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
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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)