The cloud manufacturing (C-Manufacturing) paradigm, as an advanced form of networked manufacturing, has recently been proposed based on a combination of existing manufacturing systems and emerging technologies, such as cloud computing, virtual manufacturing, agile manufacturing, manufacturing grid, Internet-of-things (IOT), and service-oriented technologies. In this study, through investigating the main goals of C-Manufacturing and today's hypercompetitive global marketplace circumstances, a prospective conceptual model called cloud-based global supply chain (CBGSC) has been developed which can overcome or mitigate the issues and risks associated with supply chain processes on a global scale. CBGSC extends the conventional three-tier customer–manufacturer–supplier supply chain model into a new five-tier customer–cloud provider of manufacturing applications (CPMA)–manufacturer–cloud provider of supplying applications (CPSA)–supplier model, in which the CPMA and CPSA tiers act as intermediators in order to enhance the diversity and intensity of the markets and businesses of conventional supply chain parties while securing their own profits. On the other hand, CBGSC enriches the notion of C-Manufacturing by incorporating CPSAs to safeguard smooth and continuous supply of raw materials and goods to manufacturers (physical resource providers), thus prevailing the “share to gain” philosophy within the whole network. Also, aiming to facilitate practicalizing the CBGSC, we have proposed a multilayer architecture for the CBGSC with seven layers of user, interface, application, service, resource virtualization and service encapsulation, perception, and resource, which are blended together via four basic aspects of security, optimality, resilience, and information technology (IT) and information and communications technology (ICT) infrastructure.

References

References
1.
Xiao
,
Y. Y. E.
,
2006
, “
The Integration of International Supply Chain Management and E-Business
,” Ph.D. dissertation, Massachusetts Institute of Technology, Cambridge, MA.
2.
Abdelkafi
,
N.
,
Pero
,
M.
,
Blecker
,
T.
, and
Sianesi
,
S.
,
2011
, “
NPDSCM Alignment in Mass Customization
,”
Mass Customization Engineering and Managing Global Operations
,
F. S.
Fogliatto
and
G. J. C.
da Silveira
, eds.,
Springer-Verlag
,
London, UK
, pp.
69
85
.
3.
van Hoek
,
R. I.
,
1998
, “
Reconfiguring the Supply Chain to Implement Postponement Manufacturing
,”
Int. J. Logist. Manage.
,
9
(
1
), pp.
95
110
.10.1108/09574099810805771
4.
Vidal
,
C. J.
, and
Goetschackx
,
M.
,
2000
, “
Modelling the Effect of Uncertainties on Global Logistics Systems
,”
J. Bus. Logist.
,
21
(
1
), pp.
95
120
.
5.
Salvador
,
F.
,
Rungtusanatham
,
M.
, and
Forza
,
C.
,
2004
, “
Supply Chain Configurations for Mass Customization
,”
Prod. Plann. Control
,
15
(
4
), pp.
381
397
.10.1080/0953728042000238818
6.
Souza
,
G. C.
,
Zhao
,
Z.
, and
Chen
,
M.
,
2004
, “
Coordinating Sales and Raw Material Discounts in a Global Supply Chain
,”
Prod. Oper. Manage.
,
13
(
1
), pp.
34
45
.10.1111/j.1937-5956.2004.tb00143.x
7.
Tyagi
,
R.
,
Kalish
,
P.
,
Akbay
,
K.
, and
Munshaw
,
G.
,
2004
, “
GE Plastics Optimizes the Two-Echelon Global Fulfillment Network at Its High Performance Polymers Division
,”
Interfaces
,
34
(
5
), pp.
359
366
.10.1287/inte.1040.0088
8.
Nembhard
,
H. B.
,
Shi
,
L.
, and
Aktan
,
M.
,
2005
, “
The Effect of Implementation Time Lag on Real Options Valuation
,”
IIE Trans.
,
37
(
10
), pp.
945
956
.10.1080/07408170591008073
9.
Goh
,
M.
,
Lim
,
J.
, and
Meng
,
F.
,
2007
, “
A Stochastic Model for Risk Management in Global Supply Chain Networks
,”
Eur. J. Oper. Res.
,
182
(
1
), pp.
164
173
.10.1016/j.ejor.2006.08.028
10.
Creazza
,
A.
,
Dallari
,
F.
, and
Melacini
,
M.
,
2010
, “
Evaluating Logistics Network Configurations for a Global Supply Chain
,”
Supply Chain Manage.: Int. J.
,
15
(
2
), pp.
154
164
.10.1108/13598541011028750
11.
Singh
,
A. R.
,
Mishra
,
P. K.
,
Jain
,
R.
, and
Khurana
,
M. K.
,
2012
, “
Design of Global Supply Chain Network With Operational Risks
,”
Int. J. Adv. Manuf. Technol.
,
60
(
1
), pp.
273
290
.10.1007/s00170-011-3615-9
12.
Cruz
,
J. M.
,
2013
, “
Mitigating Global Supply Chain Risks Through Corporate Social Responsibility
,”
Int. J. Prod. Res.
,
51
(
3
), pp.
3995
4010
.10.1080/00207543.2012.762134
13.
Li
,
B. H.
,
Zhang
,
L.
,
Wang
,
S.
,
Tao
,
F.
,
Cao
,
J.
,
Jiang
,
X.
,
Song
,
X.
, and
Chai
,
X.
,
2010
, “
Cloud Manufacturing: A New Service-Oriented Networked Manufacturing Model
,”
Comput. Integr. Manuf. Syst.
,
16
(
1
), pp.
1
7
.
14.
Xu
,
X.
,
2012
, “
From Cloud Computing to Cloud Manufacturing
,”
Rob. Comput. Integr. Manuf.
,
28
(
1
), pp.
75
86
.10.1016/j.rcim.2011.07.002
15.
Zhang
,
L.
,
Luo
,
Y.
,
Tao
,
F.
,
Li
,
B.-H.
,
Ren
,
L.
,
Zhang
,
X.
,
Guo
,
H.
,
Cheng
,
Y.
,
Hu
,
A.
, and
Liu
,
Y.
,
2014
, “
Cloud Manufacturing: A New Manufacturing Paradigm
,”
Enterp. Inf. Syst.
,
8
(
2
), pp.
167
187
.10.1080/17517575.2012.683812
16.
Wu
,
D.
,
Greer
,
M. J.
,
Rosen
,
D. W.
, and
Schaefer
,
D.
,
2013
, “
Cloud Manufacturing: Strategic Vision and State-of-the-Art
,”
J. Manuf. Syst.
,
32
(
4
), pp.
564
579
.10.1016/j.jmsy.2013.04.008
17.
Tao
,
F.
,
Zhang
,
L.
,
Venkatesh
,
V. C.
,
Luo
,
Y.
, and
Cheng
,
Y.
,
2011
, “
Cloud Manufacturing: A Computing and Service-Oriented Manufacturing Model
,”
Proc. Inst. Mech. Eng., Part B
,
225
(
10
), pp.
1969
1976
.10.1177/0954405411405575
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