Data-Driven Engineering Design - Xingzhi Wang,Yuchen Wang,Ang Liu
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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 collec ... Pilns apraksts
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Aprašymas
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.
Vairāk informācijas
| Autors | Xingzhi Wang, Yuchen Wang, Ang Liu |
|---|---|
| Izdevējs | Springer International Publishing |
| Izlaides gads | 2022 |
| Vāka tips | Mīkstais vāks |
| EAN | 9783030881832 |