality and demand coverage.
Distribution Route Optimization
Leverage quantum or quantum-inspired techniques to optimize distribution routes to reduce fuel costs and delivery times.
Optimize the stocking of raw materials and components for manufacturing as well as the stocking of finished products in distribution warehouses using GEO.
Use Case Timeline (est.)
Orquestra® Benefits for Manufacturing
Orchestration Across Environments
Leverage the heterogenous 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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