Mechanical Systems And Artificial Intelligence
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MECHANICAL SYSTEMS and ARTIFICIAL INTELLIGENCE
Author: Dr. T.PREMKUMAR
language: en
Publisher: Brown Page Publication
Release Date: 2024-07-27
Table of Content The Mechanical Design Renaissance: How AI is reshaping the Field Artificial Intelligence (AI) CAD and CAD-Based Datasets Machine Learning in Mechanical Design and Optimization
ARTIFICIAL INTELLIGENCE FOR MECHANICAL ENGINEERING
The 21st century has ushered in a technological renaissance, with Artificial Intelligence (AI) standing at the forefront as a catalyst for innovation and transformation across every sphere of engineering. Once confined to the realm of computer science, AI has now firmly embedded itself in the domain of mechanical engineering, redefining how machines are designed, manufactured, operated, and maintained. This book, Artificial Intelligence for Mechanical Engineering, is an endeavor to bridge the gap between classical mechanical principles and modern computational intelligence, offering students, researchers, and industry professionals a comprehensive guide to harnessing AI in this dynamic field. Mechanical engineering, traditionally grounded in deterministic models and empirical testing, is witnessing an unprecedented shift toward data-driven, adaptive, and autonomous systems. Whether it is predictive maintenance in industrial plants, generative design in product development, AI-enhanced computational simulations, or intelligent robotics in manufacturing, the integration of AI has opened new horizons for efficiency, precision, and innovation. This transformation is not merely technological—it is philosophical, altering the way engineers perceive problems and conceive solutions. The impetus for writing this book arose from a recognition that while AI tools are rapidly advancing, their practical adoption in mechanical engineering requires both technical understanding and domain-specific adaptation. Many existing resources either focus heavily on AI theory without contextual application, or on mechanical engineering without adequately exploring AI’s potential. Our goal is to synthesize these perspectives—presenting AI concepts with clarity, grounding them in engineering fundamentals, and illustrating their use through real-world case studies.