A Systematic Literature Review on Transfer Learning for Predictive Maintenance in Industry 4.0

Saman Azari, MehdiLinnéuniversitetet,Institutionen för datavetenskap och medieteknik (DM),DISA;DISA-SIG,Linnaeus Univ, Dept Comp Sci & Media Technol, S-35195 Växjö, Sweden. (author)

The advent of Industry 4.0 has resulted in the widespread usage of novel paradigms and digital technologies within industrial production and manufacturing systems. The objective of making industrial operations monitoring easier also implied the usage of more effective data-driven predictive maintenance approaches, including those based on machine learning. Although those approaches are becoming increasingly popular, most of the traditional machine learning and deep learning algorithms experience the following three major challenges: 1) lack of training data (especially faulty data), 2) incompatible computation power, and 3) discrepancy in data distribution. A new data-driven technique, such as transfer learning, can be developed to overcome the issues related to traditional machine learning and deep learning for predictive maintenance. Motivated by the recent big interest towards transfer learning within computer science and artificial intelligence, in this paper we provide a systematic literature review addressing related research with a focus on predictive maintenance. The review aims to define transfer learning in the context of predictive maintenance by introducing a specific taxonomy based on relevant perspectives. We also discuss current advances, challenges, open-source datasets, and future directions of transfer learning applications in predictive maintenance from both theoretical and practical viewpoints.

Flammini, Francesco,Senior Lecturer,1978-Mälardalens universitet,Linnéuniversitetet,Institutionen för datavetenskap och medieteknik (DM),Mälardalen University, Sweden,Innovation och produktrealisering,Linnaeus Univ, Dept Comp Sci & Media Technol, S-35195 Växjö, Sweden(Swepub:mdh)ffi01 (author)
Santini, StefaniaUniv Naples Federico II, Dept Elect Engn & Informat Technol, I-80125 Naples, Italy. (author)
Caporuscio, Mauro,Professor,1975-Linnéuniversitetet,Institutionen för datavetenskap och medieteknik (DM),DISA;DISA-SIG,Linnaeus Univ, Dept Comp Sci & Media Technol, S-35195 Växjö, Sweden.(Swepub:lnu)macaab (author)
LinnéuniversitetetInstitutionen för datavetenskap och medieteknik (DM) (creator_code:org_t)

By the author/editor: Saman Azari, Meh ...; Flammini, France ...; Santini, Stefani ...; Caporuscio, Maur ...

About the subject

NATURAL SCIENCES: NATURAL SCIENCES; and Computer and Inf ...; and Computer Science ...

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