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.
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
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.
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.
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.