Content deleted Content added
→Digital Twin: Date errors |
Citation bot (talk | contribs) Add: article-number, bibcode. Removed URL that duplicated identifier. Removed parameters. Some additions/deletions were parameter name changes. | Use this bot. Report bugs. | Suggested by Headbomb | Linked from Wikipedia:WikiProject_Academic_Journals/Journals_cited_by_Wikipedia/Sandbox | #UCB_webform_linked 676/1032 |
||
| (13 intermediate revisions by 9 users not shown) | |||
Line 1:
{{Short description|Data-driven architecture
{{context|date=November 2018}}
'''Digital
The term '
Digital thread enables "data to be integrated into one platform, allowing seamless use of and ease of access to all data".<ref name=":5">{{Cite journal |last1=Pang |first1=Toh Yen |last2=Pelaez Restrepo |first2=Juan D. |last3=Cheng |first3=Chi-Tsun |last4=Yasin |first4=Alim |last5=Lim |first5=Hailey |last6=Miletic |first6=Miro |date=January 2021 |title=Developing a Digital Twin and Digital Thread Framework for an 'Industry 4.0' Shipyard |journal=Applied Sciences |language=en |volume=11 |issue=3 |pages=1097 |doi=10.3390/app11031097 |issn=2076-3417 |doi-access=free }}</ref>
The digital thread is a critical capability in [[model-based systems engineering]] (MBSE) and the foundation for a [[Digital twin]], which is defined as "a digital replica of a physical entity"<ref name=":3">{{Cite journal |last=Aheleroff |first=Shohin |last2=Xu |first2=Xun |last3=Zhong |first3=Ray Y. |last4=Lu |first4=Yuqian |date=January 2021 |title=Digital Twin as a Service (DTaaS) in Industry 4.0: An Architecture Reference Model |url=https://linkinghub.elsevier.com/retrieve/pii/S1474034620301944 |journal=Advanced Engineering Informatics |language=en |volume=47 |pages=101225 |doi=10.1016/j.aei.2020.101225}}</ref>. In fact, digital thread was first described as related to [[Digital twin]] in the Global Horizons 2013 report<ref name=":0" />. Digital thread is a means to gather data for use in the development of a [[Digital twin]]; "some argue [digital thread] is the backbone of digital twin applications"<ref>{{Cite journal |last=Kwon |first=Soonjo |last2=Monnier |first2=Laetitia V. |last3=Barbau |first3=Raphael |last4=Bernstein |first4=William Z. |date=October 2020 |title=Enriching standards-based digital thread by fusing as-designed and as-inspected data using knowledge graphs |url=https://linkinghub.elsevier.com/retrieve/pii/S1474034620300719 |journal=Advanced Engineering Informatics |language=en |volume=46 |pages=101102 |doi=10.1016/j.aei.2020.101102}}</ref>. "digital thread platforms can capture data from different systems, standardize it, and provide a seamless link between the physical process or product and the digital twin"<ref>{{Cite web |last=ahuff |date=2022-06-04 |title=How digital twins, IIoT technologies benefit operations |url=https://www.controleng.com/articles/how-digital-twins-iiot-technologies-benefit-operations/ |access-date=2023-07-11 |website=Control Engineering |language=en-US}}</ref>. The term digital thread is also used to describe the traceability of the [[digital twin]] back to the requirements, parts and control systems that make up the physical asset. <ref>{{Cite web|url=https://www.gardnerweb.com/articles/what-are-digital-twins-and-digital-threads|title=What Are Digital Twins and Digital Threads?|last=Gould|first=Lawrence S.|website=Automotive Design & Production|access-date=2021-07-27}}</ref>▼
=== Digital twin ===
Although digital thread and [[Digital twin]] are "every so often understood to be synonymous...they are not the same as Digital Twin relies on real-time data from its physical counterpart"<ref name=":3" />. "In short, digital thread describes the process while digital twin symbolizes technology"<ref name=":4">{{Cite journal |last=Daase |first=Christian |last2=Haertel |first2=Christian |last3=Nahhas |first3=Abdulrahman |last4=Volk |first4=Matthias |last5=Steigerwald |first5=Heiko |last6=Ramesohl |first6=Achim |last7=Schneider |first7=Bernd |last8=Zeier |first8=Alexander |last9=Turowski |first9=Klaus |date=2023 |title=Following the Digital Thread – A Cloud-Based Observation |url=https://linkinghub.elsevier.com/retrieve/pii/S1877050922024723 |journal=Procedia Computer Science |language=en |volume=217 |pages=1867–1876 |doi=10.1016/j.procs.2022.12.387}}</ref>. "Compared to the digital twin, the digital thread can support decision-making by designing and regulating the data interaction and processing instead of high-fidelity system models"<ref name=":1" />.▼
[[Idaho National Laboratory|Idaho National Laboratories]] describes Digital Twin as "the merging of integrated and connected data, sensors and instrumentation, artificial intelligence, and online monitoring into a single cohesive unit."<ref>{{Cite web |last=Cristopher |first=Ritter |date=July 28, 2023 |title=Lab Directed Research and Development (LDRD) Digital Twin Overview |url=https://www.nrc.gov/docs/ML2132/ML21326A185.pdf |access-date=July 28, 2023 |publisher=Digital Innovation Center of Excellence}}</ref>
▲
=== Internet of Things ===▼
A key aspect of digital thread is the [[Internet of things]], whose "cyber-physical systems, sensors, and so-called smart devices" are an important source of the data required by digital thread<ref name=":4" />. "The ability to gather massive amounts of data through the aspired omnipresence of sensors furthermore fuels the emergence of other key technologies" such as [[Big data analytics]], [[Artificial intelligence]], and [[Cloud computing]]<ref name=":4" />. "Thus, the data collected by using IoT technologies constitute the basis of advanced simulation models, which is in essence the livelihood of the digital twin paradigm and therefore also an integral part of the wider digital thread."<ref name=":4" />▼
▲Although digital thread and [[Digital twin]] are "every so often understood to be synonymous...they are not the same as Digital Twin relies on real-time data from its physical counterpart".<ref name=":3" />
=== Smart Manufacturing ===▼
[[Big data analytics]] and [[Artificial intelligence|Artificial Intelligence]] used in conjunction with Digital Thread are increasingly more required in [[smart manufacturing]] applications<ref name=":4" />. [[Big data analytics]] is a "prerequisite for managing highly variable"<ref name=":4" /> data of [[smart manufacturing]] processes, gathered through digital thread. [[Artificial intelligence|Artificial Intelligence]] can be trained using this data to create "autonomously self-improving production processes [14] and to facilitate organizational decision-making"<ref name=":4" />. "the digital thread paradigm not only leads to the accumulation and processing of massive amounts of data but is also shaped by the analytical results these both technologies provide"<ref name=":4" />.▼
A digital thread enables a [[Digital twin]]<ref>{{Cite news |last=altair |date=2024-06-20 |title=How digital threads enable a new era of product development |url=https://www.fastcompany.com/91142265/how-digital-threads-enable-a-new-era-of-product-development |archive-url=http://web.archive.org/web/20250219123819/https://www.fastcompany.com/91142265/how-digital-threads-enable-a-new-era-of-product-development |archive-date=2025-02-19 |access-date=2025-03-27 |work=Fast Company |language=en-US}}</ref> by ensuring that incoming data is made uniform and easily accessible through the three main data chains:<ref name=":5" />
# '''The Product Innovation chain''' - Product designs, processes, and design flow are incorporated into the digital thread<ref name=":5" />
# '''The Enterprise Value chain''' - Supplier information, material data, and manufacturing processes are incorporated into the digital thread.<ref name=":5" />
# '''The Field and Service chain''' - Maintenance manuals and part availability are incorporated into the digital thread.<ref name=":5" />
Enabling a [[Digital twin]] could result in petabytes of data,<ref name=":6">{{Cite book |last=Darrington |first=John Wayne |title=The DeepLynx Data Warehouse |publisher=Idaho National Laboratory |year=2022 |language=en}}</ref> and "necessitate the use of highly sophisticated tools and software."<ref name=":6" />
==== Tools ====
===== DeepLynx =====
"DeepLynx is an ontological [[data warehouse]] with [[Time series|timeseries]] data support". It was primarily authored by John Darrington and Cristopher Ritter to tackle Model-Based Systems Engineering (MBSE) tool integrations and warehousing, and has evolved to enable support for [[digital twin]].
▲A key aspect of digital thread is the [[Internet of things]], whose "cyber-physical systems, sensors, and so-called smart devices" are an important source of the data required by digital thread.<ref name=":4" />
▲[[Big data analytics]] and [[
== References ==
| |||