Thermomechanical Oriented Reliability Enhancement of Si MOSFET Panel-Level Packaging Fusing Ant Colony Optimization With Backpropagation Neural Network

Jiang, Jing; None, Wei Chen; Qian, Yichen; Meda, Abdulmelik H.; Fan, X.; Zhang, Kouchi; Fan, J.

doi:10.1109/TCPMT.2023.3267411

Thermomechanical Oriented Reliability Enhancement of Si MOSFET Panel-Level Packaging Fusing Ant Colony Optimization With Backpropagation Neural Network

Journal article (2023)

Authors

Jing Jiang Fudan University

Wei Chen Fudan University

Yichen Qian Hohai University

Abdulmelik H. Meda The Hong Kong Polytechnic University

X. Fan Lamar University

Kouchi Zhang Electronic Components, Technology and Materials -

J. Fan Fudan University

Research Group

Electronic Components, Technology and Materials () (TU Delft)

DOI: https://doi.org/10.1109/TCPMT.2023.3267411

Stress Genetic Algorithm Packaging Reliability MOSFET Thermal resistance Thermal stresses Ant Colony Neural Network Fan-out panel-level packaging Power device Reliability optimization Thermomechanical processes

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Published Date

2023

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Electronic Components, Technology and Materials

Abstract

Considerable advancements in power semiconductor devices have resulted in such devices being increasingly adopted in applications of energy generation, conversion, and transmission. Hence, we proposed a fan-out panel-level packaging (FOPLP) design for 30-V Si-based metal-oxide-semiconductor field-effect transistor (MOSFET). To achieve superior reliability of packaging, we applied the nondominated sorting genetic algorithm with elitist strategy (NSGA-II) and ant colony optimization-backpropagation neural network (ACO-BPNN) to optimize the design of redistribution layer (RDL) in FOPLP. We first quantified the thermal resistance and thermomechanical coupling stress of the designed package under thermal cycling loading. Next, NSGA-II and ACO-BPNN were used to optimize the size of the RDL blind via. Finally, the effectiveness of the proposed reliability optimization methods was verified by performing thermal shock reliability aging tests on the prepared devices.

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