Predictive Maintenance Using Machine Learning

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Outline:

1 Theoretical Framework
1.1 Maintenance
1.1.1 Why Should Machines Be maintained?
1.1.2 The analysis of the different forms of maintenance is based on 4 concepts:
1.2 Types of Maintenance
1.3 Machine Learning
1.4 Deep Learning
1.4.1 Types of Machine Learning Algorithms
1.4.2 Recurrent Neural Networks(RNN)
1.4.3 Application of Deep learning
1.5 Previous Papers review
2 Case Study
2.1 Software and Hardware Environment
2.2 Modeling Of Data-set
2.2.1 System Modeling
2.2.2 Damage Propagation Modeling
2.3 Models used
2.3.1 Model Configuration
2.3.2 Gated Recurrent Units (GRU) .
2.3.3 Long Short Term Memory(LSTM).
2.3.4 Simple Recurrent Network(SRN)
2.3.5 The Use of CuDNN
3 Results and Analysis
3.1 Long Short Term Memory(LSTM) Model
3.1.1 CuDNNLSTM
3.2 Gated Recurrent Unit(GRU) Model .
3.2.1 CuDNNGRU .
3.3 Simple Recurrent Network(SRN)
3.4 Discussion
3.4.1 Overall Table of Results
3.4.2 Interpretation .
4 Future Work
4.1 Stacking LSTM cell, SRN cell and GRU cell
5 Conclusion
Nomenclature

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