Data-Driven Engineering Design - 9783030881832

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.

• | Author: Ang Liu, Yuchen Wang, Xingzhi Wang
• | Publisher: Springer
• | Publication Date: Oct 10, 2022
• | Number of Pages: 208 pages
• | Language: English
• | Binding: Paperback
• | ISBN-10: 3030881830
• | ISBN-13: 9783030881832