Chapter 2
Digital Transformation Using Industry 4.0 and Artificial Intelligence
M. Keerthika,
M. Pragadeesh,
M. Santhiya,
G. Belshia Jebamalar,
Harish Venu,
M. Keerthika
Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India
Search for more papers by this authorM. Pragadeesh
Department of Information Technology, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India
Search for more papers by this authorM. Santhiya
Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India
Search for more papers by this authorG. Belshia Jebamalar
Department of Computer Science and Engineering, S.A Engineering College, Chennai, Tamil Nadu, India
Search for more papers by this authorHarish Venu
Institute of Sustainable Energy (ISE), Universiti Tenaga Nasional, Putrajaya Campus, Malaysia
Search for more papers by this authorM. Keerthika,
M. Pragadeesh,
M. Santhiya,
G. Belshia Jebamalar,
Harish Venu,
M. Keerthika
Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India
Search for more papers by this authorM. Pragadeesh
Department of Information Technology, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India
Search for more papers by this authorM. Santhiya
Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India
Search for more papers by this authorG. Belshia Jebamalar
Department of Computer Science and Engineering, S.A Engineering College, Chennai, Tamil Nadu, India
Search for more papers by this authorHarish Venu
Institute of Sustainable Energy (ISE), Universiti Tenaga Nasional, Putrajaya Campus, Malaysia
Search for more papers by this authorBook Editor(s):Mahmoud Ragab AL-Refaey,
Amit Kumar Tyagi,
Abdullah Saad AL-Malaise AL-Ghamdi,
Swetta Kukreja,
Mahmoud Ragab AL-Refaey
Information Technology Department, Faculty of Computing and Information Technology (FCIT), King Abdulaziz University (KAU), Jeddah, Saudi Arabia
Mathematics Department, Faculty of Science, Al-Azhar University, Naseir City, Cairo, Egypt
Search for more papers by this authorAmit Kumar Tyagi
Department of Fashion Technology, National Institute of Fashion Technology, New Delhi, India
Search for more papers by this authorAbdullah Saad AL-Malaise AL-Ghamdi
Information Systems Department, Faculty of Computing and Information Technology (FCIT), King Abdulaziz University (KAU), Jeddah, Saudi Arabia
Information Systems Department, School of Engineering, Computing and Design, Dar Al-Hekma University, Jeddah, Saudi Arabia
Search for more papers by this authorSwetta Kukreja
Department of Computer Science and Engineering, Amity University, Mumbai, Maharashtra, India
Search for more papers by this authorFirst published: 05 April 2024
Summary
The establishment of the industry 4.0 project has resulted in an increase in interdependence, unpredictability, and the collection of enormous volumes of data, which has caused industrial settings to become ever more dynamic, connected, and inherently difficult. Industry 4.0, a paradigm that incorporates contemporary technology and advances, may be seen as a reality today. Industrial artificial intelligence (AI) has recently achieved strides that have highlighted its potential to aid manufacturers in overcoming the difficulties associated with the digital evolution of cyber- physical systems as well. This is due to its data-driven predictive modeling process and its capacity to support decision-making in highly complicated, nonlinear, and frequently multiple-stage settings. The main force is transforming industries because it allows intelligent robots to do self-regulation derivation, assessment, and analytics. Machine learning, as well as deep learning, particularly helps in manufacturing, and industries forecast their upkeep requirements and minimize delay. Explainable artificial intelligence (XAI) conducts studies and creates tools, techniques, and algorithm designs that produce information and judgments made by AI-based systems that are comprehensible to humans. Digital technology has revolutionized the manufacturing and industrial sectors. This chapter provides a thorough analysis of the AI based techniques used in the industry 4.0 paradigm for digital transformation. We first quickly go through the many technological innovations behind the idea of Industry 4.0. Then, along with details on what, how, why, and where these approaches have been applied for Industry 4.0, we provide a complete review of the main methodologies that have been used in the literature. We also discuss the potential and constraints that should lead future research toward moral or human-focused aspects among XAI networks that are needed to carry out high-stakes applications in commerce. This research aims to define and analyze AI's fundamental elements and recent advancements, providing a detailed definition and thorough comprehension within the context of the sector 4.0 trend. Researchers and manufacturers are hoping that the study's findings would enable them to better understand the circumstances and steps required for a seamless shift to Industry 4.0 with AI support for digital transformation.
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