Jyeniskhan, Nursultan2023-05-272023-05-272023Jyeniskhan, N. (2023). Investigation of developing digital twin for additive manufacturing. School of Engineering and Digital Scienceshttp://nur.nu.edu.kz/handle/123456789/7119Additive 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.enAttribution-NonCommercial-ShareAlike 3.0 United StatesType of access: EmbargoAdditive manufacturing3D printingdigital twindigitalizationreal-time monitoringerror predictionmachine learningdigital manufacturingMaster's thesis