Digital Manufacturing and Cloud Manufacturing

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.

Zude Zhou Jerry Fuh Shane Xie Zhongwei Jiang