Federated Learning for Predictive Maintenance and Quality Inspection in Industrial Applications

Author:

Pruckovskaja Viktorija1,Weissenfeld Axel2,Heistracher Clemens2,Graser Anita2,Kafka Julia3,Leputsch Peter3,Schall Daniel4,Kemnitz Jana4

Affiliation:

1. Technische Universität Wien,Vienna,Austria

2. Data Science & Artificial Intelligence AIT Austrian Institute of Technology,Vienna,Austria

3. Innovation Software Stiwa Automation,Attnang-Puchheim,Austria

4. Distributed AI Systems Research Siemens Technology,Vienna,Austria

Publisher

IEEE

Reference27 articles.

1. Fair resource allocation in federated learning;li;arXiv preprint arXiv 1905 10520,2019

2. Federated optimization in heterogeneous networks;li;arXiv preprint arXiv 1812 06798,2018

3. Federated learning: Strategies for improving communication efficiency;kone?ný;arXiv preprint arXiv 1610 05492,2016

4. Communication-efficient learning of deep networks from decentralized data;mcmahan;Artificial Intelligence and Statistics,2017

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2. A Workflow Management System Approach To Federated Learning: Application to Industry 4.0;2024 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT);2024-04-29

3. Federated Learning for Predictive Maintenance and Anomaly Detection Using Time Series Data Distribution Shifts in Manufacturing Processes;Sensors;2023-08-22

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