Closed-loop design evolution of engineering system using condition monitoring through internet of things and cloud computing

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  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 =          "",
  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