Mechanical Engineering
Data analytics and machine learning for efficient production and smart vehicles.
With data-driven AI solutions, we unlock efficiency potential that purely physical models leave hidden.
From physical models to data-driven solutions
The development, design and maintenance of machines and plants traditionally rely on physics, mathematics and materials science. Beyond that model world lies significant potential in data-driven methods.
Supper & Supper complements existing systems with modern AI methods. This increases precision, exposes hidden patterns and leads to tangible cost savings.
Areas of application
Machine learning models complement existing systems and enable precise planning:
- Anomaly detection: Identification of defective or non-normal states
- Predictive maintenance: Damage and fault prediction for running mechanical systems
- Image-based damage detection: Automatic detection of physical damage from image data
- Process optimisation: AI-supported optimisation of grinding processes in precision mechanics
Which industries?
Our solutions are aimed at all mechanised industries that want to overcome the limits of physical models and increase their efficiency, including:
Automotive · Medical technology · Precision engineering · Aeronautics and space · Shipbuilding · Manufacturing
Mechanical Engineering Use Cases
Manufacturing companies use our know-how to analyse abnormalities in quality data, support decisions for more efficient production and uncover the relationships between cost and quality.