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Название: Advanced Manufacturing and Supply Chain with IoT: Revolutionizing Industries Through Smart Technologies and Connectivity
Автор: Ameya Deshpande, Bidyut Sarkar, Deep Dave, Ravi Dave
Издательство: BPB Publications
Год: 2024
Страниц: 414
Язык: английский
Формат: pdf, epub (true)
Размер: 11.0 MB

In the world of industrial manufacturing and supply chain, the lack of real-time visibility and insights into processes poses a significant challenge. However, IoT is set to bring about a profound transformation. This technological revolution promises efficiency gains, operational optimization, and unprecedented business insights.

Step into the world of Industry 4.0 and 5.0 with IoT and discover how it revolutionizes production and logistics. Learn about real-time monitoring, predictive maintenance, and quality control while ensuring a secure IoT infrastructure. Explore practical examples in manufacturing, including smart factories, personalized transit, and sustainability practices. Use the potential of AI, predictive analytics, and 3D printing to align your IoT strategies with business goals for enhanced performance.

Completing this book equips readers to excel in leveraging IoT for industrial manufacturing and supply chain advancements. They will master IoT concepts, optimize processes, and handle integration challenges. With the acquired knowledge, readers can develop strong IoT strategies, assess project outcomes effectively, and introduce significant improvements to their manufacturing and supply chain operations.

Driven by the integration of Artificial Intelligence (AI) and the Internet of Things (IoT), the manufacturing industry is in the midst of a digital revolution. AI and advanced analytics translate this data into valuable insights, enabling smart, self-optimizing production environments known as Industry 4.0. This chapter explores AI’s diverse applications in manufacturing, from shop floor operations to supply chain coordination, encompassing predictive maintenance, dynamic scheduling, defect detection, demand forecasting, and sustainability. Industrial IoT platforms, computer vision, natural language processing (NLP) and edge computing underpin this intelligent, interconnected manufacturing ecosystem. Successful adoption requires infrastructure upgrades, workforce reskilling, and change management, offering manufacturers the potential for increased throughput, cost reduction, improved quality control, and real-time market responsiveness. These technologies pave the way for factories that continuously self-optimize through data-driven learning and decision-making.

Chapter 1: IoT Fundamentals, Architecture, and Protocols - The introduction section of the book provides a comprehensive overview of the digital revolution and the ascent of IoT in advanced manufacturing. It explores the origins and pivotal technologies steering Industry 4.0, progressing toward Industry 5.0, characterized by human-machine collaboration. The section traces the evolution and milestones of IoT, detailing the enabling technologies and their transformative influence on industries. The role of IoT in manufacturing is emphasized, showcasing applications in predictive maintenance, production planning optimization, and quality control. Additionally, it examines IoT's transformative impact on supply chain management, focusing on real-time tracking, coordination, collaboration, and demand forecasting.

Chapter 2: Embracing IoT in Manufacturing - This chapter explores the transformative impact of IoT on manufacturing, focusing on real-time monitoring and maintenance with IoT-enabled sensors for predictive maintenance. It covers how IoT improves efficiency in production planning through real-time tracking and agile planning. Quality control is addressed, emphasizing automation, precision, and data analysis using IoT. Integrating robotics and IoT is discussed, covering innovation, safety, and maintenance. Real-world case studies illustrate IoT applications across various manufacturing processes, showcasing its role in monitoring, production planning, quality control, and robotics.
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Chapter 8: The Future of IoT - This chapter explores the potential of IoT in various industries, emphasizing the synergy of predictive analytics and AI for optimizing supply chain and manufacturing processes. A case study demonstrates using AI-driven predictive analytics within an IoT strategy. The intersection of blockchain and IoT is examined through a supply chain and manufacturing case study. The chapter delves into IoT's role in promoting supply chain sustainability, featuring a case study on IoT-powered sustainability efforts. Using a healthcare-focused case study, it explores the interaction of 3D printing and IoT in modern manufacturing. The final section underscores the significance of big data analytics for gaining valuable business insights and making data-driven decisions, emphasizing real-time processing and analysis capabilities when combining IoT and big data technologies.

Chapter 9: Key Takeaways - This chapter concludes the book by summarizing the key lessons learned from the IoT revolution in supply chain and manufacturing. It summarizes IoT's transformative power and impact on various topics, including real-time monitoring, predictive maintenance, production planning, quality control, and supply chain optimization.

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