Development of Artificial Neural Network and Topology Reconstruction Schemes for Fan-Out Wafer Warpage Analysis

Wen Chun Wu, Kuo Shen Chen, Tang Yuan Chen, Dao Lung Chen, Yu Chin Lee, Chia Yu Chen, David Tarng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

How to accurate predict the topology of a constituted wafer and its warpage would be critical in improving processing reliabilities. Traditionally, Stoney equation has been widely used to correlate film stress and wafer warpage. However, it only works under ideal situation and could be deviated from real situation significantly. Many previous studies thus have been performed to revise the relation but these analytical-based formulations usually take single factor into consideration. In reality, multiple imperfection issues are usually simultaneously existed and pure analytical approach would be too challenging to yield useful results. Instead, data-driven methods such as artificial neural network might be feasible to achieve effective black box mapping to evaluate the problem. Specifically, the stress state of bi-layer structures with thicker, viscoelastic, and multi-layer films are investigated in this work to demonstrate the feasibility. The multilayer perception model is chosen and the effects of thick film, viscoelasticity, and multiple layers on film stress are individually investigated subsequently. Finally, all three factors are simultaneously considered under the same MLP structure and a 99% successful rate can be achieved based on a 5% deviation threshold with 2300 simulation data. Meanwhile, a program is designed to reconstruct and visualize the deformed wafer surface from local curvatures as the preparation for final real 3D reconstitute structure study in the future.

Original languageEnglish
Title of host publicationProceedings - IEEE 71st Electronic Components and Technology Conference, ECTC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1450-1456
Number of pages7
ISBN (Electronic)9780738145235
DOIs
Publication statusPublished - 2021
Event71st IEEE Electronic Components and Technology Conference, ECTC 2021 - Virtual, Online, United States
Duration: 2021 Jun 12021 Jul 4

Publication series

NameProceedings - Electronic Components and Technology Conference
Volume2021-June
ISSN (Print)0569-5503

Conference

Conference71st IEEE Electronic Components and Technology Conference, ECTC 2021
Country/TerritoryUnited States
CityVirtual, Online
Period21-06-0121-07-04

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Development of Artificial Neural Network and Topology Reconstruction Schemes for Fan-Out Wafer Warpage Analysis'. Together they form a unique fingerprint.

Cite this