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Data-Driven Engineering Design

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Data-Driven Engineering Design
Περιγραφή: 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.
Συγγραφείς: Ang Liu, Yuchen Wang, Xingzhi Wang
Resource Type: eBook.
Θέματα: Engineering design--Data processing
Categories: TECHNOLOGY & ENGINEERING / Industrial Design / General, COMPUTERS / Design, Graphics & Media / CAD-CAM, COMPUTERS / Data Science / General, TECHNOLOGY & ENGINEERING / Engineering (General), TECHNOLOGY & ENGINEERING / Industrial Engineering
Βάση Δεδομένων: eBook Index
FullText Text:
  Availability: 0
Header DbId: edsebk
DbLabel: eBook Index
An: 3058951
RelevancyScore: 962
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 962.24267578125
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  Data: 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.
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RecordInfo BibRecord:
  BibEntity:
    Classifications:
      – Code: 620.00420285
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Engineering design--Data processing
        Type: general
    Titles:
      – TitleFull: Data-Driven Engineering Design
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Ang Liu
      – PersonEntity:
          Name:
            NameFull: Yuchen Wang
      – PersonEntity:
          Name:
            NameFull: Xingzhi Wang
      – PersonEntity:
          Name:
            NameFull: Ang Liu
      – PersonEntity:
          Name:
            NameFull: Yuchen Wang
      – PersonEntity:
          Name:
            NameFull: Xingzhi Wang
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2022
            – D: 11
              M: 10
              Type: profile
              Y: 2021
          Identifiers:
            – Type: isbn-print
              Value: 9783030881801
            – Type: isbn-electronic
              Value: 9783030881818
          Titles:
            – TitleFull: Data-Driven Engineering Design
              Type: main
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