Metal bottle cap surface electroplating defect traceability analysis method for micro defects

By constructing a process anchoring module and a temporal causal mask generator, and combining multi-source heterogeneous data and a historical case library, the problems of dynamic tracing difficulties and high misjudgment rates in the source analysis of electroplating defects in metal bottle caps are solved. This enables efficient and interpretable defect cause analysis, which is suitable for real-time optimization in industrial settings.

CN122222985APending Publication Date: 2026-06-16DONGGUAN YIHAN HARDWARE PRODUCTS CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
DONGGUAN YIHAN HARDWARE PRODUCTS CO LTD
Filing Date
2026-03-20
Publication Date
2026-06-16

AI Technical Summary

⚠Technical Problem

Existing technologies for tracing and analyzing the sources of electroplating defects on metal bottle caps suffer from problems such as difficulty in dynamic tracing, lack of interpretability, poor model flexibility, high misjudgment rate, and high deployment cost. In particular, in scenarios with multiple processes and long time spans, it is difficult to achieve accurate defect cause analysis.

⚗Method used

By acquiring the timestamps, equipment identifiers, and key process parameters of metal bottle caps in the pre-processes of stamping, cleaning, and passivation, a process anchoring data sequence carrying multi-dimensional working condition characteristics is generated. Combined with high-resolution defect images for weak supervision alignment, a spatiotemporally aligned multi-source heterogeneous fusion dataset is generated. Causal inference is performed using a temporal causal mask matrix, and confidence is verified by combining a historical case library. Finally, a structured causal tracing report is generated.

🎯Benefits of technology

It achieves high efficiency, interpretability, and reliability in cross-process defect tracing, reduces computational overhead, is suitable for the real-time and safety requirements of industrial sites, and provides efficient quality optimization support.

✦ Generated by Eureka AI based on patent content.

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Abstract

The present application relates to a kind of micro flaw-oriented metal bottle cap surface electroplating defect traceability analysis method, to solve the problem of bottle cap electroplating defect cause tracing difficulty and multi-source heterogeneous data fusion deficiency. By real-time acquisition of key process parameters, time stamp and equipment identifier on production line, and using semantic embedding and lightweight coding to generate multi-dimensional process anchoring data, cross-modal alignment with electroplating defect image is realized, and a spatiotemporal fusion dataset is constructed. Based on this dataset, the causal contribution of process variables to defects is identified in reverse, generating multi-level causal heat maps and interactive traceability reports. Combined with expert knowledge and manual review, the accuracy of the cause path is ensured and hierarchical visualization is achieved. This scheme can efficiently and accurately locate the cause of defects, improving the level of intelligent traceability and process optimization.
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