A method for STK account material self-checking and abnormal self-healing based on device state comparison
By collecting equipment status data to calculate health status and state entropy values, constructing a task dependency chain graph, optimizing storage location selection and anomaly handling, the problem of identifying sub-health and unstable states of STK equipment is solved, and production stability and energy efficiency are improved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- JIANGSU DAODA INTELLIGENT TECH CO LTD
- Filing Date
- 2026-06-23
- Publication Date
- 2026-07-21
AI Technical Summary
Existing STK self-verification and anomaly self-healing methods cannot identify sub-health and unstable states of equipment in advance, resulting in frequent abnormal interruptions during task execution, poor accuracy and traceability of material management, and problems such as out-of-order task execution, dependency conflicts, and high energy consumption.
By collecting equipment status data, calculating health scores and status entropy values, constructing task dependency chain graphs, dynamically adjusting task paths, optimizing storage location selection, and handling anomalies, a self-healing process and task avoidance are achieved, reducing the impact of equipment anomalies on production.
Effectively identify sub-health and unstable equipment conditions, reduce abnormal interruptions, improve the accuracy and traceability of material management, avoid task disorder and resource contention, optimize Crane paths, and reduce energy consumption.
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