Improving process monitoring of ultrasonic metal welding using classical machine learning methods and process-informed time series evaluation-Reference-Cited by-同舟云学术

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Improving process monitoring of ultrasonic metal welding using classical machine learning methods and process-informed time series evaluation

Published:2022-05 Issue: Volume:77 Page:54-62
ISSN:1526-6125
Container-title:Journal of Manufacturing Processes
language:en
Short-container-title:Journal of Manufacturing Processes

Author:

Schwarz Elisabeth Birgit,Bleier Fabian,Guenter Friedhelm,Mikut Ralf,Bergmann Jean Pierre

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Reference40 articles.

1. Process monitoring of ultrasonic metal welding of battery tabs using external sensor data;Balz;J Adv Join Process,2020

2. Ultraschallfuegen und -trennen;Wodara,2004

3. Mechanical and microstructural characterization of ultrasonic metal welded large cross section aluminum wire/copper terminal joints;Gester,2019

4. Effect of the interface characteristics on the joint properties and diffusion mechanisms during ultrasonic metal welding of Al/Cu;Bergmann;Weld World,2017

5. Ultrasonic Metal Welding: Principles and Applications of High-grade Bonding Technology;Golde,1997

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4. Explainable few-shot learning for online anomaly detection in ultrasonic metal welding with varying configurations;Journal of Manufacturing Processes;2023-12

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