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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.
Autorius: | Ang Liu, Xingzhi Wang, Yuchen Wang, |
Leidėjas: | Springer International Publishing |
Išleidimo metai: | 2021 |
Knygos puslapių skaičius: | 208 |
ISBN-10: | 3030881806 |
ISBN-13: | 9783030881801 |
Formatas: | 241 x 160 x 17 mm. Knyga kietu viršeliu |
Kalba: | Anglų |
Parašykite atsiliepimą apie „Data-Driven Engineering Design“