Industrial Intelligence A structured map of industrial AIA structured map of industrial AI
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Technology
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Engineering & Simulation · Concept
Data & Classical Analytics / Mathematical Optimization
Early feasibility trade-off optimization
Research Support low 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
Early‑stage concept modeling of an automotive body‑in‑white for design optimization
Description: An automotive OEM‑collaborative thesis presents a concept‑stage beam‑like FE model of a vehicle body‑in‑white that enables rapid structural screening and parameter‑based optimization of stiffness and attributes before detailed CAD exists, used to explore early feasibility and trade‑offs.



Optimization of crash‑relevant vehicle structures during the concept phase
Description: A crash‑safety study uses simplified parametric FE models of a Toyota Yaris front‑end structure to run multi‑parameter optimization early in the concept phase, assessing feasibility of alternative layouts and energy‑absorption configurations before committing to detailed design.



Methodology for early design‑phase cost and performance trade‑off analyses
Description: A value‑engineering methodology applies simplified mathematical models at the concept stage to evaluate alternative automotive component architectures, balancing cost, performance, and manufacturability as a screening layer before detailed engineering.
https://webthesis.biblio.polito.it/18263/https://www.ansys.com/content/dam/resource-center/case-study/optimization-crash-relevant-vehicle-structures-during-concept-phasehttps://www.cambridge.org/core/services/aop-cambridge-core/content/view/C695F5E2E3CB22EBF075FC11C957B7DE/S2732527X2200061Xa.pdf
Sources
Autodesk — Airbus generative design — ; ESTECO modeFRONTIER —
https://www.autodesk.com/customer-stories/airbushttps://engineering.esteco.com/modefrontier/