Digital Twin for Integration of Design-Manufacturing-Maintenance: An Overview

Fu, Yang; Zhu, Gang; Zhu, Ming‐Liang; Xuan, Fu‐Zhen

doi:10.1186/s10033-022-00760-x

Cited by 39 publications

(20 citation statements)

References 158 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cluster Information The primary cluster, identified as #0, comprises 50 members with a silhouette value of 0.772 and is denoted as "digital shadow" by LLR. Its main reference article is Fu, Y (2022.0-JAN) [30] Table 9 displays the citation counts of clusters, with publisher names serving as node names.…”

Section: Document Citation Analysis Of Digital Twin For Manufacturingmentioning

confidence: 99%

Scientometric Insights of Digital Twins in Industry 4.0

Kaur,

Bhatia

2024

Preprint

View full text Add to dashboard Cite

Industry 4.0 is a new era of digitization that integrates digital technologies to create smart, interconnected production systems, marking a paradigm shift in different domains. One of the key technologies in this era is 'Digital Twin', which offers virtual representations of physical assets and processes. It is crucial to analyze the role of digital twin technology in the context of Industry 4.0 using scientometric analysis with citeSpace, a powerful tool for visualizing and analyzing citation networks. This research focuses on the growth trajectory of digital twin literature, identifies influential authors, institutions, and journals, and analyzes the geographical distribution of research contributions from the Scopus database for 2018-2024. The findings reveal insights into the current state of digital twin research, its impact on Industry 4.0, and opportunities for future exploration and collaboration in this rapidly evolving field.

show abstract

Section: Document Citation Analysis Of Digital Twin For Manufacturingmentioning

confidence: 99%

Scientometric Insights of Digital Twins in Industry 4.0

Kaur,

Bhatia

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The term digital twin has gained popularity recently in academic and industrial circles [18]. A digital twin is a set of virtual information constructs which fully describe the possible or actual physical manufactured product from the micro-atomic level to the macro-geometric level [19,20]. At its optimum, any information that could be obtained by inspecting a physically manufactured product can be derived from its digital twin [19].…”

Section: Plos Onementioning

confidence: 99%

“…Headlamps with no points outside tolerances satisfied the limits for accuracy. The remainder of the samples were separated according to the number of points outside tolerances: low (1-4), medium (5-10) and high (11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25).…”

Section: Plos Onementioning

confidence: 99%

Adjusting products with compensatory elements using a digital twin: Model and methodology

Konecny

Bailova²,

Beremlijski³

et al. 2023

PLoS ONE

View full text Add to dashboard Cite

The article presents a novel strategy for reducing the geometric error of a vehicle headlamp equipped with a set of calibration screws, which represents a product assembly. Using a general method for designing and implementing a digital twin, we determined the optimal configuration for a compensatory element that minimizes the total geometric error. Formulated as a problem of constrained minimization, we solved the error using the gradient method and the Broyden–Fletcher–Goldfarb–Shanno method. Products are automatically adjusted according to this optimal setting during the manufacturing process. The results of this novel method indicate that all points can be aligned when the non-individual calibration satifies a geometrical specification of 92%. The digital twin approach was compared to the manufacturing process on 84,055 samples. Overall, 98.19% of the samples were perfectly aligned.

show abstract

“…[202] Digital twin technology Widely used in the establishment and enrichment of the database. [203] Divide and conquer The adaptability was enhanced. [85] ANN, PLS, GA.…”

Section: Characteristics Referencesmentioning

confidence: 99%

A State‐of‐Art Review on Prediction Model for Fatigue Performance of Welded Joints via Data‐Driven Method

Feng

Zhao

et al. 2023

Adv Eng Mater

View full text Add to dashboard Cite

Fatigue fracture of welded joints is an important cause for engineering accidents. Due to the coexistence of so many influencing factors, the current prediction model of fatigue behavior cannot be used for all service conditions. The progress of each module (database establishment, data processing, data augmentation, dimension reduction, and comprehensive consideration of influencing factors) during the process of constructing a prediction model is summarized herein. Specifically, the state‐of‐art prediction models of fatigue strength, fatigue crack growth rate, fatigue life, and fatigue reliability are introduced. Moreover, suggestions for future work are given at the end of each section. Finally, according to the influential prediction methods, the establishment of fatigue performance prediction methods of welded joints via data‐driven method is summarized.

show abstract

Digital Twin for Integration of Design-Manufacturing-Maintenance: An Overview

Cited by 39 publications

References 158 publications

Scientometric Insights of Digital Twins in Industry 4.0

Scientometric Insights of Digital Twins in Industry 4.0

Adjusting products with compensatory elements using a digital twin: Model and methodology

A State‐of‐Art Review on Prediction Model for Fatigue Performance of Welded Joints via Data‐Driven Method

Contact Info

Product

Resources

About