Evidence map›Paper›PMID 34300614›Full record

ArticleSensors (Basel, Switzerland)2021

Uncertainty Evaluation in Vision-Based Techniques for the Surface Analysis of Composite Material Components.

Giulio D'Emilia, Antonella Gaspari, Emanuela Natale, Davide Ubaldi

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.0field-weighted citation impact, top 22% 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

1 citing paper in PubMed, 10 citations in OpenAlex.

  1. Article
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 at 2 institutions in 1 country.

Giulio D'EmiliaDepartment of Industrial and Information Engineering and of Economics, University of L'Aquila, 67100 L'Aquila, Italy.ORCID 0000-0002-9285-3355
Antonella GaspariDepartment of Mechanics, Mathematics and Management, Polytechnic of Bari, 70125 Bari, Italy.ORCID 0000-0002-9535-6848
Emanuela NataleDepartment of Industrial and Information Engineering and of Economics, University of L'Aquila, 67100 L'Aquila, Italy.ORCID 0000-0002-4547-0538
Davide UbaldiDepartment of Industrial and Information Engineering and of Economics, University of L'Aquila, 67100 L'Aquila, Italy.
University of L'Aquila · ITPolytechnic University of Bari · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, a methodology is discussed concerning the measurement of yarn's angle of two different glass-reinforced polypropylene matrix materials, widely used in the production of automotive components. The measurement method is based on a vision system and image processing techniques for edge detection. Measurements of angles enable, if accurate, both useful suggestions for process optimization to be made, and the reliable validation of the simulation results of the thermoplastic process. Therefore, uncertainty evaluation of angle measurement is a mandatory pre-requisite. If the image acquisition and processing is considered, many aspects influence the whole accuracy of the method; the most important have been identified and their effects evaluated with reference to two different materials, which present different optical-type characteristics. The influence of piece geometry has also been taken into account, carrying out measurements on flat sheets and on a semi-spherical object, which is a reference standard shape, to verify the effect of thermoforming and to tune the process parameters. Complete uncertainty in the order of a few degrees has been obtained, which is satisfactory for purposes of simulation validation and consequent process optimization. The uncertainty budget also allowed individuation of the most relevant causes of uncertainty for measurement process improvement.

Indexed as

angle measurementcomposite materialsimage analysissurface inspectionthermoforminguncertainty

Identifiers

PMID34300614
PMCPMC8309869
OpenAlexW3185422827

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.