Evidence map›Paper›PMID 38756928›Full record

ArticleData in brief2024

Surface roughness and dimension accuracy data from hybrid manufacturing process using PLA material.

Benny Susanto, Muhammad Ibnu Rashyid, Fefria Tanbar, Hifni Mukhtar Ariyadi, Muhammad Akhsin Muflikhun

Abstract read
In one paragraph

Article in Data in brief, 2024. 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
–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

1 citing paper in PubMed.

  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

5 authors.

Benny SusantoPLN Research Institute, Jakarta, Indonesia.
Muhammad Ibnu RashyidMechanical and Industrial Engineering Department, Gadjah Mada University, Indonesia.
Fefria TanbarPLN Research Institute, Jakarta, Indonesia.
Hifni Mukhtar AriyadiMechanical and Industrial Engineering Department, Gadjah Mada University, Indonesia.
Muhammad Akhsin MuflikhunMechanical and Industrial Engineering Department, Gadjah Mada University, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper introduces a comprehensive dataset focusing on the surface roughness and dimensional accuracy of 3D printed specimens derived from a hybrid manufacturing process. The design of these specimens incorporates surfaces oriented at 0˚, 45˚, and 90˚ angles for surface roughness testing, along with cylindrical, radial, and pocket areas to evaluate dimensional accuracy. Utilizing PLA material, the specimens undergo a printing phase followed by milling within the same machine, thereby enhancing both surface roughness and dimensional quality. Surface roughness data is gathered through a surface roughness tester, while dimensional accuracy is assessed using a digital vernier caliper. The dataset includes comparative analyses conducted before and after the hybrid manufacturing process, revealing notable improvements in both surface roughness and dimensional accuracy post-processing. These findings furnish valuable insights for researchers and engineers engaged in hybrid manufacturing processes involving PLA material, serving as a foundational resource for further investigations and advancements in the field.

Indexed as

3D printingHybrid manufacturingSurface roughness, Dimension accuracy

Identifiers

PMID38756928
PMCPMC11096829

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.