A methodology for information modelling and analysis of manufacturing processes for digital twins

Shuo Su*, Aydin Nassehi, Qunfen Qi, Ben J Hicks

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

6 Citations (Scopus)

Abstract

This paper introduces a methodology for information modelling and analysis of physical manufacturing processes for digital twins (DTs). It aims to establish a comprehensive and fundamental understanding of manufacturing processes regarding the specific purpose of the DT. Through this methodology, information entities within the manufacturing process that can be represented in DTs, along with their essential attributes, are systematically identified. To achieve this, an information model is firstly proposed to define such entities, termed as representative information. The attributes and hierarchy of entities are formulated based on a requirements analysis of the DT lifecycle. An Integration Definition for Process Modelling 0 (IDEF0) model, Petri nets, and a literature-based identification process are applied to represent the manufacturing process’s workflow and identify information entities. Moreover, the relative importance of representing each information entity in a DT is evaluated by integrating domain-specific knowledge with the specific purpose of the DT. Three types of information analysis are suggested, each with its corresponding methods: empirical analysis, theoretical analysis, and experimental analysis. Specifically, this study explores the material extrusion (MEX) process of the Prusa i3 MK3 printer, resulting in an information model consisting of 128 entities including 21 components, 25 activities and 82 properties. These information entities and associated attributes provide a reference for selecting and synchronizing specific physical information in a DT for estimating dimensional accuracy during the MEX process.
Original languageEnglish
Article number102813
Number of pages20
JournalRobotics and Computer-Integrated Manufacturing
Volume90
Early online date6 Jul 2024
DOIs
Publication statusPublished - 1 Dec 2024

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© 2024 The Author(s)

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