ISSN2320-2882
Impact Factor9.17
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CrossRefDOI
ESTD2013
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Paper Title
Neural Networks for Predictive Maintenance in Manufacturing: An Adaptive Spatiotemporal Attention Framework
Authors
Dr. S. Brindha , Ms. T. Rajeshwari , Mr. N. Balaji , Ms. MB. Bhooshita , Mr. R. Gowri Shankar
Keywords
Predictive maintenance, Deep learning, spatiotemporal attention, multimodal sensor data, RUL estimation, fault detection, Industry 4.0.
Abstract
These instructions give you guidelines for preparing papers for IEEE Access. Use this document as a template if you are using Microsoft Word 6.0 or later. Otherwise, use this document as an instruction set. The electronic file of your paper will be formatted further at IEEE. Paper titles should be written in uppercase and lowercase letters, not all uppercase. Avoid writing long formulas with subscripts in the title; short formulas that identify the elements are fine (e.g., "Nd-Fe-B"). Do not write "(Invited)" in the title. Full names of authors are preferred in the author field, but are not required. Put a space between authors' initials. The abstract must be a concise yet comprehensive reflection of what is in your article. In particular, the abstract must be self-contained, without abbreviations, footnotes, or references. It should be a microcosm of the full article. The abstract must be between 150-250 words. Be sure that you adhere to these limits; otherwise, you will need to edit your abstract accordingly. The abstract must be written as one paragraph, and should not contain displayed mathematical equations or tabular material. The abstract should include three or four different keywords or phrases, as this will help readers to find it. It is important to avoid over-repetition of such phrases as this can result in a page being rejected by search engines. Ensure that your abstract reads well and is grammatically correct.
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How To Cite
Choose the style your journal or department asks for, then copy it. Every version below is generated from this paper's own record.
IJCRT — journal style
"Neural Networks for Predictive Maintenance in Manufacturing: An Adaptive Spatiotemporal Attention Framework", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.14, Issue 2, page no.c598-c602, February 2026, Available :https://ijcrt.org/papers/IJCRT2602289.pdf
APA — 7th edition
Brindha, S., Rajeshwari, T., Balaji, N., Bhooshita, M., & Shankar, R. G. (2026). Neural Networks for Predictive Maintenance in Manufacturing: An Adaptive Spatiotemporal Attention Framework. International Journal of Creative Research Thoughts, 14(2), c598-c602. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602289
MLA — 9th edition
Brindha, S., et al. "Neural Networks for Predictive Maintenance in Manufacturing: An Adaptive Spatiotemporal Attention Framework." International Journal of Creative Research Thoughts, vol. 14, no. 2, 2026, pp. c598-c602, https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602289.
Chicago — 17th, bibliography
Brindha, S., et al. "Neural Networks for Predictive Maintenance in Manufacturing: An Adaptive Spatiotemporal Attention Framework." International Journal of Creative Research Thoughts 14, no. 2 (2026): c598-c602. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602289.
Harvard — author–date
Brindha, S. et al. (2026) 'Neural Networks for Predictive Maintenance in Manufacturing: An Adaptive Spatiotemporal Attention Framework', International Journal of Creative Research Thoughts, 14(2), pp. c598-c602. Available at: https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602289
IEEE — numbered reference
S. Brindha, T. Rajeshwari, N. Balaji, M. Bhooshita and R. G. Shankar, "Neural Networks for Predictive Maintenance in Manufacturing: An Adaptive Spatiotemporal Attention Framework," IJCRT, vol. 14, no. 2, pp. c598-c602, Feb. 2026.
Vancouver — biomedical
Brindha S, Rajeshwari T, Balaji N, Bhooshita M, Shankar RG. Neural Networks for Predictive Maintenance in Manufacturing: An Adaptive Spatiotemporal Attention Framework. IJCRT. 2026 Feb;14(2):c598-c602.
AMA — 11th edition
Brindha S, Rajeshwari T, Balaji N, Bhooshita M, Shankar RG. Neural Networks for Predictive Maintenance in Manufacturing: An Adaptive Spatiotemporal Attention Framework. IJCRT. 2026;14(2):c598-c602. Accessed at https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602289
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT2602289,
author = {S. Brindha and T. Rajeshwari and N. Balaji and MB. Bhooshita and R. Gowri Shankar},
title = {Neural Networks for Predictive Maintenance in Manufacturing: An Adaptive Spatiotemporal Attention Framework},
journal = {International Journal of Creative Research Thoughts},
volume = {14},
number = {2},
pages = {c598-c602},
year = {2026},
month = {February},
issn = {2320-2882},
url = {https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602289}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Brindha, S.
AU - Rajeshwari, T.
AU - Balaji, N.
AU - Bhooshita, MB.
AU - Shankar, R. Gowri
TI - Neural Networks for Predictive Maintenance in Manufacturing: An Adaptive Spatiotemporal Attention Framework
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 14
IS - 2
PY - 2026
SN - 2320-2882
UR - https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602289
SP - c598-c602
ER -
Issue
Volume 14 Issue 2,
February-2026
Pages : c598-c602
Article Information
- Published In
- International Journal of Creative Research Thoughts — Volume 14, Issue 2, February 2026
- Pages
- c598-c602
- Published
- February 2026
- Registration ID
- IJCRT_301340
- Published Paper ID
- IJCRT2602289
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- Coimbatore, Tamil Nadu, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 201
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602289
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT2602289.pdf
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International Journal of Creative Research Thoughts
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2320-2882
ISSN
9.17
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2013
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Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal of Creative Research Thoughts for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
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