INVESTIGATION OF DEVELOPING DIGITAL TWIN FOR ADDITIVE MANUFACTURING
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Date
2023
Authors
Jyeniskhan, Nursultan
Journal Title
Journal ISSN
Volume Title
Publisher
School of Engineering and Digital Sciences
Abstract
Additive manufacturing and digital twin concept are both important pillar technologies for fourth
industrial revolution. The additive manufacturing method is being appealing by many highperformance
industries owing to its ability to produce geometrically challenging parts with
traditional manufacturing method. However, there are issues such as final product defects and
requirement of human interventions and monitoring during printing processes to avoid time,
material, and cost waste with additive manufacturing area.
The main aim of this research is to investigate the developments of digital twin technology for
additive manufacturing specifically in fused deposition modeling 3D printers. The main objectives
are to develop digital twin architecture and creating digital twin model for FDM printers. Digital
twin is virtual model or digital representation of a physical entity, process, or component. Due to
the challenges in additive manufacturing field, digital twin technology is considered as one of the
possible solutions to fully digitize additive manufacturing processes and solve additive
manufacturing problems such as real-time monitoring and controlling, predicting the faults and
errors of printers and parts to avoid further waste on time and material, and increase manufacturing
efficiency. After developing digital twin framework and architecture to implement, digital twin
development is conducted. The main approach used to fulfill this research is to use Raspberry Pi
3B+ to connect FDM printer to OctoPrint, open-source software, to remotely control and monitor.
In addition to this, extracting important data from OctoPrint and use them in modeling digital twin
of FDM printer and its processes. The developed digital twin for the FDM printer meets its
functional requirements such as bidirectional communication between physical and digital models,
real-time remotely control and monitoring, and integration of machine learning for leveraging
FDM printers to smart manufacturing.
The main key contributions of this study to knowledges are identification of benefits of digital
twin implementation in different level, and implementation challenges. The development of the
digital twin framework and architectural design are another important key contribution in addition
to novel digital twin model of FDM printer with integration of some intelligence level.
Description
Keywords
Type of access: Embargo, Additive manufacturing, 3D printing, digital twin, digitalization, real-time monitoring, error prediction, machine learning, digital manufacturing
Citation
Jyeniskhan, N. (2023). Investigation of developing digital twin for additive manufacturing. School of Engineering and Digital Sciences