Use Neural Designer to model engineered systems, optimize industrial processes, detect failures, and improve performance from operational and sensor data.
Where Neural Designer applies
Engineering applications often involve complex systems with many variables, nonlinear behavior, and large volumes of process, sensor, or simulation data.
Neural Designer helps teams in mechanical, electrical, civil, chemical, industrial, energy, environmental, automotive, aerospace, and marine engineering.
How machine learning helps
Create predictive models for performance, quality, maintenance, emissions, and process behavior.
Use validated models to optimize decisions, reduce cost, improve reliability, and support digital transformation.
Representative use cases
Performance optimization
Model process behavior and identify conditions that improve performance. Read use case ›
Predictive maintenance
Predict equipment condition and plan maintenance before failures occur. Read use case ›
Product quality improvement
Relate product features and process variables to quality outcomes. Read use case ›
Building virtual sensors
Estimate measures that are difficult, expensive, or delayed to collect directly. Read use case ›