Evidence map›Paper›PMID 37688259›Full record

ArticlePolymers2023

Analyzing Surface Roughness Variations in Material Extrusion Additive Manufacturing of Nylon Carbon Fiber Composites.

Muhammad Abas, Mohammed Al Awadh, Tufail Habib, Sahar Noor

Abstract read
In one paragraph

Article in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 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

4 authors.

Muhammad AbasDepartment of Industrial Engineering, University of Engineering & Technology, Peshawar 25100, Pakistan.ORCID 0000-0002-9294-2964
Mohammed Al AwadhDepartment of Industrial Engineering, King Khalid University, Farah 64231, Saudi Arabia.ORCID 0000-0002-9810-1111
Tufail HabibDepartment of Industrial Engineering, University of Engineering & Technology, Peshawar 25100, Pakistan.ORCID 0000-0002-1424-5960
Sahar NoorDepartment of Industrial Engineering, University of Engineering & Technology, Peshawar 25100, Pakistan.

Funding

King Khalid University RGP.2/306/44Pakistan Science Foundation PSF/CRP/KPK-UET/T-Helix (126)
6 · The paper itself

Abstract

In recent years, fused deposition modeling (FDM) based on material extrusion additive manufacturing technology has become widely accepted as a cost-effective method for fabricating engineering components with net-shapes. However, the limited exploration of the influence of FDM process parameters on surface roughness parameters, i.e., Ra (average surface roughness), Rq (root mean square surface roughness), and Rz (maximum height of the profile) across different sides (bottom, top, and walls) poses a challenge for the fabrication of functional parts. This research aims to bridge the knowledge gap by analyzing surface roughness under various process parameters and optimizing it for nylon carbon fiber printed parts. A definitive screening design (DSD) was employed for experimental runs. The Pareto chart highlighted the significant effects of layer height, part orientation, and infill density on all surface roughness parameters and respective sides. The surface morphology was analyzed through optical microscopy. Multi-response optimization was performed using an integrated approach of composited desirability function and entropy. The findings of the present study hold significant industrial applications, enhancing the quality and performance of 3D printed parts. From intricate prototypes to durable automotive components, the optimized surfaces contribute to production of functional and visually appealing products across various sectors.

Indexed as

composite desirability functiondefinitive screening designentropyfused deposition modelingnylon carbon fibersurface roughness

Identifiers

PMID37688259
PMCPMC10489770

What OpenQuestion holds

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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.