This book presents an intelligent, integrated, problem-independent method for multiresponse process optimization. In contrast to traditional approaches, the idea of this method is to provide a unique model for the optimization of various processes, without imposition of assumptions relating to the type of process, the type and number of process parameters and responses, or interdependences among them. The presented method for experimental design of processes with multiple correlated responses is composed of three modules: an expert system that selects the experimental plan based on the orthogonal arrays; the factor effects approach, which performs processing of experimental data based on Taguchi's quality loss function and multivariate statistical methods; and process modeling and optimization based on artificial neural networks and metaheuristic optimization algorithms. The implementation is demonstrated using four case studies relating to high-tech industries and advanced, non-conventional processes.

This book gathers the proceedings of the 5th International Conference on the Industry 4.0 Model for Advanced Manufacturing (AMP 2020), held in Belgrade, Serbia, on 1-4 June 2020. The event marks the latest in a series of high-level conferences that bring together experts from academia and industry to exchange knowledge, ideas, experiences, research findings, and information in the field of manufacturing. The book addresses a wide range of topics, including: design of smart and intelligent products, developments in CAD/CAM technologies, rapid prototyping and reverse engineering, multistage manufacturing processes, manufacturing automation in the Industry 4.0 model, cloud-based products, and cyber-physical and reconfigurable manufacturing systems. By providing updates on key issues and highlighting recent advances in manufacturing engineering and technologies, the book supports the transfer of vital knowledge to the next generation of academics and practitioners. Further, it will appeal to anyone working or conducting research in this rapidly evolving field.

This book examines an intelligent system for the inspection planning of prismatic parts on coordinate measuring machines (CMMs). The content focuses on four main elements: the engineering ontology, the model of inspection planning for prismatic parts on CMMs, the optimisation model of the measuring path based on an ant-colony approach, and the model of probe configuration and setup planning based on a genetic algorithm. The model of inspection planning for CMMs developed here addresses inspection feature construction, the sampling strategy, probe accessibility analysis, automated collision-free operation, and probe path planning. The proposed model offers a novel approach to intelligent inspection, while also minimizing human involvement (and thus the risk of human error) through intelligent planning of the probe configuration and part setup. The advantages of this approach include: reduced preparation times due to the automatic generation of a measuring protocol; potential optimisation of the measuring probe path, i.e., less time needed for the actual measurement; and increased planning process autonomy through minimal human involvement in the setup analysis and probe configuration.

This book presents the proceedings of the 3rd International Conference on the Industry 4.0 Model for Advanced Manufacturing (AMP 2018), held in Belgrade, Serbia, on 5-7 June 2018, the latest in a series of high-level conferences that brings together experts from academia and industry to exchange knowledge, ideas, experiences, research findings, and information in the field of manufacturing. The book addresses a wide range of topics, including, for example, design of smart and intelligent products, developments in CAD/CAM technologies, rapid prototyping and reverse engineering, multistage manufacturing processes, manufacturing automation in the Industry 4.0 model, cloud-based products, and cyber-physical and reconfigurable manufacturing systems. By providing updates on key issues and recent advances in manufacturing engineering and technologies, it aids the transfer of vital knowledge to the next generation of academics and practitioners. It appeals to anyone working or conducting research in this rapidly evolving field.

This book gathers the proceedings of the 5th International Conference on the Industry 4.0 Model for Advanced Manufacturing (AMP 2020), held in Belgrade, Serbia, on 1-4 June 2020. The event marks the latest in a series of high-level conferences that bring together experts from academia and industry to exchange knowledge, ideas, experiences, research findings, and information in the field of manufacturing. The book addresses a wide range of topics, including: design of smart and intelligent products, developments in CAD/CAM technologies, rapid prototyping and reverse engineering, multistage manufacturing processes, manufacturing automation in the Industry 4.0 model, cloud-based products, and cyber-physical and reconfigurable manufacturing systems. By providing updates on key issues and highlighting recent advances in manufacturing engineering and technologies, the book supports the transfer of vital knowledge to the next generation of academics and practitioners. Further, it will appeal to anyone working or conducting research in this rapidly evolving field.

This book examines an intelligent system for the inspection planning of prismatic parts on coordinate measuring machines (CMMs). The content focuses on four main elements: the engineering ontology, the model of inspection planning for prismatic parts on CMMs, the optimisation model of the measuring path based on an ant-colony approach, and the model of probe configuration and setup planning based on a genetic algorithm. The model of inspection planning for CMMs developed here addresses inspection feature construction, the sampling strategy, probe accessibility analysis, automated collision-free operation, and probe path planning. The proposed model offers a novel approach to intelligent inspection, while also minimizing human involvement (and thus the risk of human error) through intelligent planning of the probe configuration and part setup. The advantages of this approach include: reduced preparation times due to the automatic generation of a measuring protocol; potential optimisation of the measuring probe path, i.e., less time needed for the actual measurement; and increased planning process autonomy through minimal human involvement in the setup analysis and probe configuration.

This book gathers the proceedings of the 12th International Conference on Measurement and Quality Control - Cyber Physical Issues (IMEKO TC 14 2019), held in Belgrade, Serbia, on 4-7 June 2019. The event marks the latest in a series of high-level conferences that bring together experts from academia and industry to exchange knowledge, ideas, experiences, research findings, and information in the field of measurement of geometrical quantities. The book addresses a wide range of topics, including: 3D measurement of GPS characteristics, measurement of gears and threads, measurement of roughness, micro- and nano-metrology, laser metrology for precision measurements, cyber physical metrology, optical measurement techniques, industrial computed tomography, multisensor techniques, intelligent measurement systems, evaluating measurement uncertainty, dimensional management in industry, product quality assurance methods, and big data analytics. By providing updates on key issues and highlighting recent advances in measurement and quality control, the book supports the transfer of vital knowledge to the next generation of academics and practitioners.

This book presents an intelligent, integrated, problem-independent method for multiresponse process optimization. In contrast to traditional approaches, the idea of this method is to provide a unique model for the optimization of various processes, without imposition of assumptions relating to the type of process, the type and number of process parameters and responses, or interdependences among them. The presented method for experimental design of processes with multiple correlated responses is composed of three modules: an expert system that selects the experimental plan based on the orthogonal arrays; the factor effects approach, which performs processing of experimental data based on Taguchi's quality loss function and multivariate statistical methods; and process modeling and optimization based on artificial neural networks and metaheuristic optimization algorithms. The implementation is demonstrated using four case studies relating to high-tech industries and advanced, non-conventional processes.

This book gathers the proceedings of the 4th International Conference on the Industry 4.0 Model for Advanced Manufacturing (AMP 2019), held in Belgrade, Serbia, on 3-6 June 2019. The event marks the latest in a series of high-level conferences that bring together experts from academia and industry to exchange knowledge, ideas, experiences, research findings, and information in the field of manufacturing. The book addresses a wide range of topics, including: design of smart and intelligent products, developments in CAD/CAM technologies, rapid prototyping and reverse engineering, multistage manufacturing processes, manufacturing automation in the Industry 4.0 model, cloud-based products, and cyber-physical and reconfigurable manufacturing systems. By providing updates on key issues and highlighting recent advances in manufacturing engineering and technologies, the book supports the transfer of vital knowledge to the next generation of academics and practitioners. Further, it will appeal to anyone working or conducting research in this rapidly evolving field.