CoChat
Sign Up
Cited by 153Digital Transformation in IndustryFlexible and Reconfigurable Manufacturing SystemsImpact of AI and Big Data on Business and Society

Ubiquitous knowledge empowers the Smart Factory: The impacts of a Service-oriented Digital Twin on enterprises' performance

Open access
Longo, Francesco, Nicoletti, Letizia, Padovano, Antonio·2019·Annual Reviews in Control
DOI 10.1016/j.arcontrol.2019.01.001
Open this paper in CoChat — free accountOpen PDF

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.arcontrol.2019.01.001

Cites

27 of 27 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Seven articles in Table 1 developed ad-hoc systems to build DT.

    “In Table 1 seven articles developed ' ad-hoc ' systems to build DT: for the management of a didactic production line [26], to construct a MES in Android systems [43], to build user guides for safety reason [60,62], and to evaluate the performances of a cloud-based DT [74,75];”

    From Review of digital twin applications in manufacturing (2019) · cites this paper as [43]

    Section 3.2.2 (p. 16) describes a purpose-built Android application that accesses services from the authors’ Digital Twin, supporting its inclusion as an ad-hoc DT system. But §3.2 (p. 12) describes MES as a possible third-party system for integration, not as something the authors built on Android. This paper also cannot establish the citing document’s count of seven articles. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • The reviewed articles can be divided into two categories by cloud usage: those that effectively use a cloud and build a cloud-based DT application, and those that construct the DT application in a virtual space with software highlighting the possibility to build it also in a cloud-based environment.

    “For this aspect, the articles considered can be divided into two different categories: (i) those that effectively use a cloud and build a cloud-based DT application, marked in the table as [27,34,37,43,47,48,54,56,62,67,74-76], (ii) those that construct the DT application in a virtual space with the use of a software highlighting the possibility to build it also in a cloud”

    From Review of digital twin applications in manufacturing (2019) · cites this paper as [43]

    Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

  • The only reviewed articles that actually perform control of the real system are ad-hoc systems, meaning they used open protocols and programmable boards.

    “The only articles that actually perform a control of the real system (i.e. in Table 1, column 'Control of the real system from the digital twin') are ' ad-hoc systems ' [43,74,75], meaning that they used open protocols and programmable boards.”

    From Review of digital twin applications in manufacturing (2019) · cites this paper as [43]

    Section 3.1 (p. 11) describes a service that converts production scenarios into CPPS parameters and actuator instructions, and section 3.2 (p. 12) describes RESTful web services and CoAP. But the deployed prototype in section 4 (p. 18) is described as providing knowledge access; our copy does not establish that it actually controlled the physical system or used programmable boards. The 'only articles' comparison is the citing authors’ review conclusion, not a finding attributed to this source. (LLM, conf=0.79)

    Experimental — accuracy not yet measured

  • Only in one case the DT is constructed in an Android application to be itself a MES for the system [43]; in the other cases, integration with the MES is mentioned only in a theoretical way.

    “Only in one case the DT is constructed in Android application to be itself a MES for the system [43], in the other cases, already showed in Section 3, the integration with the MES is mentioned only in a theoretical way.”

    From Review of digital twin applications in manufacturing (2019) · cites this paper as [43]

    Section 3.2.2 (p. 16) describes an Android application for shop-floor operators, supporting that part of the cited clause. But Section 3.2 (pp. 12–13) describes the app as a gateway to a distributed Digital Twin and treats MES as a separate system; it does not say the Digital Twin was constructed in the Android app or that the app itself served as the MES. The claim about the other cases is not attributed to this citation. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • Digital twins monitor a production line.

    “or a production line [42,43,46]”

    From Review of digital twin applications in manufacturing (2019) · cites this paper as [43]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. [7]7. Iarovyi, S., Mohammed, W. M., Lobov, A., Ferrer, B. R., & Lastra, J. L. M. (2016). Cyberphysical systems for open-knowledge-driven manufacturing execution systems. Proceedings of the IEEE , 104(5), 1142-1154.

Cited by

Sorted by citations

Related

Authors
Longo, F., Nicoletti, L., & Padovano, A.
Affiliations
University of Calabria (IT)
Corresponding author
  • Longo, Francesco
  • Nicoletti, Letizia
  • Padovano, Antonio
ORCID
Venue
Annual Reviews in Control
Publisher
Elsevier BV
Published
2019
Volume
47
Pages
221-236
ISSN
1367-5788 (ISSN-L)
DOI
10.1016/j.arcontrol.2019.01.001
OpenAlex
W2913961714
Cited by
153
References
27
Citations by year
2026: 10 · 2025: 25 · 2024: 23 · 2023: 22 · 2022: 37 · 2021: 20 · 2020: 15 · 2019: 1
FWCI
13.47
Type
journal article
Language
en
Open access
Licence
Locations
  • Annual Reviews in Control (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • Archive of Doctoral Theses and Digital Collections (University of Calabria) (submittedVersion)
  • arXiv (Cornell University)
Topics
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Flexible and Reconfigurable Manufacturing Systems
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
Keywords
human-centric manufacturing, Industry 4.0, smart factory, augmented reality, vocal interaction, knowledge retrieval, machine setup, small and medium-sized enterprises, firm performance, Industrial Internet of Things

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review