Instruments TRIZ Cases

Coordinate automated and manual drilling tasks with adaptive process control.

Enumerate supply-chain paths, remove loops, and optimize duty rates by site and product flow to reduce computation and costs.

Code dependencies, structures, and documentation are analyzed continuously to build current profiles for retention and training.

UAV imaging and machine learning improve warehouse put-away accuracy and alerts.

A hierarchical data structure and data fusion engine let users adjust manufacturing workflows without custom code.

A first model and domain adaptation generate pseudo-labels, then iterative updates train accurate models from unlabeled images.

A brightness gradient based on pixel distance from image boundaries reduces crosstalk while preserving clearer autostereoscopic 3D images.

The apparatus detects insufficient acquisition data and generates targeted guidance, reducing redundant training-data collection.

Inventory analysis verifies active personality files after updates, preserving consistent device configuration across firmware changes.

A lightweight web supervisor discovers commissioned devices, assigns schedules, and manages operation across sites without on-site gateways.

This case maps analog environment devices into virtual devices, enabling normalized data, condition detection, and automated action.

A modular platform links scripts, budgets, casting, and crewing while generating resource-aware schedules and reservations.

Laser beams overlap parallel particulate flows to form visible mid-air 3D voxels without screens or containment.

Continuous interaction monitoring updates candidate temperature, helping employers identify passive candidates as interest rises.

Computer vision and OCR extract BOM values from drawings, build material lists, and support faster cutting orders.

RFID readers track items entering and leaving totes, enabling rapid transition checks and more accurate warehouse inventory records.

Feedback targets label-mismatch images for resource-efficient synthetic augmentation.

This case replaces generic mode lists with angulation-aware machine learning to select X-ray settings for improved image quality.

Jet-printed pigment stays on convex peaks while reflection and refraction create comfortable stereoscopic visuals.

A production cycle indicator ranks work orders by delivery timing, process direction, and grade transition cost to reduce inventory.

Historical alarm and action data help recommend responses to new process events, reducing confusion during alarm floods.

Weighted risk factors produce asset risk profiles that guide tailored controls across confidentiality, integrity, and availability.

ERP application data is checked automatically, then models are trained, evaluated, activated, and retrained as needed.

Active and reinforcement learning improve impediment classification and reduce manual monitoring.

Alternating sub-sub-pixels and overlapping anode projections provide continuous light emission, reducing dark regions and moiré fringes.

This case coordinates walker pickups and vehicle deliveries using location, preparation, and arrival estimates to reduce denials.

A unified sensor system representation aligns calibration across LIDAR, cameras, and radar without shutdown.

A resource-aware display filters medical records to fit processing capacity while preserving faster chronological access across devices.

A scope-resource matrix embeds resource columns in the WBS, reducing navigation while clarifying task allocation.

A product information server extracts differing fields and displays them beside shared outlines, helping sellers select records faster.

Deep learning maps fields across report types and preserves non-mapping information in one integrated healthcare report.

Local signals and server analysis update diagnostic databases for more accurate abnormality detection and timely maintenance notification.