Abstract
Nowadays, the main features of Industry 4.0 are interpreted to the ability of machines to communicate with each other and with a system, increasing the production efficiency and development of the decision-making mechanisms of robots. In these cases, new analytical algorithms of Industry 4.0 are needed. By using deep learning technologies, various industrial challenging problems in Industry 4.0 can be solved. Deep learning provides algorithms that can give better results on datasets owing to hidden layers. In this chapter, deep learning methods used in Industry 4.0 are examined and explained. In addition, data sets, metrics, methods, and tools used in the previous studies are explained. This study can lead to artificial intelligence studies with high potential to accelerate the implementation of Industry 4.0. Therefore, the authors believe that it will be very useful for researchers and practitioners who want to do research on this topic.
TopBackground
In order to understand the literature review section better, this section will focus on the introduction of Industry 4.0, deep learning and success metrics of the research. The research strategy of the study is also mentioned.
Key Terms in this Chapter
Deep Learning: Deep learning is an artificial neural network technique with hidden layers.
LSTM: The long short-term memory is an artificial repetitive neural network architecture used in deep learning.
CNN: Convolutional neural network is a sub-branch of deep learning and is often used to analyze visual information.
SVM: Support vector machine can be defined as a vector space-based machine learning method that finds a decision boundary between two classes that are farthest from any point in the training data.
Metrics: Metrics are the scales used to evaluate and compare of a performance system.
SMS: Systematic mapping studies provide an overview of a research area, and identify the quantity and type of research and results available within it.
IoT: The internet of things is to equip devices with the ability to transfer data to each other over a network.
Industry 4.0: Industry 4.0 is the subset of the fourth industry-related industrial revolution. It covers all smart systems.
RNN: Recurrent neural network is a class of artificial neural networks in which the connections between the nodes form a guided graphic across a temporary array.