Industrial Automation Using Mobile Cyber Physical Systems

Industrial Automation Using Mobile Cyber Physical Systems

Thangavel M., Abhijith V. S., Sudersan S.
Copyright: © 2022 |Pages: 28
DOI: 10.4018/978-1-7998-8161-2.ch008
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Abstract

In recent years, the rise in the demand for quality products and services along with systems that could integrate the control mechanisms with high computational capabilities led to the evolution of cyber-physical systems (CPS). Due to the ongoing COVID-19 pandemic, several industries have remained closed, causing several monetary losses. Automation can help in such scenarios to keep the industries up and running in a way that the system could be monitored and controlled remotely using voice. The chapter deals with the integration of both industrial automation and cyber-physical systems in various industries like the automobile industry, manufacturing industries, construction industries, and so on. A proposed approach for machine handling using CPS, deep learning, and industrial automation with the help of voice. The proposed approach provides greater insights into the application of CPS in the area and the combination of CPS and deep learning to a greater extent.
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Introduction

The rapid advancements in computation methodologies and cloud computing along with a rapid expansion of the Internet of things have resulted in tremendous advancements in Cyber-Physical Systems (CPS) especially in industrial systems. As the name suggests, Cyber-physical systems integrate the cyber world with the physical. The integrated cyber and physical objects constitute a Cyber-Physical System (CPS).

The objects could be any hardware or software resources by which the computational process and other functions can be made possible on an extremely large scale especially in the case of industries or for larger communities. Here the term physical objects may refer to the already existing system or computational resources or large-scale production machines as in the industrial perspective. In short, CPS reiterates or modifies the way we communicate with the physical world. A more detailed explanation of CPS and Industrial Automation would be dealt with in the upcoming sections. Some of the main characteristics of CPS include:

  • 1.

    Querying and real-time for processing of the data and further processing,

  • 2.

    Decision making from the processed data,

  • 3.

    Providing the actual results and recommendations.

CPS over the years has provided efficient and innovative solutions in Healthcare management, Transportation systems, household appliances, distribution systems, Smart Grid, and much more.

The vision called “Smart Factory” is facilitated by the technological concepts of the CPS, Internet of Things, and the Internet of services. The CPS in the context of Industries creates a virtual copy of the physical world and makes decisions that are not centralized. T

That is how CPS helps in communicating seamlessly between the cyber world and the humans. The year 2020-21 has been marked by the COVID-19 pandemic, as a result of which several industries have either remain closed or went out of business, The pandemic has also made industrial experts rethink other production approaches-one such approach is Industrial automation.

Before getting to know what Industrial Automation is, the term “Automation” should be made clear. Automation is the process of providing products and services wherein the process involves minimal human intervention whereas mechanization is the process of manufacturing that requires more human-powered machines and involves decision-making by human intelligence. Thus when we complement Industries with

Automation we can replace manual labor with computer systems that provide better control and robustness than manually controlled systems. The benefits of Industrial automation are:

  • 1.

    Increase productivity

  • 2.

    Optimum Cost of Production

  • 3.

    Improve Product Quality

  • 4.

    Reduce routine check

  • 5.

    Increase Level of Safety

Thus, as a result, we get better products with fewer expenses incurred in production. In the scope of automation in industries, Industrial Automation (IA) is considered as the next step after mechanization. It not only reduces workload but also increases the production rate, quality, and reliability by adopting new technologies. The architecture of Industrial automation starts from the Field Level to the Control Level, Production level, and to the information level at the top. Based on the methodologies and the way of working the IA can be classified as Fixed, Programmable, Flexible and Integrated.

Some Problems in Industrial Automation are:

  • 1.

    Automation based devices are costly

  • 2.

    Training automation operating devices take time and are not cost-efficient

  • 3.

    Ambiguous predictions may lead to system failure

  • 4.

    Requires skilled labor for management and maintenance.

  • 5.

    Operating systems of devices need to be periodically trained and updated to manage the changing needs.

  • 6.

    Inability to manage remotely

  • 7.

    Integration makes it difficult to cope up with the trends

Key Terms in this Chapter

Mobile Cyber Physical Systems: The type of cyber physical systems wherein the physical system under study has inherent mobility.

Internet of Things: IoT represents the network of physical objects called Things that are embedded with the help of sensors, software and other technologies that serves the purpose of data exchange over the internet.

Wireless Sensor Networks (WSN): WSN refers to the networks of spatially dispersed and dedicated sensors that monitor and record the physical conditions of the environment and forward the collected data to a central location or base station.

Cyber Physical Systems: Cyber physical systems (CPS) are integration of computing, networking and physical processes making an intelligent system in which the entire mechanism is controlled based on computer-algorithms.

Industry 4.0: Industry 4.0 is the current trend of automation and data exchange in manufacturing technologies that includes cyber physical systems.

Sensors: A sensor is a device that detects the changes in the environment and responds to the change in the form an output signal to another system or actuator.

Deep Learning: A type of machine learning based on artificial neural networks in which several layers of processing happen that help in extracting higher level features of data.

Automation: Automation refers to the use of wide range of technologies that reduce human intervention in processes. In simpler terms, the technique of making a system operate automatically.

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