SOURCE-LINKED INTELLIGENCE
Semantic Signal-Assisted Inspection and Recovery Allocation in Reverse Logistics
Reverse-logistics operators often decide how to inspect and route returned assets before their condition is fully observed, while full inspection consumes scarce labor. Semantic Signal-Assisted Decision Support converts return notes into a condition factor and a signal-quality score that guide inspection depth and recovery allocation under shared labor capacity. We evaluate the framework in three synthetic benchmark scenarios spanning information technology decommissioning, aircraft maintenance, and consumer-electronics returns. Across 30 paired simulation seeds, the keyword implementation imp
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T05:10:00.000Z
First collected: 2026-09-21T05:51:54.566Z. This is not the publication date.