Data & Classical Analytics / Mathematical Optimization
Early feasibility trade-off optimization
ResearchSupportlow effect
Core capability
The system computes the best feasible production or logistics plan under real constraints, helping improve throughput, delivery reliability, and cost efficiency.
How it works
Business rules, capacities, deadlines, and resource limits are encoded mathematically, and the solver computes the best feasible plan instead of leaving planners to resolve trade-offs manually.
Application here
Simple optimization models screen concept alternatives for engineering feasibility before teams commit to detailed development.
Business impact
This helps stop weak concepts earlier and focus effort on the most promising directions.
Limitations
Concept-stage inputs are uncertain, so results should guide direction rather than lock in decisions. Unconventional but viable ideas can still be screened out too early.
In production
This is already a real production capability in many companies: the system helps build better plans for production, logistics, and resources under real business limits.
Research
The direction of travel is toward systems where a planner describes the problem in business language and the software helps turn that into a solvable planning model much faster than today.
Examples
Airbus used Autodesk Generative Design for an A320 cabin partition: the optimised variant was 45 % lighter (30 kg vs 55 kg) meeting all structural requirements (Autodesk customer story). ESTECO modeFRONTIER is used for multi-objective concept trade-offs in aerospace and automotive — .