Geometric CAD TRIZ Cases

Measured blank-shape data is used to model real sheet variation, compare formed-part shapes, and verify press-forming analysis accuracy.

Aspect labels in mechanical CAD add mechatronic metadata, keeping control and mechanical models synchronized for virtual commissioning.

A bead map assigns polygon indexes and ON/OFF flags to automate deposition paths for continuous bead formation in laminated shaped products.

Frequency-tuned cab and seat damping units isolate low-frequency vibration while improving cab fatigue life and reducing structural weight.

Density-based topology optimization sets layer boundaries and milling directions so 3D parts fit 2.5-axis machining with less programming effort.

Mobile image and sensor capture replaces manual multi-point laser scanning to build complete 3D packaging plant models faster and with fewer omissions.

Virtual ECUs in a shared simulation environment let teams test ECU applications across platforms without relying on limited physical devices.

Automated constant-angle addendum generation avoids self-intersections, cuts CAD time, and helps prevent sheet tearing in ISF.

Pre-trained neural networks replace repeated CFD runs to predict aerodynamic flow fields faster while reducing design time and compute load.

Compares measured and elastoplastic model shapes at bottom dead center to improve springback prediction and press-part dimensional accuracy.

Uses inline type 2 and type 3 data to estimate processing results accurately, cutting extra experiments and measurement burden.

Waveform-based blank models predict how metal sheet shape variation affects formed-part accuracy and reveal critical regions needing correction.

A GUI-driven knowledge graph maps engineering queries across design and maintenance platforms to cut manual search time and return relevant data.

An intermediary software layer merges executable instruction lists from separate manufacturing packages into one NC program, cutting integration effort.

Facial measurements and modular frame selections are converted into CAM-ready eyewear specifications for precise fit without trial-and-error shopping.

Virtual CAD-based distance images replace repeated physical bulk loading, speeding precise training data creation for workpiece pick-position models.

Actual usage data from sensors and networked analysis improves remaining useful life estimates for vehicle parts beyond fixed schedules.

Digital twin forecasting helps reposition a hot-air balloon in real time to avoid adverse weather, air quality, and obstruction risks.

Real-time sensor data and machine learning refine stamping control parameters to cut defects, downtime, and line integration delays.

Equivalent spring models cut aircraft assembly simulation time while preserving positioner load accuracy and compensating for floor defects.

3D robotic sliders map crucial locations to stored time points, letting engineers jump through simulations without manual scrolling errors.

Adjust coupling points, types, and motion directions on CAD-based assemblies to improve full-machine motion simulation accuracy in 3D.

Boolean-built compartment and bridging volumes keep housing CAD models reusable and stable as component parameters and shell geometry change.

Duplex API calls let an external control service update process simulation models in real time while keeping the core simulation service separate.

Compares measured and CAE stress distributions to pinpoint regions causing springback mismatch and reduce die adjustment effort.

Construction worker counts drive automatic UAV cruise-cycle adjustment, improving site imaging and 3D modeling without manual retuning.

Interactive parametric fit models interpolate learned product data and user adjustments to improve custom fit and generate manufacturing instructions.

Pareto optimization co-designs automotive controllers and Ethernet parameters to cut E/E design effort while improving control performance.

Graph-based permissions let building platforms share contextual data securely, enabling integrated control without losing subsystem independence.

Virtual rigidity analysis pinpoints where sheet reinforcement best cuts springback, improving shape fixability and dimensional accuracy.

Machine learning links end bending and press bending settings to predict post-expansion pipe out-of-roundness and cut trial time.

Approximate linear regions let mechatronic control models be assembled with less re-engineering while avoiding commercial software dependence.

Iterative CAD shape updates use stress simulation and fatigue constraints to meet loading-cycle targets without sacrificing structural integrity.

Additive manufacturing reshapes integrated valve flow channels and supports to cut weight, defects, pressure loss, and leakage risk.

Physics-guided Auto-ML builds a hybrid AI model that improves dynamic system prediction while lowering memory use and computational cost.

Automated manufacturability and cost analysis flags impermissible design features early and guides design-to-production decisions.

Autonomous manufacturability and cost analysis helps product designs move into production faster with fewer manual review steps.

Shared 3D CAD features and process capability data adjust inspection frequency, cutting unnecessary checks in small-batch component manufacturing.

A servo-adjusted resistor and relay create dynamic copper cable faults, enabling portable training with realistic post-repair and recurring fault scenarios.

Axially clamped threaded sleeves create opposed bond stresses in concrete, distributing loads before cracks form and improving tensile reinforcement.

Nonlinear descent guidance updates aircraft performance in real time to cut fuel use, control altitude accurately, and smooth cruise-to-descent transition.

A torque arm carries most operating loads while a stiff shaft joint resists transverse forces, enabling compact and stable transmission support.

By adding brightness, color, and sign display data to BIM models, this case improves tunnel guidance simulation realism and accuracy.

Uses actual position, preset trajectory, and kinematic links to determine target speed and direction for more accurate automated control.

A virtual map mirrors real driving trips and displays risk indicators to improve driver awareness and encourage safer vehicle operation.

Precise tooth-angle calculation and positioning reduce meshing error and assembly limits in multi-linkage planetary gear mechanisms.

Container-based simulation lets engineers repeat autonomous vehicle tests across varied road, sensor, and control parameters without extensive live trials.

Automated use of architecture, state, and template data builds state-specific control-system models without manual nominal-mode setup.

Operational requirements embedded in piping diagrams are evaluated automatically to generate automation functions with less planning effort and error.

Separating vehicle and door polygons enables realistic open-door scene reconstruction for autonomous vehicle sensor simulation.