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Data-Driven Digital Twin Requirements for Additive Layer Manufacturing

Authors :
Shehab Essam
Jumassultan Assel
Khoyashov Nurgabyl
Juziyeva Shynar
Jyeniskhan Nursultan
Ali Md Hazrat
Source :
MATEC Web of Conferences, Vol 401, p 02012 (2024)
Publication Year :
2024
Publisher :
EDP Sciences, 2024.

Abstract

Digital twin and additive layer manufacturing plays a vital role of the fourth industrial revolution. Digital twin is the ideal solution for data-driven optimisation of additive manufacturing challenges. It is helpful in understating, analysing, and improving 3D printing machining process variables and consequently reducing the number of trial-and-error and component’s non-conformance and shorten product development lead time. Furthermore, the development of genuine digital twin still requires more research efforts to develop a thorough understanding of its concept, data management framework, and development techniques. Therefore, this paper aims to capture important data-driven digital twin requirements for additive layer manufacturing through a systematic approach by identifying the requirements, analysing technologies and processes for digital twin development. The main novelty of this research is applying a holistic approach to build digital twin of additive manufacturing process by capturing the requirements from both literature review and world-class aerospace industrial experts. Overall, the captured requirements will not only serve industries as a basis for implementing digital twin for additive manufacturing and modernize existing data management systems but also opens new research areas in the digital twin domain.

Details

Language :
English, French
ISSN :
2261236X and 20244010
Volume :
401
Database :
Directory of Open Access Journals
Journal :
MATEC Web of Conferences
Publication Type :
Academic Journal
Accession number :
edsdoj.58aa1d19a0db415fb36ec7532262cb9a
Document Type :
article
Full Text :
https://doi.org/10.1051/matecconf/202440102012