Data-Driven Engineering Design (Hardcover, 1st ed. 2022)

Ang Liu, Yu-Chen Wang, Xingzhi Wang

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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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Release date:	October 2021
First published:	2022
Authors:	Ang Liu • Yu-Chen Wang • Xingzhi Wang
Dimensions:	235 x 155 x 18mm (L x W x T)
Format:	Hardcover
Pages:	197
Edition:	1st ed. 2022
ISBN-13:	978-3-03-088180-1
Categories:	Books > Professional & Technical > Technology: general issues > Technical design > Computer aided design (CAD) Books > Professional & Technical > Mechanical engineering & materials > Production engineering > General Books > Computing & IT > Applications of computing > Databases > General Promotions
LSN:	3-03-088180-6
Barcode:	9783030881801