Cloud intelligence in manufacturing

Journal of Intelligent Manufacturing, Jul 2015

Tin-Chih Toly Chen

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Cloud intelligence in manufacturing

J Intell Manuf Cloud intelligence in manufacturing Tin-Chih Toly Chen 0 0 Department of Industrial Engineering and Systems Management, Feng Chia University , 100, Wenhwa Road, Seatwen, Taichung City 407 , Taiwan - Cloud manufacturing (CMfg) is a new-generation, centrally-managed, service-oriented networked manufacturing model that can provide manufacturing resources and services to users in different locations (Wu et al. 2013b; Archimede et al. 2014) . Cloud computing enthusiasts have advocated CMfg as a direct extension of cloud computing in the manufacturing sector, but the full application of cloud computing to manufacturing is a problem (Chen 2014) . There are also many differences between information services and manufacturing services (Fan et al. 2004). Nevertheless, from the existing reports and case studies, the benefits of CMfg appear to include: cost savings, efficiency, additional data analysis capabilities, flexibility, and closer partner relationships (Chen 2014) . While CMfg may be suitable for small or mid-sized enterprises, most capital-intensive businesses directly buy all necessary systems and equipment (Chen 2014) , which makes some of the cost-saving incentives insignificant. Many manufacturing operations managers have hesitated to migrate systems to clouds (Davidson 2013) . Although some researchers have asserted that CMfg is a new paradigm that will revolutionize manufacturing (Wu et al. 2014) , most existing CMfg technologies center on information technology, rather than manufacturing technology (Chen 2014) . To tackle these problems, manufacturers need manufacturing-oriented CMfg, supplemented by information technology. In the opinion of Wu et al. (2013a), research fields critical to the enablement of CMfg include automation, industrial control systems, service composition, flexibility, business models, implementation models, and architectures. In addition, two important concepts in cloud computing interoperability and scalability - if successfully applied to CMfg, can enable flexible responses to orders and flexible adjustments of factory capacity (Newman et al. 2008; Panetto and Molina 2008; Chen 2014; Galasso et al. 2014) . The mainstream research on CMfg has been focused on topics like cyber-physical systems (CPSs) (Colombo et al. 2013) , resource virtualization and visualization (Chen and Romanowski 2014; Huang et al. 2015) , cloud-based manufacturing services (Wang and Xu 2013) , distant monitoring and control, and others. Entirely new directions for CMfg, including Industry 4.0 (Federal Ministry of Education and Research 2013), are yet to be developed. The objective of this special issue is intended to provide the details of developing manufacturing-oriented CMfg intelligence and its applications for researchers in process engineering, industrial engineering, information engineering, and operations research, as well as practicing managers/engineers. This special issue features a balance between state-of-the-art research and usually reported applications. This special issue also provides a forum for researchers and practitioners to review and disseminate quality research work on manufacturing-oriented CMfg intelligence and its applications, and to identify critical issues for further developments. After a strict review, eleven articles from researchers around the world were finally accepted. Since 1960s, with the development of societal and related technologies, many advanced manufacturing systems (AMSs) and modes have been put forward. F. Tao, Y. Cheng, L. Zhang, and A. Y. C. Nee overviewed the development process of AMSs, and established a tri-view model to analyze the evolution and socialization characteristics of AMSs. It is found that the sharing of manufacturing resources and capabilities, the value creation carriers, the value measuring criteria, the composition of the value chain and enterprise collaboration, and user participation in manufacturing are all moving towards socialization. Factory operations have shifted from labor-based to semi-automatic and fully automatic and may even become unmanned in the future. Therefore, the conditions of a factory can be monitored from a distance and the machines can be remotely controlled. T. Chen, Y.-C. Wang, and Z. Lin investigated the predictive distant operation of a computer numerical control (CNC) machine virtually controlled with hand gestures. The attempt in their study is a crucial step toward entirely Internet- or cloud-based manufacturing. Y. Zhang, G. Zhang, Y. Liu, and D. Hu presented a service encapsulation and virtualization access model for manufacturing machines by combining the IoT (Internet of Things) techniques and cloud computing. By implementing the proposed service encapsulation and virtualization access model, the capability of a machine could be actively perceived, the production process is transparent and can be timely visited, and the virtualized machine could be accessed t (...truncated)


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Tin-Chih Toly Chen. Cloud intelligence in manufacturing, Journal of Intelligent Manufacturing, 2017, pp. 1057-1059, Volume 28, Issue 5, DOI: 10.1007/s10845-015-1122-9