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Applied Sciences
Volume 16
Issue 17
10.3390/app16178599
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Review

Machine Learning in Smart Manufacturing: Challenges and Solutions

by
Omar Adalat
1,
Nereida Polovina
2 and
Savas Konur
3,*
1
Department of Computing, Imperial College London, London M15 6BH, UK
2
Business School, Manchester Metropolitan University, Manchester M15 6BX, UK
3
School of Computer Science and Digital Technologies, Aston University, Birmingham B4 7ET, UK
*
Author to whom correspondence should be addressed.
Appl. Sci. 2026, 16(17), 8599; https://doi.org/10.3390/app16178599 (registering DOI)
Submission received: 16 July 2026 / Revised: 18 August 2026 / Accepted: 25 August 2026 / Published: 28 August 2026
(This article belongs to the Special Issue Advances in AI and Multiphysics Modelling)
Versions Notes

Abstract

In this paper, we consider the intertwined challenges that arise for process optimisation within smart manufacturing, reviewing fundamental aspects including concept drift in relation to the dynamic nature of manufacturing, the prevalence of heterogeneous data streams, integration of prior domain knowledge, and trustworthiness and transparency of machine learning models. We investigate the real-world nature of these challenges and the proposed solutions in the literature for each of the aforementioned challenges. Whilst other surveys exist for optimisation in the field of smart manufacturing, there is a lack of a comprehensive review addressing the underlying conceptual issues associated with the deployment and adoption of machine learning in smart manufacturing.
Keywords: smart manufacturing; industrial internet of things; machine learning; industrial informatics; artificial intelligence; heterogeneous data; trustworthy systems smart manufacturing; industrial internet of things; machine learning; industrial informatics; artificial intelligence; heterogeneous data; trustworthy systems

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MDPI and ACS Style

Adalat, O.; Polovina, N.; Konur, S. Machine Learning in Smart Manufacturing: Challenges and Solutions. Appl. Sci. 2026, 16, 8599. https://doi.org/10.3390/app16178599

AMA Style

Adalat O, Polovina N, Konur S. Machine Learning in Smart Manufacturing: Challenges and Solutions. Applied Sciences. 2026; 16(17):8599. https://doi.org/10.3390/app16178599

Chicago/Turabian Style

Adalat, Omar, Nereida Polovina, and Savas Konur. 2026. "Machine Learning in Smart Manufacturing: Challenges and Solutions" Applied Sciences 16, no. 17: 8599. https://doi.org/10.3390/app16178599

APA Style

Adalat, O., Polovina, N., & Konur, S. (2026). Machine Learning in Smart Manufacturing: Challenges and Solutions. Applied Sciences, 16(17), 8599. https://doi.org/10.3390/app16178599

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