Toggle Main Menu Toggle Search

Open Access padlockePrints

Early-stage analysis of cyber-physical production systems through collaborative modelling

Lookup NU author(s): Dr Ken Pierce

Downloads


Licence

This is the authors' accepted manuscript of an article that has been published in its final definitive form by Springer Nature, 2020.

For re-use rights please refer to the publisher's terms and conditions.


Abstract

This paper demonstrates the flexible methodology of modelling cyber-physical systems (CPSs) using the INTO-CPS technology through co-simulation based on Functional Mock-up Units (FMUs). It explores a novel method with two main co-simulation phases: homogeneous and heterogeneous. In the first phase, high-level, abstract FMUs are produced for all subsystems using a single discrete-event formalism (the VDM-RT language and Overture tool). This approach permits early co-simulation of system-level behaviours and serves as a basis for dialogue between subsystem teams and agreement on interfaces. During the second phase, model refinements of subsystems are gradually introduced, using various simulation tools capable of exporting FMUs. This heterogeneous phase permits high-fidelity models of all subsystems to be produced in appropriate formalisms. This paper describes the use of this methodology to develop a USB stick production line, representing a smart system of systems. The experiments are performed under the assumption that the orders are received in a Gaussian or Uniform distribution. The focus is on the homogeneous co-simulation phase, for which the method demonstrates two important roles: first, the homogeneous phase identifies the right interaction protocols (signals) among the various subsystems, and second, the conceptual (system-level) parameters identified before the heterogeneous co-simulation phase reduce the huge size of the design space and create stable constraints, later reflected in the physical implementation.


Publication metadata

Author(s): Neghina M, Zamfirescu C-B, Pierce K

Publication type: Article

Publication status: Published

Journal: Software and Systems Modeling

Year: 2020

Volume: 19

Pages: 581-600

Print publication date: 01/05/2020

Online publication date: 20/09/2019

Acceptance date: 22/08/2019

Date deposited: 23/09/2019

ISSN (print): 1619-1366

ISSN (electronic): 1619-1374

Publisher: Springer Nature

URL: https://doi.org/10.1007/s10270-019-00753-w

DOI: 10.1007/s10270-019-00753-w


Altmetrics

Altmetrics provided by Altmetric


Share