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| 001 | 395405 | ||
| 003 | ES-MaUEC | ||
| 005 | 20230301132559.0 | ||
| 006 | a||||fo|||| 00| 0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 211009s2022 sz | s |||| 0|eng d | ||
| 020 | _a9783030881818 | ||
| 024 | 7 |
_a10.1007/978-3-030-88181-8 _2doi |
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| 040 |
_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC |
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| 050 | 4 |
_aTA174 _b2022 EB |
|
| 100 | 1 |
_aLiu, Ang _eautor _9687131 |
|
| 245 | 1 | 0 |
_aData-Driven Engineering Design _cby Ang Liu, Yuchen Wang, Xingzhi Wang |
| 250 | _a1st edition 2022 | ||
| 264 | 1 |
_aCham _bSpringer International Publishing _c2022 |
|
| 300 |
_a1 recurso en línea (IX, 197 páginas) _b55 ilustraciones, 51 ilustraciones a color |
||
| 336 |
_atexto _btxt _2rdacontent |
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| 337 |
_aelectrónico _bc _2rdamedia |
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| 338 |
_arecurso electrónico _bcr _2rdacarrier |
||
| 347 |
_aarchivo de texto _bPDF |
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| 505 | 0 | _aData-driven Engineering Design -- User-Generated Content Analysis for Customer Needs Elicitation -- Data-driven Conceptual Design -- Management of Constraints, Complexities, and Contradictions in the Data Era -- Blockchain-based Data-driven Smart Customisation -- Data-driven Design of Smart Product -- Data-driven Smart Product Service System -- Digital Twin for Data-driven Engineering Design -- Enabling Technologies of Data-driven Engineering Design. | |
| 520 | _aThis 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. | ||
| 988 | _aSpringer_Engineering_2022 | ||
| 700 | 1 |
_9687132 _aWang, Yuchen _d1967- _eautor |
|
| 776 | 0 | 8 |
_iPrinted edition: _z9783030881801 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030881825 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030881832 |
| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi-org.ezproxy.universidadeuropea.es/10.1007/978-3-030-88181-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
| 942 |
_2lcc _cLE |
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| 998 |
_b03/2023 _dz _eu _zSI |
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