AI Applications in Industry by Wai Yie Leong (.ePUB)+
File Size: 107.5 MB
AI Applications in Industry by Wai Yie Leong
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Overview: AI Applications in Industry offers a comprehensive and forward-looking exploration of how Artificial Intelligence (AI) is reshaping the global industrial landscape. From manufacturing and energy systems to healthcare, logistics, construction, and smart cities, this book examines the transformative power of AI in driving efficiency, safety, sustainability, and innovation across sectors. Written in a clear and authoritative style, the book bridges cutting-edge research with real-world implementation. It presents a structured overview of the key technologies—including Machine Learning, deep neural networks, Generative AI, digital twins, computer vision, robotics, edge–cloud computing, and autonomous systems—and demonstrates how these capabilities are being deployed to solve complex industrial challenges. Through case studies, architecture diagrams, and actionable frameworks, readers gain insights into how AI optimizes production lines, enhances quality assurance, enables predictive maintenance, strengthens supply-chain resilience, and accelerates the transition toward Industry 5.0 and 6.0 paradigms. Machine Learning provides the mathematical machinery for pattern recognition, anomaly detection, and predictive analytics. Regression models, support vector machines, and decision trees underpin predictive maintenance, demand forecasting, and defect detection. Deep Learning, with its convolutional neural networks and transformer architectures, extends these capabilities to high-dimensional data such as images, video, and time series, enabling automated quality assurance, natural language understanding, and process forecasting. Reinforcement Learning introduces adaptability, allowing robotic systems, logistics platforms, and energy controllers to learn through interaction, refining strategies through reward-driven optimization. Natural language processing unlocks insights from unstructured textual data – compliance documents, safety logs, operator manuals – bringing intelligence to the administrative layers of industry. Generative models, including GANs and diffusion systems, simulate industrial scenarios, accelerate design through generative design frameworks, and generate synthetic datasets for training. The convergence of these techniques allows industries to construct hybrid architectures tailored to their unique challenges, integrating perception, reasoning, and decision-making into coherent pipelines. This book also addresses the broader implications of AI adoption: governance, ethical considerations, cybersecurity, workforce transformation, ESG compliance, and the integration of human-centered design. With perspectives spanning engineering, policy, and strategic management, it equips industry leaders, engineers, researchers, policymakers, and students with a holistic understanding of AI’s impact on modern industry. AI Applications in Industry is an essential reference for anyone seeking to understand or lead the next wave of digital and industrial transformation. Whether you are an engineer, academic, manager, or innovator, this book provides the insights and tools needed to harness AI’s full potential in shaping tomorrow’s industries.
Genre: Non-Fiction > Tech & Devices
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