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This book provides both researchers in the academia, students, and industrial experts the chance to exchange new ideas, build relations, and find virtual partners. It is a scientific event whose proceedings have set a very high standard. ICORSE’s distinctive feature is represented by its breadth of topics: mechatronics, integronics and adaptronics; reliable systems engineering; cyber-physical systems; optics; theoretical and applied mechanics; robotics; modelling and simulation; smart integrated control systems; computer imaging processing; smart bio-medical and bio-mechatronic systems; MEMS and NEMS; new materials; sensors and transducers; nano-chemistry, physical chemistry of biological systems; micro- and nanotechnology; system optimization; communications, renewable energy and environmental engineering. They all come together to deliver a clear picture of the state of the art reached in these areas so far.
This current book comprises state-of-the-art research results in the field of mechatronics and reliable systems engineering, gathering papers from almost all continents. Since the chapters represent contributions of research scholars who work in both governmental financed institutions and in the business environment, one could infer that they certainly reflect a clear picture of the developments in these cutting-edge sciences. Moreover, the contributions are not limited to mechatronics, as nowadays it has grown to embed all smart technical sciences. Medical applications based on nano-technologies – seemingly the most promising of all newly developed branches – could not be left out of this work. It is our belief that the book is useful to both students, who want to learn from the best scholars (as most of the authors hold a Ph.D. degree and are well-known professors), and to researchers in all areas of smart engineering, who will definitely find here hot topics meant to inspire them in their line of work.
This book presents the proceedings of the 30th International Conference on Systems Engineering held at the University of Nevada, Las Vegas (UNLV), USA, during August 22-24, 2023. Research in the discipline of Systems Engineering is an important concept in the advancement of engineering and information sciences. Systems Engineering attempts to integrate many of the traditional engineering disciplines to solve large complex functioning engineering systems, dependent on components from all the disciplines. The research papers contained in these proceedings reflect the state of the art in systems engineering from all over the world and should serve as vital references to researchers to follow. The topics covered in this book include AeroSpace Systems, Cyber-Physical Systems, Autonomous Systems, Sensor Networks, Machine Learning and Analytics, Internet of Things, Applied Media Informatics and Technology, Control Systems, Energy Systems, Automotive Systems, Biological Systems, Vehicular Networking and Connected Vehicles, Aerospace Systems, Automation, Manufacturing, Smart Grids, Nonlinear Systems, Power Systems, Robotics, Social Systems, Economic Systems, and others. This book is a very good resource for graduate students, researchers, and scholars who want to learn about the most recent development in the fields.
This book introduces a new Model-Based Reliability System Engineering (MBRSE) methodology, including its concept connotation, basic theory and technologies, framework of integrated platform and engineering application cases. Different from traditional Reliability System Engineering (RSE) methods that mainly rely on the management of documents, MBRSE is model centric method, with which the design for hexability (including “reliability, maintainability, testability, supportability, environmental adaptability and safety”) is performed by the revolution of united models in complete R&D fields and the process of closed- loop failure mitigation. This method can integrate all techniques and approaches of reliability engineering into the main process of R&D, and therefore is considered as a generalized hexability design and analysis tool. Furthermore, the future perspectives in the development of MBRSE are also presented through the combination of Digital Twin technology. The main objective of the book is to provide the readers who have engaged in theoretical and technical researches, project management and engineering design applications of reliability engineering, as well as for teachers, senior undergraduates and postgraduates in colleges and universities working on reliability engineering and system engineering.
Guidelines for Risk Based Process Safety provides guidelines for industries that manufacture, consume, or handle chemicals, by focusing on new ways to design, correct, or improve process safety management practices. This new framework for thinking about process safety builds upon the original process safety management ideas published in the early 1990s, integrates industry lessons learned over the intervening years, utilizes applicable "total quality" principles (i.e., plan, do, check, act), and organizes it in a way that will be useful to all organizations - even those with relatively lower hazard activities - throughout the life-cycle of a company.
Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.