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Ontology-Driven Guidelines for Architecting Digital Twins in Factory Automation Applications

Authors :
Wael M. Mohammed
Rodolfo E. Haber
Jose L. Martinez Lastra
Source :
Machines, Vol 10, Iss 10, p 861 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

The rapid emerging technologies in various fields permitted the creation of simulation tools. These tools are designed to replicate physical systems in order to provide faster, cheaper and more detailed illustrative analysis of the physical system. In this regard, the concept of digital twins has been introduced to generally define these simulation tools. In fact, and according to the creator of the digital twin term Micheal Grieves, a digital twin is defined as a physical system, a digital replica of the physical system and information flow between the former parts. This definition is simple and generic for describing digital twins and yet, holistic. This broad definition creates a challenge for developers who target the development of such applications. Therefore, this paper presents a paradigm for architecting digital twins for manufacturing processes. The approach is inspired by the definitions of the ISA95 standard and the onion concept of computer applications to create multi-layer and multi-level concepts. Furthermore, and to satisfy the different required features by industries, the approach considers a multi-perspective concept that allows the separation of the digital twin views based on functionality. This paradigm aims at providing a modular, scalable, reusable, interoperable and composable approach for developing digital twins. Then, an implementation of the approach has been introduced using an ontology-based system and the IEC61499 standard. This implementation has been demonstrated on a discrete manufacturing assembly line.

Details

Language :
English
ISSN :
20751702
Volume :
10
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Machines
Publication Type :
Academic Journal
Accession number :
edsdoj.3210594861344b7afd29af73a775af1
Document Type :
article
Full Text :
https://doi.org/10.3390/machines10100861