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Artificial Intelligence in Predictive Maintenance: A Systematic Literature Review on Review Papers
Publication Type:
Conference/Workshop Paper
Venue:
7th International Congress and Workshop on Industrial AI and eMaintenance
Abstract
In recent years, there has been a significant amount of focus paid
all across the globe to the fourth industrial revolution i.e. industry
4.0. There, the use of Artificial Intelligence backed industrial intel-
ligence in predictive maintenance (PdM) has been linked to the rise
of smart manufacturing and the advent of industry 4.0. Since in re-
cent years the number of articles focusing on Artificial Intelligence
(AI) in PdM is high a review on the available literature reviews in
this domain would be useful for the future researchers who would
like to advance the research in this area and also for the persons who
would like to apply PdM in their application domains. Therefore,
this study identifies the AI revolution in PdM and focuses on the
next stages available in the literature reviews in this area by qual-
ity assessment of secondary study.A well-known structured review
approach (Systematic Literature Review, or SLR) was employed to
perform this tertiary study. In addition, the SARNA approach for
evaluating the quality of review papers has been employed to sup-
port a few of the research questions. Here, this tertiary study con-
siders four key aspects of secondary articles: 1) particular research
areas, 2) the yearly tendencies in the quantity, variety, and quality 3)
a footsteps of top researchers, and 4) research constraints of review
articles between the year 2015 and 2022. The results show that the
majority of the application areas are applied to the manufacturing
industry. Year 2022, Scopus database, United States, Journals are
leading in terms of the number of published articles. It also leads
to the identification of the revolution of AI in PdM. X.Cheng et al.
are the dominant in this field, we could follow them as a newcomer
or industrial practitioner. The final outcome is that there is a lack of
progress in SLR formulation and in adding explainable or interpre-
tive AI methodologies in secondary studies
Bibtex
@inproceedings{Islam 6652,
author = {Md Rakibul Islam and Shahina Begum and Mobyen Uddin Ahmed},
title = {Artificial Intelligence in Predictive Maintenance: A Systematic Literature Review on Review Papers},
editor = {Prof. Uday Kumar, Prof. Ramin Karim, Prof. Diego Galar, and Dr. Ravdeep Kour},
month = {July},
year = {2023},
booktitle = {7th International Congress and Workshop on Industrial AI and eMaintenance},
url = {http://www.es.mdu.se/publications/6652-}
}
