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Full Description
This book provides an in-depth exploration of cutting-edge research at the intersection of robotics, autonomous manufacturing, and intelligent production systems. It integrates theoretical foundations with applied case studies, offering readers both a conceptual framework and practical approaches to advancing the next generation of industrial technologies. The central focus lies in the convergence of smart sensor systems, predictive maintenance algorithms, fault detection methodologies, and advanced control systems engineering. These elements are examined not as isolated disciplines, but as interconnected pillars driving the transformation of modern manufacturing into highly adaptive, efficient, and resilient ecosystems. Key chapters include pioneering studies such as the effect of fluid-structure interaction on the instability of porous gas bearings, novel fault detection and localization methods in photovoltaic systems under dark conditions, and the prediction and control of burr formation in milling and drilling. Readers will also encounter innovative approaches like thermographic image preprocessing for fault diagnosis in electromechanical systems, predictive hysteresis modeling in discrete dynamic systems, and AI-based predictive modeling of tool life in Industry 4.0 contexts. Practical applications are highlighted through case studies on production process simulation, along with strategies to improve the productivity and sustainability of CNC machining via process monitoring. These contributions underline the importance of predictive and adaptive intelligence in addressing pressing industrial challenges such as minimizing downtime, optimizing energy consumption, ensuring process reliability, and extending equipment life cycles. The relevance of these topics lies in their direct response to the urgent demands of global manufacturing: sustainability, efficiency, and resilience in an era defined by Industry 4.0 and beyond. By bridging advanced theory with applied methodologies, the book not only contributes to academic research but also offers insights with real-world industrial impact. Ultimately, this book seeks to solve the challenge of how to design, monitor, and control intelligent manufacturing systems that are capable of adapting to uncertainty, predicting failures before they occur, and ensuring seamless integration of robotics and autonomous technologies.
Contents
Bridging Continents and Decades: The Evolution of the Mexican-Hungarian Collaboration in Manufacturing Science.- Effect of the Fluid-Structure Interaction and Frequency Ratio on the Dynamic Behavior of a Porous Gas Bearing.- Method of detection and location of open circuit faults in photovoltaic systems with pulsed red light operated under dark conditions.- Burr formation, prediction and measurement: review.- A material flow simulation module package.- Recent advancements in AI-assisted tool path generation for CNC machining.- Identifying Force-Velocity Hysteresis in Drilling with Physics-Informed Neural Networks.- Artificial Intelligence-Based Predictive Modeling of Tool Life in the Frame of Industry 4.0.- Modeling and simulation of wheelchair dynamics using the Hanavan model.- Influence of Fluid Type on Seismic Wave Propagation in Soils with Inclusions.
