Micro Manufacturing Unit and the Corresponding 3D-Model for the Digital Twin

Lohtander, Mika; Ahonen, Niko; Lanz, Minna; Ratava, Juho; Kaakkunen, Jarno

doi:10.1016/j.promfg.2018.06.057

Cited by 68 publications

(12 citation statements)

References 8 publications

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“…Another application of Digital Twins is in the automotive industry, most notably demonstrated by Tesla. The ability to have a Digital Twin of an engine or car part can be valuable in terms of using the twin for simulation and data analytics [30] [31]. AI improves the accuracy of testing as it can perform data analytics on live vehicle data to predict the current and future performance of components.…”

Section: ) Manufacturingmentioning

confidence: 99%

Digital Twin: Enabling Technologies, Challenges and Open Research

et al. 2020

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Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry. The Digital Twin is defined extensively but is best described as the effortless integration of data between a physical and virtual machine in either direction. The challenges, applications, and enabling technologies for Artificial Intelligence, Internet of Things (IoT) and Digital Twins are presented. A review of publications relating to Digital Twins is performed, producing a categorical review of recent papers. The review has categorised them by research areas: manufacturing, healthcare and smart cities, discussing a range of papers that reflect these areas and the current state of research. The paper provides an assessment of the enabling technologies, challenges and open research for Digital Twins.

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Section: ) Manufacturingmentioning

confidence: 99%

Digital Twin: Enabling Technologies, Challenges and Open Research

et al. 2020

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“…When it comes to manufacturing, DT can help predict issues sooner as it can give real-time data on machine performances and production lines [27]. In the case of the automotive industry, the DT of the car engine or other parts can be used for simulation while data analytics can be used to predict the component"s present as well as future capabilities [28], [29]. Such use of DT has most famously been implemented by Tesla [12].…”

Section: Manufacturingmentioning

confidence: 99%

Digital Twin and Its Implementation in 3D Printing: A Research Review

Bhattarai¹,

Shrestha²,

Chohan³

2022

int.jour.sci.res.mana.

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The emergence of Additive Manufacturing (AM) has created a plethora of opportunities for different industries due to its application in 3D printing technology. Since its introduction back in 1980, 3D printing technology has overseen numerous developments and changes. A rarity back in the day, 3D printing has now become cheaper and available for everyone who wishes to learn and experiment with the technology. Although 3D printing technology can produce optimized and detailed printing at a cheaper rate than in earlier days, it can still be time-consuming and quite costly due to the technology's tendency to follow the trial-and-error method when printing. A proposed solution to such an issue is by implementing Digital Twin (DT), a virtual representation of an object that provides real-time reflection between the virtual and physical space and can interact and converge with the flow of data between both spaces. However, despite the need, Digital Twin is yet to achieve its fullest potential due to a gap in knowledge regarding its concept and development methods. This paper, therefore, intends to provide a brief review regarding the implementation, applications as well as challenges of DT for 3D printing, to provide an understanding of the current trends that can be utilized for further research regarding Digital Twin and its implementation in 3D printing.

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“…In this new domain early works have demonstrated appropriate geometric representation [38], usability of simulation modelling methods [39], modules to support decision making [35], product cell emulation for control verification [40], data exchange, modelling and storage [41,42]. However, significant stated challenges in realising Digital Shadows and Digital Twins relate to the availability / acquisition of real-time and appropriate shopfloor data and open or standards for hardware/software architectures and interfaces [37,38,42,43,44]. To the authors best knowledge, no works have used simulation approaches, in the form of a Digital Model or Digital Shadow, to examine the data exchange requirements between the digital representation of a production system and its associated financial representation.…”

Section: Simulationmentioning

confidence: 99%