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Data-Driven Engineering Design. 2022 ed.
・ISBN 978-3-030-88183-2 paper EUR 59.99
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| 著者・編者 | Liu, Ang / Wang, Yuchen / Wang, Xingzhi, |
|---|---|
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2022 |
| ページ数 | 197 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A02-89956＞ |
解説
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.