Closed-loop design evolution of engineering system using condition monitoring through internet of things and cloud computing
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @Article{Xia:2016:CN,
-
author = "Min Xia and Teng Li and Yunfei Zhang and
Clarence W. {de Silva}",
-
title = "Closed-loop design evolution of engineering system
using condition monitoring through internet of things
and cloud computing",
-
journal = "Computer Networks",
-
volume = "101",
-
pages = "5--18",
-
year = "2016",
-
note = "Industrial Technologies and Applications for the
Internet of Things",
-
ISSN = "1389-1286",
-
DOI = "doi:10.1016/j.comnet.2015.12.016",
-
URL = "http://www.sciencedirect.com/science/article/pii/S1389128615005034",
-
abstract = "Flexibility of a manufacturing system is quite
important and advantageous in modern industry, which
function in a competitive environment where market
diversity and the need for customized product are
growing. Key machinery in a manufacturing system should
be reliable, flexible, intelligent, less complex, and
cost effective. To achieve these goals, the design
methodologies for engineering systems should be
revisited and improved. In particular, continuous or
on-demand design improvements have to be incorporated
rapidly and effectively in order to address new design
requirements or resolve potential weaknesses of the
original design. Design of an engineering system, which
is typically a multi-domain system, can become
complicated due to its complex structure and possible
dynamic coupling between domains. An integrated and
concurrent approach should be considered in the design
process, in particular in the conceptual and detailed
design phases. In the context of multi-domain design,
attention has been given recently to such subjects as
multi-criteria decision making, multi-domain modelling,
evolutionary computing, and genetic programing. More
recently, machine condition monitoring has been
considered for integration into a scheme of design
evolution even though many challenges exist for this to
become a reality such as lack of systematic approaches
and the existence of technical barriers in massive
condition data acquisition, transmission, storage and
mining. Recently, the internet of things (IoT) and
cloud computing (CC) are being developed quickly and
they offer new opportunities for evolutionary design
for such tasks as data acquisition, storage and
processing. In this paper, a framework for the
closed-loop design evolution of engineering systems is
proposed in order to achieve continuous design
improvement for an engineering system through the use
of a machine condition monitoring system assisted by
IoT and CC. New design requirements or the detection of
design weaknesses of an existing engineering system can
be addressed through the proposed framework. A design
knowledge base that is constructed by integrating
design expertise from domain experts, on-line process
information from condition monitoring and other design
information from various sources is proposed to realize
and supervise the design process so as to achieve
increased efficiency, design speed, and effectiveness.
The framework developed in this paper is illustrated by
using a case study of design evolution of an industrial
manufacturing system.",
-
keywords = "genetic algorithms, genetic programming, Engineering
system design, Design evolution, Multi-domain
modelling, Machine condition monitoring, Internet of
things, Cloud computing",
- }
Genetic Programming entries for
Min Xia
Teng Li
Yunfei Zhang
Clarence W de Silva
Citations