A Deep Learning Framework for Simulation and Defect Prediction Applied in Microelectronics

no code implementations • 25 Feb 2020 • Nikolaos Dimitriou, Lampros Leontaris, Thanasis Vafeiadis, Dimosthenis Ioannidis, Tracy Wotherspoon, Gregory Tinker, Dimitrios Tzovaras

In particular, we propose an architecture based on 3D Convolutional Neural Networks (3DCNN) in order to model the geometric variations in manufacturing parameters and predict upcoming events related to sub-optimal performance.

Fault Diagnosis in Microelectronics Attachment via Deep Learning Analysis of 3D Laser Scans

no code implementations • 25 Feb 2020 • Nikolaos Dimitriou, Lampros Leontaris, Thanasis Vafeiadis, Dimosthenis Ioannidis, Tracy Wotherspoon, Gregory Tinker, Dimitrios Tzovaras

A common source of defects in manufacturing miniature Printed Circuits Boards (PCB) is the attachment of silicon die or other wire bondable components on a Liquid Crystal Polymer (LCP) substrate.