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Journal of Intelligent Manufacturing
Published in: Journal of Intelligent Manufacturing 7/2023

21-06-2022

Knowledge-embedded machine learning and its applications in smart manufacturing

Authors: Farzam Farbiz, Mohd Salahuddin Habibullah, Brahim Hamadicharef, Tomasz Maszczyk, Saurabh Aggarwal

Published in: Journal of Intelligent Manufacturing | Issue 7/2023

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Abstract

Demands for more accurate machine learning models have given rise to rethinking current modeling approaches that were deemed unsuitable, primarily due to their computational complexity and the lack of availability and accessibility to representative data. In Industry 4.0, rapid advancements in Digital Twin (DT) technologies and the pervasiveness of cost-effective sensor technologies have pushed the incorporation of artificial intelligence, particularly data-driven machine learning models, for use in smart manufacturing. However, the persistent issue with such models is their high sensitivity to the training data and the lack of interpretability in the outcomes, at times generating unrealistic results. The incorporation of knowledge into the machine learning pipeline has been earmarked as the most promising approach to address such issues. This paper aims to answer this call through a Knowledge-embedded Machine Learning (KML) framework for smart manufacturing, which embeds knowledge from experience and, or physics information into the machine learning pipeline, thus making the outcomes from these models more representative of real applications. The merits of KML were then presented through comparative studies showing its capability to outperform knowledge-based and data-driven models. This promising outcome led to the development of frameworks that can potentially incorporate KML for smart manufacturing applications such as Prognostics and Health Management (PHM) and DT, further supporting the usefulness of the proposed KML framework.
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Metadata
Title
Knowledge-embedded machine learning and its applications in smart manufacturing
Authors
Farzam Farbiz
Mohd Salahuddin Habibullah
Brahim Hamadicharef
Tomasz Maszczyk
Saurabh Aggarwal
Publication date
21-06-2022
Publisher
Springer US
Published in
Journal of Intelligent Manufacturing / Issue 7/2023
Print ISSN: 0956-5515
Electronic ISSN: 1572-8145
DOI
https://doi.org/10.1007/s10845-022-01973-6

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