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The book summarizes the results of the European research project "Intelligent fixtures for the manufacturing of low rigidity components" (INTEFIX). The structure of the book follows the sub-projects which are dedicated to case studies within the scenarios "vibrations", "deformations" and "positioning". The INTEFIX project deals with the development and analysis of several exemplary types of intelligent, sensor and actuator integrated fixtures for the clamping of sensitive workpieces in cutting machine tools. Thus, the book gives a representative overview about this innovative field of technology. The demands of the case studies are described and the technological approaches and solutions are introduced. Furthermore, innovative methods for the design and optimization of intelligent fixtures are presented.
Engineering. --- Mechanics. --- Mechanics, Applied. --- Machinery. --- Manufacturing industries. --- Machines. --- Tools. --- Industrial engineering. --- Manufacturing, Machines, Tools. --- Machinery and Machine Elements. --- Operating Procedures, Materials Treatment. --- Theoretical and Applied Mechanics. --- Mechanics, Applied --- Mathematical models. --- Technological innovations --- Applied mechanics --- Engineering, Mechanical --- Engineering mathematics --- Manufactures. --- Mechanics, applied. --- Manufacturing, Machines, Tools, Processes. --- Construction --- Industrial arts --- Technology --- Manufactured goods --- Manufactured products --- Products --- Products, Manufactured --- Commercial products --- Manufacturing industries --- Classical mechanics --- Newtonian mechanics --- Physics --- Dynamics --- Quantum theory --- Machinery --- Machines --- Manufactures --- Power (Mechanics) --- Mechanical engineering --- Motors --- Power transmission --- Curious devices
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The book summarizes the results of the European research project "Intelligent fixtures for the manufacturing of low rigidity components" (INTEFIX). The structure of the book follows the sub-projects which are dedicated to case studies within the scenarios "vibrations", "deformations" and "positioning". The INTEFIX project deals with the development and analysis of several exemplary types of intelligent, sensor and actuator integrated fixtures for the clamping of sensitive workpieces in cutting machine tools. Thus, the book gives a representative overview about this innovative field of technology. The demands of the case studies are described and the technological approaches and solutions are introduced. Furthermore, innovative methods for the design and optimization of intelligent fixtures are presented.
Classical mechanics. Field theory --- Machine elements --- Applied physical engineering --- Plant and equipment --- Production management --- fabrieken --- toegepaste mechanica --- productie --- machines --- ingenieurswetenschappen --- mechanica
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Machine Learning under Resource Constraints addresses novel machine learning algorithms that are challenged by high-throughput data, by high dimensions, or by complex structures of the data in three volumes. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Hence, modern computer architectures play a significant role. Novel machine learning algorithms are optimized with regard to minimal resource consumption. Moreover, learned predictions are executed on diverse architectures to save resources. It provides a comprehensive overview of the novel approaches to machine learning research that consider resource constraints, as well as the application of the described methods in various domains of science and engineering. Volume 3 describes how the resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples. In the areas of health and medicine, it is demonstrated how machine learning can improve risk modelling, diagnosis, and treatment selection for diseases. Machine learning supported quality control during the manufacturing process in a factory allows to reduce material and energy cost and save testing times is shown by the diverse real-time applications in electronics and steel production as well as milling. Additional application examples show, how machine-learning can make traffic, logistics and smart cities more effi cient and sustainable. Finally, mobile communications can benefi t substantially from machine learning, for example by uncovering hidden characteristics of the wireless channel.
SCIENCE / Chemistry / General. --- Artificial Intelligence. --- Big Data and Machine Learning. --- Cyber-physical systems. --- Data mining for Ubiquitous System Software. --- Embedded Systems and Machine Learning. --- Highly Distributed Data. --- ML on Small devices. --- Machine learning for knowledge discovery. --- Machine learning in high-energy physics. --- Resource-Aware Machine Learning. --- Resource-Constrained Data Analysis.
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