Industrial Transformation

Implementation and Essential Components and Processes of Digital Systems

Om Prakash Jena, Sudhansu Shekhar Patra, Mrutyunjaya Panda, Zdzislaw Polkowski, S. Balamurugan, Om Prakash Jena, Sudhansu Shekhar Patra, Mrutyunjaya Panda, Zdzislaw Polkowski, S. Balamurugan

• Publisher: CRC Press
• Year: 2022
• Print ISBN: 9781032133980
• eBook ISBN: 9781000567076
• Edition: 1
• Topic: Design
• Subtopic: Manufacturing

This book focuses on industrial development, design, implementation, and transformation using technologies such as Artificial Intelligence, Machine Learning, the Internet of Things (IoT), Big Data Analysis, and Blockchain. It incorporates complex processes, functions, and various other elements as one central component of digital systems.

Industrial Transformation: Implementation and Essential Components and Processes of Digital Systems discusses the industry transformation aligned with the computerization of manufacturing and the required skills needed to build a new workforce. This book covers the role that AI plays in the management of resource flow and decision-making in the transformation of operations, as well as supply chain management. It presents sustainability and efficiency with IoT, Machine Learning, Data Analysis, and Blockchain technologies as it focuses on industrial development, design, and implementation. This book showcases the incorporation of complex processes and functions as one central component of digital systems and explores current trends that are working to accelerate industrial transformation. Case studies are also included, depicting the technologies that are influencing the transition into the fourth Industrial Revolution, such as industrial infrastructure, biodiversity, and enhanced productivity.

This book is aimed at researchers, scholars, and students that require real-time knowledge and applications where the transformation and implementation of digital systems in the manufacturing sector are needed.

1Computational Intelligence for Automation of Industrial Processes

K. Sujatha, G. Nalinashini, N. Kanimozhi, A. Kalaivani, N.P.G. Bhavani, V. Srividhya and R. Vani

DOI: 10.1201/9781003229018-1

CONTENTS

• 1.1 Introduction
  • 1.1.1 Introduction to Industrial Boilers
  • 1.1.2 Introduction to Bottling System
  • 1.1.3 Introduction to Automated Inspection in Industries
  • 1.1.4 Introduction to Quality Assessment in Industries
• 1.2 Algorithms for Automation
  • 1.2.1 Discriminant Function Analysis
  • 1.2.2 Radial Basis Function (RBF)
  • 1.2.3 Fundamentals of Fuzzy Logic
  • 1.2.4 Importance of Deep Learning
  • 1.2.5 Recurrent Neural Network (RNN)
• 1.3 Existing Method
  • 1.3.1 Current System in Practice for Industrial Temperature Measurement in Combustion Chambers
  • 1.3.2 Current System in Practice for Level Measurement in Bottling Industries
  • 1.3.3 Current System in Practice for Manufacturing PCB
  • 1.3.4 Current System in Practice for Monitoring of Steel Sheet Fabrication
• 1.4 Proposed Method
  • 1.4.1 An Intelligent Approach to Recognize Furnace Flame Temperature in an Industrial Boiler
  • 1.4.2 Design of Self Tuning Controller for Level Control using Fuzzy Logic in Bottling Aerated Drinks
  • 1.4.3 Automated Testing of PCB using Sensor-Less Vision Based Technique
  • 1.4.4 Automatic Segmentation for Flaw detection in Steel Sheet Fabrication using Deep Learning Neural Networks
    • 1.4.4.1 Pre-Processing
    • 1.4.4.2 Feature Extraction
    • 1.4.4.3 Classification using RNN
• 1.5 Results and Discussion
  • 1.5.1 Temperature Measurement of Furnace Flame
  • 1.5.2 Level Monitoring and Control using FLC in Bottling Industries
  • 1.5.3 Quality Check During PCB Manufacturing
  • 1.5.4 Quality Assessment During Steel Sheet Fabrication
• 1.6 Conclusion
• References

1.1 Introduction

1.1.1 INTRODUCTION TO INDUSTRIAL BOILERS

The first section of automation includes an intelligent scheme to monitor the temperature from furnace flame for an industrial boiler. These boilers in the industry are used to generate steam, where the feed water is superheated to produce steam. The water tube boilers have tubes which carry water and this water will be heated up by the furnace flame, so that it gets converted to steam. Industrial boilers play an important role in power generation plants where the pulverized coal is burnt in the presence of oxygen to facilitate combustion. Generally, power plant steam is produced and plays an important role in the case of steam power plant. It is a must that an appropriate air to fuel ratio is maintained to confirm the complete combustion in industrial boilers that are used for power generation. The law of conservation of energy suggests that in boilers, the potential energy of the water stored along with the chemical and light energy during burning of coal is converted to heat energy which converts water to steam, followed by conversion to mechanical energy and electrical energy. This combustion process takes place inside the combustion chamber. When the fuel is burnt inside the combustion chamber, heat energy is produced, and exhaust gases are liberated. The heat energy produced generates steam due to the combustion process in the boiler furnace within the boiler. The performance of the boiler can be optimized to reduce the cost. There are two methods for optimization of the performance of the boiler. Improvement in combustion quality can be obtained by controlling flame temperature, which offers energy savings and reduces the cost in a boiler. Another method commonly used for combustion improvement is injecting a correct combination of air and fuel; optimizing this air fuel mixture increases the boiler performance. Combustion efficiency is indicated by the combustion improvement which is carried out within the boiler combustion process. The flame colour indicates the combustion quality approach where statistical indicators are used to access the patterns.

The entire chapter is organized with six broader sections like Introduction, Material and Methods, Existing Method, Proposed Method, Results, its related Discussion and Conclusion. Some of these broader sections also include sub divisions to give the readers a better understanding.

1.1.2 INTRODUCTION TO BOTTLING SYSTEM

The bottling system focuses on mathematical modelling and automation by using control logic. The system is divided into three modules for estimation, controller design circuit and hardware for the controller. The controller parameters are estimated on-line, followed by designing a suitable...

Table of contents

• Cover Page
• Half-Title Page
• Series Page
• Title Page
• Copyright Page
• Contents
• Preface
• Contributors
• Editor Biographies
• Chapter 1 Computational Intelligence for Automation of Industrial Processes
• Chapter 2 Machine Learning Applications for Additive Manufacturing: State-of-the-Art and Future Perspectives
• Chapter 3 Implementation of Total Productive Maintenance (TPM) in the Manufacturing Industry for Improving Production Effectiveness
• Chapter 4 Application of AI in Smart Cities
• Chapter 5 Effect of Sustainable Energy Sources for Load Frequency Control (LFC) of Single-Area Wind Power Systems
• Chapter 6 AI Technology in Networks-on-Chip
• Chapter 7 Modeling, Analysis, and Simulation of Hydrogen Leakage Jet in the Air
• Chapter 8 Multi-Objective Interval Assignment Problems and their Solutions using Genetic Algorithms
• Chapter 9 Evolutionary Approaches in Engineering Applications
• Chapter 10 Quality Prediction in Vertical Centrifugal Casting Using Criterion Function
• Chapter 11 On Type D Fuzzy Cellular Automata-Based MapReduce Model in Industry 4.0
• Chapter 12 Fine-Grained Feature Classification of Objects by Learning-Based Feature Selection Using Region-Proposal Convolutional Neural Network (RCNN)
• Chapter 13 An Embedded Implementation of a Traffic Light Detection System for Advanced Driver Assistance Systems
• Chapter 14 CO2 Emissions, Financial Development, and Renewable Energy Consumption (REC): A Metadata Analysis
• Chapter 15 A Machine Learning Approach for Translating Weather Information into Actionable Advisory for Farmers
• Chapter 16 Modeling of Fast Charging Electric Vehicles Using Different Controllers
• Chapter 17 Joining of AA7075/SiC Composite Using Friction Stir Welding (FSW)
• Chapter 18 Generation Scheduling of Solar-Wind-Hydro-Thermal Power System with Pumped Hydro Energy Storage using Squirrel Search Algorithm (SSA)
• Index