Data-Driven Engineering Design

di Ang Liu (Autore)

Yuchen Wang (Autore)

Xingzhi Wang (Autore)

Springer Nature Switzerland AG, 2022

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.

• Autore: Ang Liu, Yuchen Wang, Xingzhi Wang
• Editore: Springer Nature Switzerland AG
• Anno: 2022
• Rilegatura: Paperback / softback
• Pagine: 197 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783030881832

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