Evidence map›Paper›PMID 39686320›Full record

ArticleSensors (Basel, Switzerland)2024

Digitalization of an Industrial Process for Bearing Production.

Jose-Manuel Rodriguez-Fortun, Jorge Alvarez, Luis Monzon, Ricardo Salillas, Sergio Noriega, David Escuin, David Abadia, Aitor Barrutia, Victor Gaspar, Jose Antonio Romeo and 2 more

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Jose-Manuel Rodriguez-FortunTechnological Institute of Aragón, Calle Maria de Luna, 7-8, 50018 Zaragoza, Spain.ORCID 0000-0001-8080-7696
Jorge AlvarezIdeko S.Coop, Member of Basque Research and Technology Alliance (BRTA), Arriaga Kalea, 2, 20870 Elgoibar, Gipuzkoa, Spain.ORCID 0000-0002-4031-9281
Luis MonzonTechnological Institute of Aragón, Calle Maria de Luna, 7-8, 50018 Zaragoza, Spain.ORCID 0000-0001-9128-3074
Ricardo SalillasTechnological Institute of Aragón, Calle Maria de Luna, 7-8, 50018 Zaragoza, Spain.ORCID 0000-0003-1369-4745
Sergio NoriegaTechnological Institute of Aragón, Calle Maria de Luna, 7-8, 50018 Zaragoza, Spain.ORCID 0000-0002-0945-9921
David EscuinTechnological Institute of Aragón, Calle Maria de Luna, 7-8, 50018 Zaragoza, Spain.ORCID 0000-0003-2062-8092
David AbadiaTechnological Institute of Aragón, Calle Maria de Luna, 7-8, 50018 Zaragoza, Spain.ORCID 0000-0002-6005-3863
Aitor BarrutiaIdeko S.Coop, Member of Basque Research and Technology Alliance (BRTA), Arriaga Kalea, 2, 20870 Elgoibar, Gipuzkoa, Spain.ORCID 0009-0000-2196-0666
Victor GasparFersa Bearings, Calle Bari 37, 50197 Zaragoza, Spain.
Jose Antonio RomeoFersa Bearings, Calle Bari 37, 50197 Zaragoza, Spain.
Fernando CebrianFersa Bearings, Calle Bari 37, 50197 Zaragoza, Spain.
Rafael Del-Hoyo-AlonsoTechnological Institute of Aragón, Calle Maria de Luna, 7-8, 50018 Zaragoza, Spain.ORCID 0000-0003-2755-5500

Funding

European Union 958363
6 · The paper itself

Abstract

The developments in sensing, actuation, and algorithms, both in terms of Artificial Intelligence (AI) and data treatment, have open up a wide range of possibilities for improving the quality of the production systems in diverse industrial fields. The present paper describes the automatizing process performed in a production line for high-quality bearings. The actuation considered new sensing elements at the machine level and the treatment of the information, fusing the different sources in order to detect quality defects in the grinding process (waviness, burns) and monitoring the state of the tool. At a supervision level, an AI model has been developed for monitoring the complete line and compensating deviations in the dimension of the final assembly. The project also contemplated the hardware architecture for improving the data acquisition and communication among the machines and databases, the data treatment units, and the human interfaces. The resulting system gives feedback to the operator when deviations or potential errors are detected so that the quality issues are recognized and can be amended in advance, thereby reducing the quality cost.

Indexed as

burnsdigitalizationgrindingIndustry 4.0machine learningwaviness

Identifiers

PMID39686320
PMCPMC11644985

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.