Evidence map›Paper›PMID 36365805›Full record

ArticleSensors (Basel, Switzerland)2022

AI-Based Support System for Monitoring the Quality of a Product within Industry 4.0 Paradigm.

Izabela Rojek, Ewa Dostatni, Jakub Kopowski, Marek Macko, Dariusz Mikołajewski

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.5field-weighted citation impact, top 19% of its field
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

3 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

5 authors at 2 institutions in 1 country.

Izabela RojekInstitute of Computer Science, Kazimierz Wielki University, 85-064 Bydgoszcz, Poland.ORCID 0000-0002-9958-6579
Ewa DostatniFaculty of Mechanical Engineering, Poznan University of Technology, 60-965 Poznan, Poland.ORCID 0000-0003-3723-4540
Jakub KopowskiInstitute of Computer Science, Kazimierz Wielki University, 85-064 Bydgoszcz, Poland.ORCID 0000-0002-5160-1776
Marek MackoFaculty of Mechatronics, Kazimierz Wielki University, 85-064 Bydgoszcz, Poland.ORCID 0000-0002-8743-6602
Dariusz MikołajewskiInstitute of Computer Science, Kazimierz Wielki University, 85-064 Bydgoszcz, Poland.ORCID 0000-0003-4157-2796
Kazimierz Wielki University in Bydgoszcz · PLPoznań University of Technology · PL

Funding

The work presented in the paper has been co-financed under grant to maintain the research poten-tial of Kazimierz Wielki University and grant no. 0613/SBAD/4710. The work presented in the paper has been co-financed under grant to maintain the research poten-tial of Kazimierz Wielki University and grant no. 0613/SBAD/4710.
6 · The paper itself

Abstract

Three-dimensional (3D) printing, also known as additive manufacturing (AM), has already shown its potential in the fourth technological revolution (Industry 4.0), demonstrating remarkable applications in manufacturing, including of medical devices. The aim of this publication is to present the novel concept of support by artificial intelligence (AI) for quality control of AM of medical devices made of polymeric materials, based on the example of our own elbow exoskeleton. The methodology of the above-mentioned inspection process differs depending on the intended application of 3D printing as well as 3D scanning or reverse engineering. The use of artificial intelligence increases the versatility of this process, allowing it to be adapted to specific needs. This brings not only innovative scientific and technological solutions, but also a significant economic and social impact through faster operation, greater efficiency, and cost savings. The article also indicates the limitations and directions for the further development of the proposed solution.

Indexed as

Artificial IntelligencePrinting, Three-DimensionalIndustryPolymersTechnologyPolymers3D printingartificial intelligenceexoskeletonIndustrial Internet of Thingsmedical devicesprocess monitoringproduction optimization

Identifiers

PMID36365805
PMCPMC9656927
OpenAlexW4307266780

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.