| 書目名稱 | Data-Driven Engineering Design | | 編輯 | Ang Liu,Yuchen Wang,Xingzhi Wang | | 視頻video | http://file.papertrans.cn/264/263292/263292.mp4 | | 概述 | Combines current design methodologies with emerging data science.Showcases a range of validated data-driven design frameworks.Presents alternative approaches to early-stage design | | 圖書封面 |  | | 描述 | .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.. | | 出版日期 | Book 2022 | | 關(guān)鍵詞 | Engineering Design; Data-Driven Design; Data Science; Product Development; Design Methodology; Product Se | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-88181-8 | | isbn_softcover | 978-3-030-88183-2 | | isbn_ebook | 978-3-030-88181-8 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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