Evidence map›Paper›PMID 38732666›Full record

ArticlePolymers2024

Method Development for the Prediction of Melt Quality in the Extrusion Process.

Dorte Trienens, Volker Schöppner, Peter Krause, Thomas Bäck, Seraphin Tsi-Nda Lontsi, Finn Budde

Abstract read
In one paragraph

Article in Polymers, 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

6 authors.

Dorte TrienensKunststofftechnik Paderborn, Paderborn University, 33098 Paderborn, Germany.
Volker SchöppnerKunststofftechnik Paderborn, Paderborn University, 33098 Paderborn, Germany.
Peter KrauseDivis Intelligent Solutions GmbH, 44227 Dortmund, Germany.
Thomas BäckDivis Intelligent Solutions GmbH, 44227 Dortmund, Germany.
Seraphin Tsi-Nda LontsiDivis Intelligent Solutions GmbH, 44227 Dortmund, Germany.
Finn BuddeKunststofftechnik Paderborn, Paderborn University, 33098 Paderborn, Germany.

Funding

Deutsche Forschungsgemeinschaft SCHO 551/42-1
6 · The paper itself

Abstract

Simulation models are used to design extruders in the polymer processing industry. This eliminates the need for prototypes and reduces development time for extruders and, in particular, extrusion screws. These programs simulate, among other process parameters, the temperature and pressure curves in the extruder. At present, it is not possible to predict the resulting melt quality from these results. This paper presents a simulation model for predicting the melt quality in the extrusion process. Previous work has shown correlations between material and thermal homogeneity and the screw performance index. As a result, the screw performance index can be used as a target value for the model to be developed. The results of the simulations were used as input variables, and with the help of artificial intelligence-more precisely, machine learning-a linear regression model was built. Finally, the correlation between the process parameters and the melt quality was determined, and the quality of the model was evaluated.

Indexed as

machine learningmelt qualitypolymer extrusion processscrew performance indexsimulation

Identifiers

PMID38732666
PMCPMC11085388

What OpenQuestion holds

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LicenceCC BY
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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.