Modelling for agile manufacturing systems

Tung Sun Chan, Jie Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

22 Citations (Scopus)

Abstract

To address the challenges of a rapidly changing manufacturing market, a new type of manufacturing system with characteristics of reconfigurability, reusability and scalability, an agile manufacturing system (AMS) has to be developed. Reconfigurability is an essential feature of AMS. Such a system can use basic building blocks, both hardware and software, which can be reconfigured quickly and reliably. A fundamental early step in the reconfiguring process for an agile manufacturing system is to develop a model that adequately describes the proposed system, in order to be able to study and evaluate the impact of the reconfiguring decision on the system performance, before its construction. Therefore, the rapid modelling and reusable modelling capabilities are demanded. In this paper, an Object & Knowledge-based Interval Timed Petri-Net (OKITPN) approach is proposed, which provides an object-oriented and modular method of modelling manufacturing activities. It includes knowledge, interval time, modular and communication attributes. The features of object-oriented modelling allow the AMS to be modelled with the properties of classes and objects, and make the concept of software IC possible for rapid modelling of complex AMSs. Once all of the Interval Timed Petri-Net (ITPN) objects are well defined the developers need to consider only the interfaces and operations relating to the ITPN objects. In order to demonstrate the capability of the proposed OKITPN, it has been used to model rapidly AMSs that are reconfigured according to requirements.
Original languageEnglish
Pages (from-to)2313-2332
Number of pages20
JournalInternational Journal of Production Research
Volume39
Issue number11
DOIs
Publication statusPublished - 1 Jan 2001
Externally publishedYes

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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