Variable confidence model determination method for solder joint reliability prediction and structure optimization

CN116579238BActive Publication Date: 2026-07-03CHINA ELECTRONIC TECH GRP CORP NO 38 RES INST +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
CHINA ELECTRONIC TECH GRP CORP NO 38 RES INST
Filing Date
2023-05-10
Publication Date
2026-07-03

AI Technical Summary

Technical Problem

The existing research mode of simulation plus the establishment of single-precision surrogate model is costly and has low modeling efficiency. It does not meet the reliability design requirements and cannot effectively predict the reliability of BGA device solder joints under temperature cyclic loads.

Method used

The co-kriging method is used for nested/non-nested sampling to establish a variable confidence surrogate model. Combined with the genetic algorithm to optimize the solder joint structural parameters, a variable confidence co-kriging model is constructed to predict solder joint reliability and optimize its structure.

Benefits of technology

It achieves efficient and low-cost solder joint reliability prediction and structural optimization, with better model fitting effect and higher accuracy, requiring fewer high-precision sample points, better optimization convergence, and improved reliability of BGA solder joints under temperature cyclic stress.

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Abstract

The application discloses a variable confidence model determination method for solder joint reliability prediction and structure optimization, belongs to the technical field of electronic component packaging, and comprises steps of sample selection, model construction, model verification and the like.The model has better fitting effect, higher precision, needs less high-precision sample points, that is, has lower cost, and has better model optimization convergence, thereby providing certain theoretical guidance for improving the reliability of BGA solder joints under the condition of temperature cycle stress.
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