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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 117
Article Submitted : 21318
Article Published : 8476
Total Authors : 22301
Total Reviewer : 802
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| Paper Title: | Application of Predictive Maintenance and Machine Learning in Industry 4.0 |
| Authors Name: | Urmila Nagargoje , Sneha Bhor , Abhijeet Bhate , Sakshi Bhalsing |
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IJRTI_208699
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| Published Paper Id: | IJRTI2512135 |
| Published In: | Volume 10 Issue 12, December-2025 |
| DOI: | |
| Abstract: | Industry 4.0 represents a paradigm shift in industrial manufacturing through the integration of cyber–physical systems, Internet of Things (IoT), cloud computing, and advanced data analytics. Among the most impactful applications of this transformation is predictive maintenance (PdM), which leverages machine learning (ML) and data-driven models to predict equipment failures before they occur. Predictive maintenance minimizes unplanned downtime, reduces maintenance costs, improves asset reliability, and enhances operational efficiency. This paper presents a comprehensive review of predictive maintenance within the framework of Industry 4.0, focusing on the role of machine learning techniques in fault diagnosis, remaining useful life (RUL) estimation, and condition monitoring. Various ML approaches, including supervised, unsupervised, and deep learning models, are discussed along with their industrial applications. Case studies from manufacturing, energy, and process industries are reviewed to demonstrate practical implementation. Challenges related to data quality, model interpretability, cybersecurity, and scalability are also addressed. Finally, emerging trends such as physics-informed machine learning, digital twins, and edge-AI are explored, highlighting future research directions for intelligent maintenance systems in smart industries |
| Keywords: | Industry 4.0, Predictive Maintenance, Machine Learning, Smart Manufacturing, Industrial IoT |
| Cite Article: | "Application of Predictive Maintenance and Machine Learning in Industry 4.0", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 12, page no.b262-b266, December-2025, Available :http://www.ijrti.org/papers/IJRTI2512135.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2512135
Registration ID:208699
Published In: Volume 10 Issue 12, December-2025
DOI (Digital Object Identifier):
Page No: b262-b266 Country: Ahmadnagar, Maharashtra, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2512135 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2512135 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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