Evidence map›Paper›PMID 38280924›Full record

ArticleScientific reports2024

Ironing process optimization for enhanced properties in material extrusion technology using Box-Behnken Design.

Hussein Alzyod, Peter Ficzere

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

2 authors.

Hussein AlzyodDepartment of Railway Vehicles and Vehicle System Analysis, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Műegyetem Rkp. 3, 1111, Budapest, Hungary. Hussein.alzyod@edu.bme.hu.
Peter FiczereDepartment of Railway Vehicles and Vehicle System Analysis, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Műegyetem Rkp. 3, 1111, Budapest, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Material Extrusion (MEX) technology, a prominent process in the field of additive manufacturing (AM), has witnessed significant growth in recent years. The continuous quest for enhanced material properties and refined surface quality has led to the exploration of post-processing techniques. In this study, we delve into the ironing process as a vital processing step, focusing on the optimization of its parameters through the application of Design of Experiments (DoE), specifically the Box-Behnken Design (BBD). Through a systematic examination of ironing process parameters, we identified optimal conditions that resulted in a substantial reduction in surface roughness (Ra) by approximately 69%. Moreover, the integration of optimized ironing process parameters led to remarkable improvements in mechanical properties. For instance, the Ultimate Tensile Strength (UTS) saw a substantial improvement of approximately 29%, while the compressive strength (CS) showed an increase of about 25%. The flexural strength (FS) witnessed a notable enhancement of around 35%, and the impact strength (IS) experienced a significant boost of about 162%. The introduction of ironing minimizes voids, enhances layer bonding, and reduces surface irregularities, resulting in components that not only exhibit exceptional mechanical performance but also possess refined aesthetics. This research sheds light on the transformative potential of precision experimentation, post-processing techniques, and statistical methodologies in advancing Material Extrusion technology. The findings offer practical implications for industries requiring high-performance components with structural integrity and aesthetic appeal.

Identifiers

PMID38280924
PMCPMC10821878

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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.