Encapsulation mold testing and production data processing and prediction method and system

By setting up a sensor group in the packaging mold and establishing a multi-condition strain correlation prediction model, the data deviation problem in mold testing was solved, enabling accurate prediction and dynamic optimization management of mold performance, and improving production stability and mold service life.

CN122143294APending Publication Date: 2026-06-05DONGGUAN KUNQI PRECISION IND CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
DONGGUAN KUNQI PRECISION IND CO LTD
Filing Date
2026-03-06
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing packaging mold testing methods cannot fully simulate the coupling effect of thermal cycling stress and mechanical stress in actual production, resulting in significant deviations between test results and real working conditions. Furthermore, they lack the ability to monitor the strain distribution inside the mold in real time, making it difficult to establish an effective performance degradation prediction mechanism.

Method used

A sensor array is set up in the mold under test to collect test data under multiple working conditions, establish a multi-condition strain correlation prediction model, correct the no-load test data through the load influence coefficient, dynamically update the model parameters, and predict the performance degradation of the mold.

Benefits of technology

It enables real-time dynamic monitoring of mold strain distribution, accurately predicts mold performance degradation trends, eliminates systematic errors between no-load and loaded states, supports early warning of production quality failure thresholds, extends mold life, and improves production stability.

✦ Generated by Eureka AI based on patent content.

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Abstract

The present application relates to a kind of encapsulation mold test and production data processing and prediction method.The method includes: setting sensor group in each detection position;At least one preset test condition is executed to obtain test data;According to test data, obtain the multi-condition strain correlation prediction model of each detection position in preset test condition;Sample production data obtained by each sensor group;Compare the comparison value of production data and test data under the same test parameter in preset test condition, obtain model error;Update model error to multi-condition strain correlation prediction model, in multiple preset production cycle, the model error attenuation value under the same test parameter is calculated, the performance attenuation value of the packaging mold to be measured in each preset production cycle is predicted;According to performance attenuation value, the production quality failure threshold of the packaging mold to be measured is calculated.The present application predicts mold performance attenuation and calculates production quality failure threshold, effectively improves production stability and mold service life.
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