Artificial Intelligence and Machine Learning for Industry 4.0

This book is essential for any leader seeking to understand how to leverage intelligent automation and predictive maintenance to drive innovation, enhance productivity, and minimize downtime in their manufacturing processes. Intelligent automation is widely considered to have the greatest potential for Industry 4.0 innovations for corporations. Industrial machinery is increasingly being upgraded to intelligent machines that can perceive, act, evolve, and interact in an industrial environment. The innovative technologies featured in this machinery include the Internet of Things, cyber-physical systems, and artificial intelligence. Artificial intelligence enables computer systems to learn from experience, adapt to new input data, and perform intelligent tasks. The significance of AI is not found in its computational models, but in how humans can use them. Consistently observing equipment to keep it from malfunctioning is the procedure of predictive maintenance. Predictive maintenance includes a periodic maintenance schedule and anticipates equipment failure rather than responding to equipment problems. Currently, the industry is struggling to adopt a viable and trustworthy predictive maintenance plan for machinery. The goal of predictive maintenance is to reduce the amount of unanticipated downtime that a machine experiences due to a failure in a highly automated manufacturing line. In recent years, manufacturing across the globe has increasingly embraced the Industry 4.0 concept. Greater solutions than those offered by conventional maintenance are promised by machine learning, revealing precisely how AI and machine learning-based models are growing more prevalent in numerous industries for intelligent performance and greater productivity. This book emphasizes technological developments that could have great influence on an industrial revolution and introduces the fundamental technologies responsible for directing the development of innovative firms. Decision-making requires a vast intake of data and customization in the manufacturing process, which managers and machines both deal with on a regular basis. One of the biggest issues in this field is the capacity to foresee when maintenance of assets is necessary. Leaders in the sector will have to make careful decisions about how, when, and where to employ these technologies. Artificial Intelligence and Machine Learning for Industry 4.0offers contemporary technological advancements in AI and machine learning from an Industry 4.0 perspective, looking at their prospects, obstacles, and potential applications.

Table of Contents:
Preface xiii 1 Industry 4.0 and the AI/ML Era: Revolutionizing Manufacturing 1 Balusamy Nachiappan, C. Viji, N. Rajkumar, A. Mohanraj, N. Karthikeyan, Judeson Antony Kovilpillai J. and Pellakuri Vidyullatha 2 Business Intelligence and Big Data Analytics for Industry 4.0 29 N. Rajkumar, C. Viji, Balusamy Nachiappan, A. Mohanraj, N. Karthikeyan, Judeson Antony Kovilpillai J. and Sathiyaraj. R 3 "AI-Powered Mental Health Innovations": Handling the Effects of Industry 4.0 on Health 55 U Ananthanagu and Pooja Agarwal 4 AI ML Empowered Smart Buildings and Factories 87 Akey Sungheetha, Rajesh Sharma R., R. Chinnaiyan and G. S. Pradeep Ghantasala 5 Applications of Artificial Intelligence and Machine Learning in Industry 4.0 107 Tina Babu, Rekha R. Nair and Kishore S. 6 Application of Machine Learning in Moisture Content Prediction of Coffee Drying Process 145 Tuan M. Le, Thuy T. Tran, Hieu M. Tran and Son V.T. Dao 7 Survivable AI for Defense Strategies in Industry 4.0 169 Anuradha Reddy, G. S. Pradeep Ghantasala, Ochin Sharma, Mamatha Kurra, Kumar Dilip and Pellakuri Vidyullatha 8 Industry 4.0 Based Turbofan Performance Prediction 197 M. Sai Narayan, Prajakta P. Nandanwar, Annabathini Lokesh, Bathula Lakshmi Narayana, Varun Revadigar, Judeson Antony Kovilpillai J., Neelapala Anil Kumar and D.M. Deepak Raj 9 Industrial Predictive Maintenance for Sustainable Manufacturing 223 Mohammed Rihan, Ethiswar Muchherla, Shwejit Shri, Kushagra Jasoria, Judeson Antony Kovilpillai J. and G. S. Pradeep Ghantasala 10 Enhanced Security Framework with Blockchain for Industry 4.0 Cyber-Physical Systems, Exploring IoT Integration Challenges and Applications 247 P. Vijayalakshmi, B. Selvalakshmi, K. Subashini, Sudhakar G., Kavin Francis Xavier and Pradeepa K. 11 Integrating Artificial Intelligence and@Machine Learning for Enhanced Cyber Security in Industry 4.0: Designing a Smart Factory with IoT and CPS 267 Kavin Francis Xavier, Subashini K., Vijayalakshmi P., Selvalakshmi B., Sudhakar G. and Pradeepa K. 12 Application of AI and ML in Industry 4.0 287 V. Vinaya Kumari, G. S. Pradeep Ghantasala, S. A. Sahaaya Arul Mary, M. Thirunavukkarasan and Sathiyaraj. R References 303 About the Editors 307 Index 309