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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 : 21311
Article Published : 8476
Total Authors : 22301
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| Paper Title: | Hybrid Deep Learning Model for the Smart Manufacturing |
| Authors Name: | Himani Saini , Jasminder kaur |
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IJRTI_186783
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| Published Paper Id: | IJRTI2305159 |
| Published In: | Volume 8 Issue 5, May-2023 |
| DOI: | |
| Abstract: | Predictive maintenance, production scheduling, and machine health monitoring (MHM) are just a few of the areas of smart factories where timeseries forecasting is used. Machine speed prediction can optimize production throughput, lower energy consumption, and dynamically modify production processes depending on different system variables in smart factories. Making precise, data-driven predictions about machine speeds is difficult, though. Due to the complexity of the data generated by industrial production processes, predictive models that are robust to noise and can reflect the temporal and spatial distributions of timeseries signals are required for successful forecasting. Inspired by current deep learning efforts in smart manufacturing, this paper proposes an end-to-end framework for multi-step machine speed prediction. The model, also known as the 2D-Convolutional LSTM Autoencoder, is composed of the deep convolutional LSTM (ConvLSTM) encoder-decoder framework. When contrasted to cutting-edge predictive models, the utility of the suggested method is demonstrated by extensive empirical evaluations utilising real-world data from a metal packing plant in the United Kingdom. |
| Keywords: | Smart Manufacturing, LSTM, 2DConvLSTMAE, CNN |
| Cite Article: | "Hybrid Deep Learning Model for the Smart Manufacturing", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 5, page no.1007 - 1015, May-2023, Available :http://www.ijrti.org/papers/IJRTI2305159.pdf |
| Downloads: | 000205240 |
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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: IJRTI2305159
Registration ID:186783
Published In: Volume 8 Issue 5, May-2023
DOI (Digital Object Identifier):
Page No: 1007 - 1015 Country: delhi, delhi, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2305159 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2305159 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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