Design and implementation of a digital twin application for a connected micro smart factory

Recently, manufacturing concepts, such as personalized production and distributed manufacturing, have attracted attention owing to the ongoing revolution in industrial technology. Connected micro smart factories in factory-as-a-service system with these new manufacturing paradigms and Industrial Int...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of computer integrated manufacturing 2019-06, Vol.32 (6), p.596-614
Hauptverfasser: Park, Kyu Tae, Nam, Young Wook, Lee, Hyeon Seung, Im, Sung Ju, Noh, Sang Do, Son, Ji Yeon, Kim, Hyun
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Recently, manufacturing concepts, such as personalized production and distributed manufacturing, have attracted attention owing to the ongoing revolution in industrial technology. Connected micro smart factories in factory-as-a-service system with these new manufacturing paradigms and Industrial Internet of Things (IIoT) are inefficient in terms of cost and production. To solve these problems, a digital twin, which uses a digital representation of a process, with the same configuration of manufacturing elements, synchronized information, and functional units, was designed and implemented. The digital twin utilizes the latest information from the Internet to gather data from IIoT devices and interoperates in a variety of applications. In addition, it derives the components of a detailed design of the digital twin application, to which it performs procedure definition. This research differs from other digital twin studies that concentrate on the prognostic health management of only a single machine. This study could help managers organize the benefits of utilization through a digital twin based on a hierarchy as they could receive real-time monitoring of the present, tracking information from the past, and operational decision-making support for the future. In addition, the proposed application reduces the cost and production inefficiencies, ultimately resulting in the efficient operation of a manufacturing system.
ISSN:0951-192X
1362-3052
DOI:10.1080/0951192X.2019.1599439