Konstantin Schmidt



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Types of publications

Journal article
Book chapter / Article in edited volumes
Authored book
Translation
Thesis
Edited Volume
Conference contribution
Other publication type
Unpublished / Preprint

Publication year

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To

Abstract

Journal

Development and validation of a digital twin framework for SMT manufacturing (2023) Seidel R, Rachinger B, Thielen N, Schmidt K, Meier S, Franke J Journal article A Methodology for Predictive Life Expectancy of Moisture-Sensitive SMT components using Neural Networks (2022) Schmidt K, Haas L, Latifi Bidarouni A, Reinhardt A, Döpper F, Franke J Journal article Machine Learning Based Quality Prediction for Solder Paste Dispensing in Electronics Production (2022) Thielen N, Pan W, Piechulek N, Voigt C, Meier S, Schmidt K, Franke J Conference contribution Trustworthiness of machine learning models in manufacturing applications using the example of electronics manufacturing processes (2022) Seidel R, Schmidt K, Thielen N, Franke J Conference contribution Studies and Analyses of Moisture Conditioned SMT-Components (2021) Haas L, Döpper F, Schmidt K, Franke J, Reinhardt A Conference contribution, Conference Contribution An Automated Optical Inspection System for PIP Solder Joint Classification Using Convolutional Neural Networks (2021) Schmidt K, Rauchensteiner D, Voigt C, Thielen N, Bönig J, Beitinger G, Franke J Conference contribution, Conference Contribution Clustering of Image Data to Enhance Machine Learning Based Quality Control in THT Manufacturing (2021) Thielen N, Jiang Z, Schmidt K, Seidel R, Voigt C, Reinhardt A, Franke J Conference contribution Enhanced X-Ray Inspection of Solder Joints in SMT Electronics Production using Convolutional Neural Networks (2020) Schmidt K, Thielen N, Voigt C, Seidel R, Franke J, Milde Y, Bonig J, Beitinger G Conference contribution Data Mining System Architecture for Industrial Internet of Things in Electronics Production (2020) Seidel R, Hassan Amada M, Fuchs J, Thielen N, Schmidt K, Voigt C, Franke J Conference contribution Development and Test of a Data Framework for Prediction of Soldering Quality in Selective Wave Soldering Applying K-Nearest Neighbors (2020) Seidel R, Thielen N, Schmidt K, Voigt C, Franke J Conference contribution