Drawing From Basic Elements TRIZ Cases

See how integrating a screen and user interface into the trolling motor housing merges sonar, n

LEDs, lenses, and a slit film project a realistic flame image onto the pot, making induction heating status easy to recognize from a distance.

Color-coded comparison of actual and reference power use helps refrigerator users manage energy settings and schedules more easily.

A bar-shaped load ratio display with scale marks helps shovel operators judge loading progress faster than numeric-only screens.

Hierarchical status displays link standby periods in load ports, robots, and processing units to substrate results, helping pinpoint efficiency loss.

When a lead-vehicle mark falls outside the HUD display region, a second indication preserves driver awareness of detection status.

Image and video comparison turns ion mobility mass spectrometry plots into delta datasets, speeding large-sample difference analysis.

Arc-based power flow visualization arranges grid devices on a horizontal axis to reduce clutter and guide accurate switching operations.

A shared-backbone model combines image features and vehicle speed to detect close following accurately while avoiding multiple separate classifiers.

Boom-mounted cameras overlay predicted boom paths on live images to improve tip positioning, obstacle warnings, and spray accuracy.

Maintaining the meter drawer state through vehicle stop-start interruption prevents delayed or incomplete speed and warning displays.

Real-time friction circles at each wheel visualize tire force usage and changing slip limits under varying tire loads.

Connected actual and estimated laser data helps operators visualize performance trends and compare maintenance scenarios before degradation.

Animated digit morphing with Bezier curves and particles reduces speedometer flicker, saves display space, and keeps readings stable.

Local speakers and visual alerts signal EV wheel slip from wheel speed deviation, helping drivers detect traction loss on low-mu surfaces.

Predicts a vehicle's emergency stop position from travel state and adjusts indicator visibility to match communication reliability.

Coordinates drawing position, color, size, and angle across vehicle displays to reduce driver discomfort from inconsistent viewing.

Dynamic per-wheel friction circles adapt to tire load changes, showing force direction and slip limits for clearer tire usage feedback.

Staged HUD and screen overlays help drivers prepare lateral adjustment early and pass oncoming vehicles smoothly on narrow roads.

Sequential inter-vehicle markers in an AR-HUD link the host and preceding vehicle, making ACC status easier to confirm even off-screen.

Infrared sensors on the tractor capture trailer tire heatmaps to detect dangerous tire conditions without complex trailer-mounted sensors.

Vehicle sensor data reveals ramp gradients and traversed levels, enabling reliable parking-garage location when GPS is obstructed.

A shifted beam outline reveals intensity distribution deviation, simplifying optical axis adjustment and helping reduce chromatic aberration.

Color-coded left and right overlays on moving-body sensor images reduce operator orientation errors during remote work.

High-resolution grid simulation evaluates inverter-based interconnections against voltage, thermal, and backfeed limits before approval.

Angular sector time curves preserve spatial and temporal sensor cues for more reliable vehicle scenario recognition with less information loss.

Integer outer-product checks detect B-spline drawing intersections accurately and quickly without float calculations or high-order equations.

Diagonal perspective cues let a head-up display show sequential road sign information without needing a taller image area.

Maintaining the display drawer through ignition-off stopping completes shutdown drawing and prevents restart display faults under voltage drop.

Sequential inter-vehicle markers keep ACC status visually linked to a detected preceding vehicle, even when it lies outside the display region.

Automatically maps node position and type data into a live network model, reducing manual errors and speeding response to network changes.

A segmented vehicle display highlights relevant nearby, disabled, or emergency vehicles by distance and direction to reduce driver confusion.

Dynamic AR trajectory lines on a vehicle HUD adjust spacing, color, and shape to match speed and road conditions for clearer navigation.

Repeated WDS mapping at shifted analyzing-element positions builds spectrum maps faster than point analysis while preserving high energy resolution.

An overhead image overlay highlights swivel and travel attention zones around a work machine, helping operators spot collision-prone areas.

Date and time labels on power-use graphs help users anticipate peak periods, compare records, and set demand control targets more intuitively.

Sensors and a controller define prohibited areas around obstacles, slowing or stopping shovel movement to avoid collisions and reduce operator burden.

GAN-generated road images replace hard-to-capture atypical driving scenes, cutting data collection time while improving AV perception robustness.

Switching among predefined traveling patterns lets the head-up display match road conditions and driver needs with clearer driving guidance.

Large feeder maps stay responsive by limiting displayed nodes and lines and selectively showing conductive line subsets.

Onboard sensors and automatic actuator control help a shovel avoid poles and power lines while maintaining excavation efficiency.

Sensor and map data drive an AR lane display that color-codes adjacent lane safety, helping drivers judge lane changes without looking away.

By changing robot component graphs from parallel to series or mixed links, agents can learn independence and cooperation messages.

Gantt chart preprocessing turns manufacturing state data into basic and conditioned images for neural-network dispatching and real-time anomaly detection.

Drag-and-drop network diagrams generate web HMI monitoring screens, cutting SCADA setup effort while supporting legacy plant equipment.

Sensor data is converted into part-level failure probability and damage level displays to support maintenance and operation decisions.

Resource values from system logs are converted into per-function scores, making health and reserve capacity easier to assess and visualize.

Graph modules and task rules let production scheduling logic be configured for new manufacturing lines without similar past records.

Audiovisual cues and chronological playback highlight faulty and missing periods in building time-series data, reducing operator overload.

Future parameter prediction and index feedback help tune POY-to-DTY texturing in real time to prevent yarn defects and improve efficiency.

Chronological state timelines make idle periods, alarms, and processing gaps in substrate tools easier to spot and manage.

Bezier control points let operators quickly delete, reshape, and add robot route segments while preserving smooth navigation in changing environments.

Wall detection from 2D point clouds sets a main travel direction, making robot maps smoother, more regular, and easier to follow.

Branching from prior prompts lets users compare alternative chatbot responses without losing context, improving navigation and relevance.

A popup summary with interactive objects cuts user inputs and updates data visualizations dynamically for easier analysis of complex datasets.

Transforms machine logs into searchable event streams and XR visualizations, speeding pattern detection across data paths.

Spatial 3D objects make complex multidimensional data easier to inspect through real-time manipulation and personalized views.