INVESTIGATION OF DEVELOPING DIGITAL TWIN FOR ADDITIVE MANUFACTURING

dc.contributor.authorJyeniskhan, Nursultan
dc.date.accessioned2023-05-27T08:22:27Z
dc.date.available2023-05-27T08:22:27Z
dc.date.issued2023
dc.description.abstractAdditive 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.en_US
dc.identifier.citationJyeniskhan, N. (2023). Investigation of developing digital twin for additive manufacturing. School of Engineering and Digital Sciencesen_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/7119
dc.language.isoenen_US
dc.publisherSchool of Engineering and Digital Sciencesen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectType of access: Embargoen_US
dc.subjectAdditive manufacturingen_US
dc.subject3D printingen_US
dc.subjectdigital twinen_US
dc.subjectdigitalizationen_US
dc.subjectreal-time monitoringen_US
dc.subjecterror predictionen_US
dc.subjectmachine learningen_US
dc.subjectdigital manufacturingen_US
dc.titleINVESTIGATION OF DEVELOPING DIGITAL TWIN FOR ADDITIVE MANUFACTURINGen_US
dc.typeMaster's thesisen_US
workflow.import.sourcescience

Files

Original bundle
Now showing 1 - 2 of 2
No Thumbnail Available
Name:
1249_Nursultan_Jyeniskhan_Final_Softcopy_of_MS_Thesis_260527_1800730686.pdf
Size:
4.27 MB
Format:
Adobe Portable Document Format
Description:
thesis
No Thumbnail Available
Name:
Master Thesis Presentation Nursultan Jyeniskhan.pptx
Size:
116.75 MB
Format:
Microsoft Powerpoint XML
Description:
presentation
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
6.28 KB
Format:
Item-specific license agreed upon to submission
Description: