Hindawi Publishing Corporation Advances in Mechanical Engineering Volume 2013, Article ID 560691, 2 pages http://dx.doi.org/10.1155/2013/560691
Editorial Digital Manufacturing and Cloud Manufacturing Zude Zhou,1 Jerry Fuh,2 Shane Xie,3 and Zhongwei Jiang4 1
School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117576 3 Department of Mechanical Engineering, The University of Auckland, Private Bag 92019, Auckland, New Zealand 4 Department of Mechanical Engineering, Yamaguchi University, Yamaguchi, Ube 755-8611, Japan 2
Correspondence should be addressed to Zude Zhou;
[email protected] Received 10 October 2013; Accepted 10 October 2013 Copyright © 2013 Zude Zhou et al. 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.
The fierce global competition and rapid technology development faced by manufacturing industry have been forcing enterprises to evolve at an unprecedented rate [1, 2]. In order to survive and succeed in such a turbulent and dynamic environment, enterprises are striving to improve their competencies to meet the requirements for rapid response to different market opportunities including massive customization of products, high product quality, low product cost, and rapid response services. Moreover, the sustainable concerns, not only on economy, but also on environment and society, also force enterprises to examine their strategies in the full lifecycle of the products/services and to engage in a new competitive climate. Digital Manufacturing [3–5] is originated from the numerical control technology and based on the concept of “digital earth”. It enables the production in a digital space and focuses on the digitized technologies, such as digital modeling, digital machining, digital resource, digital service, and digital maintenance, for supporting the overall manufacturing performance optimisation during the whole product lifecycle. Cloud manufacturing [6–8] is originated from the cloud computing technology and based on the concept of “smart earth.” It is the developing trend of Digital Manufacturing. Besides the aforementioned digital characteristics, Cloud Manufacturing mainly focuses on offering secure, reliable, high-quality, low-cost, and on-demand services during production process. The manufacturing resources and capabilities are virtualized into service provision and being traded on a “pay-per-use” basis, which lead to a more competitive market by the sustainable incentives.
This special issue aims to collect basic theory, key technology, and application articles on the most recent achievements in such field, for the purpose to show the latest development and provide guidelines of future research directions. Z. Wei et al. present a cloud model sharing platform based on separated data log for cloud manufacturing. Y. Wang and T. Chen develop a fuzzy collaborative forecasting approach for forecasting the productivity of a factory. Q. Ai et al. propose an intelligent method of product scheme design based on product gene. Q. Liu et al. investigate the fault diagnosis of rolling bearing based on wavelet package transform and ensemble empirical mode decomposition. H. Su et al. present an adaptive approach for boundary effects reduction in rotating machine signals analysis. X. Wang and Y. Chen study the numerical analysis of the frictional characteristics of a magnetic suspended flying vehicle. G. Zhang and Y. Liu investigate the positional error analysis of PCB Rogowski coil for high accuracy current measurement. J. Zhang et al. study the dynamic characteristics of a steel/CFRP drive shaft. J. Huang et al. develop a fiber Bragg grating pressure sensor to pipeline leakage detection, and a fiber Bragg grating tension sensor for anchor rope is also presented by J. Huang et al. Z. Li et al. develop a high-speed FBG demodulation system for distributed dynamic monitoring of mechanical equipment. Z. Zhou et al. study the practical velocity tracking control of a parallel robot based on fuzzy adaptive algorithm. J. Li et al. present a virtual reality method of portal slewing crane based on WPF. We hope that this special issue will serve our readers to gain an overall perspective on Digital Manufacturing and Cloud Manufacturing.
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Advances in Mechanical Engineering
Acknowledgments We are grateful to the authors and the many individual reviewers for their contributions to this special issue. Zude Zhou Jerry Fuh Shane Xie Zhongwei Jiang
References [1] National Research Council, Visionary Manufacturing Challenges for 2020, National Academic Press, Washington, DC, USA, 1998. [2] A. J. Thomas, “Creating sustainable small to medium enterprises through technological innovation,” Proceedings of the Institution of Mechanical Engineers B, vol. 221, no. 3, pp. 513–528, 2007. [3] Z. Zhou, W. Yu, and Y. Chen, “Concept and related scientific problems of digital manufacturing,” China Mechnical Engineering, vol. 12, pp. 100–104, 2001. [4] Z. Zhou and G. Li, “On state and development of digital manufacturing,” China Mechnical Engineering, vol. 13, pp. 531– 533, 2002. [5] Z. Zhou, S. Xie, and D. Chen, Fundamentals of Digital Manufacturing Science, Springer, 2012. [6] B.-H. Li, L. Zhang, S.-L. Wang et al., “Cloud manufacturing: a new service-oriented networked manufacturing model,” Computer Integrated Manufacturing Systems, vol. 16, no. 1, pp. 1–16, 2010. [7] B.-H. Li, L. Zhang, L. Ren et al., “Further discussion on cloud manufacturing,” Computer Integrated Manufacturing Systems, vol. 17, no. 3, pp. 449–457, 2011. [8] L. Zhang, Y. Luo, F. Tao et al., “Cloud manufacturing: a new manufacturing paradigm,” Enterprise Information Systems, pp. 1–21, 2012.
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