Geometric CAD TRIZ Cases

A configurator tests component arrangements, scores them, and presents 2D and 3D fire alarm panel layouts.

Variable-thickness layers and lattice structures help additive-manufactured golf face inserts improve ball speed and spin consistency.

A grid-based method combines wind distributions with local repositioning to maximize annual energy while reducing computing demands.

This case maps fast RANS analyses to LES-trained CNN predictions for accurate urban building flow fields.

Coordinate projection keeps PINN shape optimization differentiable across material domains.

This case maps selected sketch dimensions to related 3D faces, preserving meaning while reducing manual MBD annotation errors.

Dynamic via placement maps bump coordinates across package layers to improve via density, routing speed, and power integrity.

Wireline logs and core data locate casing failure risks, guiding stronger sections where reservoir displacement raises stress.

This CAD analysis combines material, process, and factory-location data to compare embodied carbon and manufacturing cost scenarios.

Confidence-scored ML combines aerial mapping and selective human review to improve object detection and construction progress estimates.

A 3D model links dynamic riding pressure maps to printed saddle cushions that better match anatomy and riding positions.

A translation layer extracts clash data and controls CAD inputs to mark clashes and viewpoints across Revit, AutoCAD, and BricsCAD.

This CAD workflow transfers selected sketch dimensions to 3D model faces, reducing manual PMI effort and preserving dimensional accuracy.

This case adapts 3D models to mounting space and combines printed and conventional parts for faster, stronger vehicle replacements.

This case combines 6-DoF electromagnetic tracking with IMU fallback to preserve stable 3D air mouse control during occlusions.

This case automates source-to-target decorative element transfer by calculating new positions and sizes, avoiding manual resizing.

Configurable schemas and pipelines map supplier products to project models for objective comparison of cost, assembly, and compatibility.

A magnetic limiting structure suspends the bottom-entry impeller, reducing wear, contamination, and cleaning difficulty during mixing.

This case screens augmented motion trajectories to build 3D mechanisms with physical and dynamic features, reducing manual geometry work.

The review system detects text and graphics, displays them sequentially, and enlarges details to improve completeness and confidence.

This case uses iterative ERP analysis to optimize bead position, shape, size, angle, and orientation across automotive floor-panel areas.

Flow-line data reveals target stay portions, guiding facility placement to reduce movement distance and improve operational rates.

An AI suite generates clash-free, constructable plant routing options through 3D modeling, machine learning, and natural language input.

This case uses bump coordinates and pad-stack parameters to automate dense via placement, improving power integrity and reducing impedance.

Historic pallet demand guides dynamic bay allocation and aisle simulation to reduce worker travel while preserving pick-area space.

A residual compressive stress layer keeps casing bonded during CO2 injection, limiting micro-annulus formation and leakage.

This case models detector-dependent peak shapes, fits overlapping emissions, and supports baseline correction and concentration calculation.

This case combines mapped meshes and geotagged images to create accurate, interactive 360-degree models of complex properties.

An idealized 3D model helps BIM users adjust sectioning planes precisely and isolate construction project areas with less complexity.

Machine learning corrects simulation bias to tailor optical network margins.

Dynamic mode decomposition preserves key 3D displacement physics while reducing computation for wellbore cement fluid forecasts.

Machine learning converts 2D drawings into BIM or CAD models and applies project data and code rules to review compliance.

Satellite imagery and computer vision create floor plans for precise device placement.

Logical fault domains use redundant electrical zones to preserve resilience.

DLL-based BRep partitions support secure, threaded modeling in open-source platforms.

A configurable PIM accelerator overlaps neural-network layers and data batches to address mapping inefficiency and latency.

This case combines automatic and manual point-cloud processing to improve reliability and reduce operator complexity in 3D modeling.

A trained neural network maps high-fidelity B-reps to feature maps for user-specific style metrics with minimal labeled examples.

This case uses sulcus-to-sulcus data and lens thickness to predict Vault and select ICL size before implantation.

This case synchronizes water-level and trim-angle data to correct ship geometry and calculate displacement volume more accurately.

Scanned geometry deviations are extended into unscanned regions to correct print data and compensate deterministic warpage.

Simulation and reinforcement learning optimize LiDAR placement under budget and environmental constraints for better roadside point clouds.

This case aligns text prompts with 2D architectural images to produce repeatable scores for social, tranquil, or isolating spaces.

This case extracts valid 3D wall edge pairs and merges their 2D center lines, reducing manual correction and computation time.

Iterative co-optimization aligns freight logistics, vehicle powertrains, and energy pathways to reduce cost, downtime, and emissions.

A U-Net model combines material and obstacle maps to reduce onsite investigation time for indoor radio design.

A four-node zero-thickness interface model captures residual slip and interfacial damage in reinforced concrete under cyclic loading.

This case uses geophysical constraints and least-cost routing to coordinate main and lateral subsea pipelines.

Machine learning refines conduit paths in 3D plant models, helping engineers explore constraints faster and improve resource allocation.

CAD feature vectors match seed structural members to candidates, reducing manual selections and replication errors.