UV curing machine operation energy consumption analysis method based on machine learning

By constructing a device feature matrix and performing cluster analysis, combined with a machine learning model, the problem of inaccurate energy consumption prediction for UV curing machines was solved, achieving more accurate energy consumption prediction.

CN120850832AActive Publication Date: 2025-10-28SUZHOU HUI YING OPTICAL TECH CO LTD
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Patent Information

Application Number
CN202511362298.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-09-23
Publication Date
2025-10-28
Estimated Expiration
2045-09-23

AI Technical Summary

Technical Problem

Existing energy consumption analysis methods for UV curing machines cannot effectively address the differences between different plate types and chip types, resulting in inaccurate energy consumption predictions.

Method used

By constructing a device feature matrix, the distance consistency and layout similarity of circuit board components are quantified, cluster analysis is performed, and a prediction model for adhesive application and curing parameters is constructed. Combined with machine learning techniques such as GNN, LSTM and CNN, the energy consumption of the UV curing machine is predicted.

Benefits of technology

This improves the accuracy of energy consumption prediction during the UV curing process of circuit board coating and curing, and avoids energy consumption prediction distortion caused by fuzzy curing parameters.

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Abstract

The invention relates to the technical field of data processing, and provides a UV curing machine operation energy consumption analysis method based on machine learning, and the method comprises the steps: collecting related parameters and related data of a plurality of circuit boards, recording the feature codes of all elements on the circuit boards, recording a plurality of gluing parameters, curing parameters and energy consumption levels in the gluing and curing process of each circuit board by the UV curing machine; constructing a device characteristic matrix of each circuit board; obtaining the distance consistency of the two elements, and further obtaining the layout similarity of the two elements; obtaining a plurality of matching element pairs of the two circuit boards; quantifying the pattern similarity of the two circuit boards; obtaining a plurality of types of circuit boards; constructing a gluing parameter prediction model; and constructing a curing energy consumption prediction model, and predicting the energy consumption in the circuit board gluing and curing process. The method aims at solving the problem that energy consumption of fixed curing parameters is obviously different in the curing process of chips of different types.
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