Evidence map›Paper›PMID 40218590›Full record

ArticleSensors (Basel, Switzerland)2025

Digital Twin-Based Active Learning for Industrial Process Control and Supervision in Industry 4.0.

Jessica S Ortiz, Evelin K Quishpe, Grace X Sailema, Nathaly S Guamán

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jessica S OrtizDepartamento de Eléctrica, Electrónica y Telecomunicaciones, Universidad de las Fuerzas Armadas ESPE, Sangolquí 171103, Ecuador.ORCID 0000-0001-9085-4402
Evelin K QuishpeDepartamento de Ciencias de la Energía y Mecánica, Universidad de las Fuerzas Armadas ESPE, Sangolquí 171103, Ecuador.
Grace X SailemaDepartamento de Ciencias de la Energía y Mecánica, Universidad de las Fuerzas Armadas ESPE, Sangolquí 171103, Ecuador.
Nathaly S GuamánDepartamento de Ciencias de la Energía y Mecánica, Universidad de las Fuerzas Armadas ESPE, Sangolquí 171103, Ecuador.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of Digital Twin technology into active learning environments has been established as an innovative strategy to optimize engineering education. This study focuses on the development and evaluation of a learning tool based on Digital Twin technology, enabling interaction and communication between a physical teaching module and a virtualized environment representing the industrial cocoa production process. The system was operated by students using an S7-1200 PLC and an HMI interface developed in WinCC, facilitating real-time process monitoring and control via IoT. To assess its impact, an experimental design was implemented, comparing a pre-test using conventional teaching modules with a post-test incorporating Digital Twin technology. The results indicate a significant improvement in students' accuracy and efficiency, with a 38% reduction in task execution time. This improvement is attributed to the system's immersive and interactive capabilities, which allow for the simulation of actuator and sensor behavior under real-world conditions. These findings highlight the potential of Digital Twins not only as educational tools but also as valuable assets for industrial process optimization in the cocoa sector, aligning with Industry 4.0 principles.

Indexed as

active learningDigital TwinIndustry 4.0virtualized environment

Identifiers

PMID40218590
PMCPMC11991266

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.