WEAKNESS IN OPTIMIZATION OF CLOUD MANUFACTURING PROCESS UNDER VARIOUS RESOURCE EXCHANGE STRATEGIES

Abstract

Cloud manufacturing is characterized
by large uncertainties and disturbances due to its
networked, distributed, and loosely coupled
features. To target the problem of frequent cloud
resource node failure, this paper proposes (1) three
resource substitution strategies based on node
redundancy and (2) a new robustness analysis
method for cloud manufacturing systems based
on a combination of the complex network and
multi-agent simulation. First, a multi-agent
simulation model is constructed, and simulation
evaluation indexes are designed to study the
robustness of the dynamic cloud manufacturing
process (CMP). Second, a complex network model
of cloud manufacturing resources is established to
analyze the static topological robustness of the
cloud manufacturing network. Four types of node
failure modes are defined, based on the initial and
recomputed topologies. Further, three resource
substitution strategies are proposed (i.e., internal
replacement, external replacement, and internal–
external integration replacement) to enable the
normal operation of the system after resource
node failure. Third, a case study is conducted
for a cloud manufacturing project of a new energy
vehicle. The results show that (1) the proposed
robustness of service index is effective at
describing the variations in CMP robustness, (2) the
two node failure modes based on the recalculated
topology are more destructive to the robustness
of the CMP than the two based on the initial
topology, and (3) under all four failure modes, all
three resource substitution strategies can improve
the robustness of the dynamic CMP to some extent,
with the internal–external integration replacement
strategy being most effective, followed by the
external replacement strategy, and then the internal
replacement strategy.