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Inhaltsangabe
This book addresses the emerging paradigm of data-driven engineering design. In the big-data era, data is becoming a strategic asset for global manufacturers. This book shows how the power of data can be leveraged to drive the engineering design process, in particular, the early-stage design.
Based on novel combinations of standing design methodology and the emerging data science, the book presents a collection of theoretically sound and practically viable design frameworks, which are intended to address a variety of critical design activities including conceptual design, complexity management, smart customization, smart product design, product service integration, and so forth. In addition, it includes a number of detailed case studies to showcase the application of data-driven engineering design. The book concludes with a set of promising research questions that warrant further investigation.
Given its scope, the book will appeal to a broad readership, including postgraduate students, researchers, lecturers, and practitioners in the field of engineering design.
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Über die Autorin bzw. den Autor
Dr. Ang Liu is an Associate Professor of Engineering Design at the School of Mechanical and Manufacturing Engineering, University of New South Wales, Australia. He received his M.S. and Ph.D. degrees from the University of Southern California, in 2008 and 2012, respectively. He is an Associate Member of the International Academy for Production Engineering (CIRP), Fellow of the PLuS Alliance, and Senior Fellow of the Higher Education Academy (SFHEA). He chaired multiple international design conferences such as the 13th International Conference on Axiomatic Design (ICAD2019). He serves in the editorial boards of multiple journals such as the Chinese Journal of Mechanical Engineering, Digital Twin, Scientific Reports, etc. He has published over 100 book chapters, journal articles, and conference papers. His research interests include innovative design thinking, design theory and methodology, smart manufacturing, digital twin, and engineering education.
Mr. Yuchen Wang is a Ph.D.candidate in Mechanical Engineering. He completed his undergraduate degree in Aerospace Engineering at the University of New South Wales (UNSW). His research lies at the intersections of design methodology, data science, and digital twin. As a head tutor, he had been teaching engineering design to a large cohort of college student at UNSW. He has published more than 10 journal articles, conference papers, and book chapters.
Mr. Xingzhi Wang is a Ph.D. candidate in Mechanical Engineering at the University of New South Wales (UNSW). He obtained his undergraduate degree and master’s degree at the Sichuan University and UNSW, respectively. His research focuses on leveraging machine learning to enhance design customization.
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This book addresses the emerging paradigm of data-driven engineering design. In the big-data era, data is becoming a strategic asset for global manufacturers. This book shows how the power of data can be leveraged to drive the engineering design process, in particular, the early-stage design.
Based on novel combinations of standing design methodology and the emerging data science, the book presents a collection of theoretically sound and practically viable design frameworks, which are intended to address a variety of critical design activities including conceptual design, complexity management, smart customization, smart product design, product service integration, and so forth. In addition, it includes a number of detailed case studies to showcase the application of data-driven engineering design. The book concludes with a set of promising research questions that warrant further investigation.
Given its scope, the book will appeal to a broad readership, including postgraduate students, researchers, lecturers, and practitioners in the field of engineering design.
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Data-Driven Engineering Design.
Verlag:
Cham, Springer International Publishing., 2022
ISBN 10: 3030881806
ISBN 13: 9783030881801
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1st ed. 2022. IX, 197 p. Hardcover. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch. Artikel-Nr. 13121DB
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Data-Driven Engineering Design
ISBN 10: 3030881806
ISBN 13: 9783030881801
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Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book addresses the emerging paradigm of data-driven engineering design. In the big-data era, data is becoming a strategic asset for global manufacturers. This book shows how the power of data can be leveraged to drive the engineering design process, in particular, the early-stage design.Based on novel combinations of standing design methodology and the emerging data science, the book presents a collection of theoretically sound and practically viable design frameworks, which are intended to address a variety of critical design activities including conceptual design, complexity management, smart customization, smart product design, product service integration, and so forth. In addition, it includes a number of detailed case studies to showcase the application of data-driven engineering design. The book concludes with a set of promising research questions that warrant further investigation.Given its scope, the book will appeal to a broad readership, including postgraduate students, researchers, lecturers, and practitioners in the field of engineering design. Artikel-Nr. 9783030881801
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Data-Driven Engineering Design
ISBN 10: 3030881806
ISBN 13: 9783030881801
Neu
Hardcover
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Buch. Zustand: Neu. Neuware -This book addresses the emerging paradigm of data-driven engineering design. In the big-data era, data is becoming a strategic asset for global manufacturers. This book shows how the power of data can be leveraged to drive the engineering design process, in particular, the early-stage design.Based on novel combinations of standing design methodology and the emerging data science, the book presents a collection of theoretically sound and practically viable design frameworks, which are intended to address a variety of critical design activities including conceptual design, complexity management, smart customization, smart product design, product service integration, and so forth. In addition, it includes a number of detailed case studies to showcase the application of data-driven engineering design. The book concludes with a set of promising research questions that warrant further investigation.Given its scope, the book will appeal to a broad readership, including postgraduate students, researchers, lecturers, and practitioners in the field of engineering design.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 208 pp. Englisch. Artikel-Nr. 9783030881801
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Data-Driven Engineering Design
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