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Sensors 2015, 15(12), 32079-32122; doi:10.3390/s151229905

Cloud-Based Automated Design and Additive Manufacturing: A Usage Data-Enabled Paradigm Shift

1
ISIS Sensorial Materials Scientific Centre, University of Bremen, Bibliothekstraße 1, 28359 Bremen, Germany
2
Industrial and Management Systems Engineering Department, Benjamin M. Statler College of Engineering and Mineral Resources, West Virginia University, 333-A Mineral Resource BLDG, Morgantown, WV 26506, USA
3
BIBA—Bremer Institut für Produktion und Logistik GmbH, Hochschulring 20, Bremen 28359, Germany
4
Faculty of Mathematics & Computer Science, University of Bremen, Robert Hooke Str. 5, 28359 Bremen, Germany
5
Kobe University, Graduate School of Systems Informatics, Department of Systems Sciences, 1-1 Rokkodai, Nada, Kobe 657-8501, Japan
6
Faculty of Production Engineering, University of Bremen, Badgasteiner Straße 1, 28359 Bremen, Germany
7
Fraunhofer Institute for Manufacturing Technology and Advanced Materials, Wiener Straße 12, 28359 Bremen, Germany
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 4 November 2015 / Revised: 9 December 2015 / Accepted: 16 December 2015 / Published: 19 December 2015
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Abstract

Integration of sensors into various kinds of products and machines provides access to in-depth usage information as basis for product optimization. Presently, this large potential for more user-friendly and efficient products is not being realized because (a) sensor integration and thus usage information is not available on a large scale and (b) product optimization requires considerable efforts in terms of manpower and adaptation of production equipment. However, with the advent of cloud-based services and highly flexible additive manufacturing techniques, these obstacles are currently crumbling away at rapid pace. The present study explores the state of the art in gathering and evaluating product usage and life cycle data, additive manufacturing and sensor integration, automated design and cloud-based services in manufacturing. By joining and extrapolating development trends in these areas, it delimits the foundations of a manufacturing concept that will allow continuous and economically viable product optimization on a general, user group or individual user level. This projection is checked against three different application scenarios, each of which stresses different aspects of the underlying holistic concept. The following discussion identifies critical issues and research needs by adopting the relevant stakeholder perspectives. View Full-Text
Keywords: sensor integration; PEID; PLM; additive manufacturing; cloud-based manufacturing; engineering design; product customization; product design; product development; automated design sensor integration; PEID; PLM; additive manufacturing; cloud-based manufacturing; engineering design; product customization; product design; product development; automated design
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Lehmhus, D.; Wuest, T.; Wellsandt, S.; Bosse, S.; Kaihara, T.; Thoben, K.-D.; Busse, M. Cloud-Based Automated Design and Additive Manufacturing: A Usage Data-Enabled Paradigm Shift. Sensors 2015, 15, 32079-32122.

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