Advanced Signal Processing for Industry 4.0, Volume 1

This book describes the use of advance signal processing techniques for different Industry 4.0 applications, including: Non-destructive testing, Decisions under Parametric Uncertainty, Deep learning for industrial sector, Energy-efficient Industry 4.0 etc. The book will help readers to understand future needs of industries.

Industry 4.0 is an amalgamation of digital technologies with the industries; it is required for enhancing production, flexibility and scalability in industries. This field of research is a rapidly changing domain. It is also a multifaceted area of research including signal processing, computer vision, artificial intelligence, manufacturing, production engineering, etc. This book brings together professionals from academia and industry to present a review of state of knowledge in the fields of advanced signal and vision processing, the Industrial Internet of Things, AI and machine learning, signal processing for smart manufacturing, cyber-physical systems and intelligent systems for industries as applied to the implementation of Industry 4.0. The book will help readers to understand future needs of industries.

Key Features:

• Includes both signal and image processing, including real time methods
• Focus on real-time signal processing and control
• Contains current trends in AI for industries
• Industrial and academic authors
• Multidisciplinary

1 Robotics Vision for Industrial Automation
The chapter provides introduction to robotic vision for industrial Automation. Vision processing is the basis on which the foundation of the Industry 4.0 is laid.
2 A practical system based on CNN-LSTM Network for Gear Fault Diagnosis
Early fault diagnosis in complex mechanical systems such as a gearbox has always been a great challenge, even with the recent development in deep neural networks. In this chapter, the CNN structure is used to extract high-level features and then the BLSTM network is used to obtain the features related to the passage of steps or long-term dependencies, and finally the connected network is used to classify for Gear Fault Diagnosis.
3 Applications of Statistical Signal Processing for Infrared Non-Destructive Testing and Evaluation
Statistical data processing approaches gained importance due to its enhanced sub-surface defect detection capabilities for inspection of various industrial material. This chapter presents the capabilities of Principal Component Thermography (PCT) for infrared non-destructive testing and evaluation applications. Further, a detailed comparison has been proposed among the adopted post-processing approaches.
4 Real-time Signal Processing for quick decision making
Real-time signal processing is an important area to control process in real-time. This chapter will deal with that.
5 The Evolution of Cyber Physical Systems for Industry
Cyber physical systems are an example of seamless integration between computers and humans. It helps to develop integration that was not possible in earlier phases of industry. The same will be discussed here
6 Industrial Internet of Things and Its Application
Communication forms the backbone of future industries and IoT is the mechanism to achieve it. How present issues of Industries can be tackled using IoT will be discussed here
7 Artificial Intelligence in Industry 4.0
Large amount of sensor data will be generated, and AI algorithms are required to work with such data. The working of these techniques will be discussed here.
8 Customer-centric health technologies in Industry 4.0
A distributed environment is required to store data in Industry 4.0 and Cloud computing is a way to achieve it. This Chapter will be dedicated to that.
9 Different Industrial data and its Protection techniques
With large amount of data generated, signal and data security becomes a major area of research. The generated data node needs to be protected from any attack. The same will be discussed here.
10 Automation and Control in Industries using sensor data
Automation is an important element in future industrial application. The same can be achieved with advanced signal processing techniques in an effective way. This will be discussed in this chapter.
11 Smart Factories with smart signal processing
Creating of smart factories is the aim behind future industrial revolution. The application of signal processing is main key to that. The same will be discussed in this Chapter.
12 Sensor Integration for Process Control and Industry 4.0
Process and organization control is again a major area of research in future industries. The same will be focused here.