Multidisciplinary Design and Optimization Methodologies in Electronics Packaging: State-of-the-Art Review

多学科设计优化 数码产品 多学科方法 计算机科学 软件 计算机辅助设计 过程(计算) 计算机辅助设计 系统工程 可靠性工程 优化设计 工程类 控制工程 机械工程 工程制图 社会科学 机器学习 社会学 电气工程 程序设计语言 操作系统
作者
Hamid Hadim,Tohru Suwa
出处
期刊:Journal of Electronic Packaging [ASM International]
卷期号:130 (3) 被引量:16
标识
DOI:10.1115/1.2957459
摘要

Electronics packaging design is a process that requires optimized solutions based on multidisciplinary design trade-offs, which usually have complex relationships among multiple design variables. Required numerical analyses combining electrical, thermal, and thermomechanical, among others, have made the multidisciplinary design and optimization process more challenging because of their time-intensive modeling and computation. In this paper, a state-of-the-art review of recent multidisciplinary design and optimization methodologies in electronics packaging is presented. The reported methodologies are divided into three groups: (1) integrated multidisciplinary computer aided design (CAD) environment, (2) semi-automated design optimization techniques, and (3) automated component placement techniques. In the first group, multidisciplinary design and optimization are carried out using interactive CAD environment software. The electronics packaging designer inputs data and makes decisions, while the CAD software provides a comprehensive multidisciplinary modeling and simulation environment. In the second group, using semi-automated design optimization methodologies, various objectives are optimized simultaneously mainly based on package configurations (dimensions), material properties, and operating conditions. In the third group, optimal placement of heat generating components is performed automatically based on multiple requirements. In recent years, methodologies using (1) detailed numerical analysis models directly connected to optimization algorithms, (2) design of experiments (DoE), and (3) artificial neural networks (ANNs) have been proposed as new trends in this field. These methodologies have led to significant improvement in design optimization capabilities, while they require intensive computational effort. Advantages as well as disadvantages of these methods are discussed.

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