Digital twin-based designing of the configuration, motion, control, and optimization model of a flow-type smart manufacturing system

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

  • Ailin Yu
  • Rongli Zhao
  • Hao Zhang
  • Xin Chen

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)52-64
Journal / PublicationJournal of Manufacturing Systems
Volume58
Issue numberPt.B
Online published28 Apr 2020
Publication statusPublished - Jan 2021

Abstract

Digital twins can achieve hardware-in-the-loop simulation of both physical equipment and cyber model, which could be used to avoid the considerable cost of manufacturing system reconfiguration if the design deficiencies are found in the deployment process of the traditional irreversible design approach. Based on the digital twin technology, a quad-play CMCO (i.e., Configuration design-Motion planning-Control development-Optimization decoupling) design architecture is put forward for the design of the flow-type smart manufacturing system in the Industry 4.0 context. The iteration logic of the CMCO design model is expounded. Two key enabling technologies for enabling the customized and software-defined design of flow-type smart manufacturing systems are presented, including the generalized encapsulation of the quad-play CMCO model and the digital twin technique. A prototype of a digital twin-based manufacturing system design platform, named Digital Twin System, is presented based on the CMCO model. The digital twin-based design platform is verified with a case study of the hollow glass smart manufacturing system. The result shows that the Digital Twin System-based design approach is feasible and efficient.

Research Area(s)

  • Cyber-physical systems, Digital twin, Industry 4.0, Manufacturing system design, Smart manufacturing

Citation Format(s)

Digital twin-based designing of the configuration, motion, control, and optimization model of a flow-type smart manufacturing system. / Liu, Qiang; Leng, Jiewu; Yan, Douxi et al.

In: Journal of Manufacturing Systems, Vol. 58, No. Pt.B, 01.2021, p. 52-64.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review