Automatic On-Wafer Probe Positioning System Based on Convolutional Neural Network Model

Journal Article (2025)
Author(s)

Z. Gao (TU Delft - Electrical Engineering, Mathematics and Computer Science)

A. Daalman (TU Delft - Electrical Engineering, Mathematics and Computer Science)

F. Mubarak (Van Swinden Laboratorium (VSL))

C. Gao (TU Delft - Electrical Engineering, Mathematics and Computer Science)

C. De Martino (TU Delft - Electrical Engineering, Mathematics and Computer Science, Vertigo Technologies)

S. Lehmann (GlobalFoundries)

M. Spirito (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Research Group
Electronics
DOI related publication
https://doi.org/10.1109/ARFTG65332.2025.11168138 Final published version
More Info
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Publication Year
2025
Language
English
Research Group
Electronics
Journal title
ARFTG Microwave Measurement Conference, ARFTG
Issue number
2025
Event
105th ARFTG Microwave Measurement Conference, ARFTG 2025 (2025-06-20 - 2025-06-20), San Francisco, United States
Page Views
71
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Abstract

In this work we present an automatic probe positioning system based on a commercial station environment and employing open loop piezo actuators for probe control. The proposed work utilizes open source convolutional neural networks (CNNs) to identify and track the probe and the landing pad. Benchmarking of the various software modules composing the automatic station is presented in terms of their speed, and absolute position tracking control. Moreover, a procedure to define t he “zero-landing” h eight isp roposed a nd u sed to evaluate the overall system landing accuracy. The proposed system demonstrates the ability to position the probe on IC aluminum pads with a standard deviation of 1.31μm and 0.96μm on the X and Y axes, respectively.

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