You are required to read and agree to the below before accessing a full-text version of an article in the IDE article repository.

The full-text document you are about to access is subject to national and international copyright laws. In most cases (but not necessarily all) the consequence is that personal use is allowed given that the copyright owner is duly acknowledged and respected. All other use (typically) require an explicit permission (often in writing) by the copyright owner.

For the reports in this repository we specifically note that

  • the use of articles under IEEE copyright is governed by the IEEE copyright policy (available at
  • the use of articles under ACM copyright is governed by the ACM copyright policy (available at
  • technical reports and other articles issued by M‰lardalen University is free for personal use. For other use, the explicit consent of the authors is required
  • in other cases, please contact the copyright owner for detailed information

By accepting I agree to acknowledge and respect the rights of the copyright owner of the document I am about to access.

If you are in doubt, feel free to contact

Artificial Intelligence in Predictive Maintenance: A Systematic Literature Review on Review Papers

Publication Type:

Conference/Workshop Paper


7th International Congress and Workshop on Industrial AI and eMaintenance


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


@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 = {}