Effective parametric optimization for packaging design using Bayesian optimization

Dai，Weijing; Xue，Ke; Wu，Jingshen; Liu，Zihao

10.1109/ICEPT50128.2020.9202909

2020-08-01

978-1-7281-6827-2

2020 21st International Conference on Electronic Packaging Technology, ICEPT 2020

1-6

12-15 Aug. 2020

Guangzhou, China

As different structure, materials and components are widely applied in electronic packaging, complicated responses of these heterogenous but integrated parts subjecting to thermo-mechanical loading during manufacturing and usage are becoming a crucial issue to reliability of packaging. Therefore, how to find optimal engineering design of packaging receives growing attention. For the past, Design of Experiment (DoE) combined with statistical analysis is generally adopted. However, the increasing complexity of electronic packaging dramatically enlarges the amount of design parameters, making these traditional methods hard to maintain its efficiency. In current study, we implement Bayesian optimization with Gaussian process (BO-GP) as a framework to search the optimal combination of design parameters to reduce the warpage of a testing packaging vehicle. Upper confidence bound (UCB) method is adopted to define how this framework search in the design space. By employing simulated annealing algorithm, the BO-GP framework in this study can balance the exploration and exploitation within the space and present good convergence towards optimal design parameters.

Bayesian optimization engineering design machine learning Packaging parametric optimization warpage

第一

英语

EI

20204309396521

Machine learning ; Electronics packaging ; Statistical tests ; Packaging ; Design of experiments ; Monte Carlo methods

Heat Treatment Processes:537.1 ; Packaging, General:694.1 ; Artificial Intelligence:723.4 ; Engineering Research:901.3 ; Mathematical Statistics:922.2

2-s2.0-85093356585

Scopus

Southern University of Science and Technology,School of System Design and Intelligent Manufacturing,Shenzhen,China

Dai，Weijing,Xue，Ke,Wu，Jingshen,et al. Effective parametric optimization for packaging design using Bayesian optimization[C],2020:1-6.