Evidence map›Paper›PMID 34501016›Full record

ReviewMaterials (Basel, Switzerland)2021

A Review of Diagnostics Methodologies for Metal Additive Manufacturing Processes and Products.

Teng Yang, Sangram Mazumder, Yuqi Jin, Brian Squires, Mathew Sofield, Mangesh V Pantawane, Narendra B Dahotre, Arup Neogi

Abstract readReview
In one paragraph

Review in Materials (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. A Review of the Metal Additive Manufacturing Processes.Materials (Basel, Switzerland) · 2023
    Review
  4. Article
  5. Article
  6. Article
  7. 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

8 authors.

Teng YangDepartment of Materials Science and Engineering, University of North Texas, Denton, TX 76207, USA.
Sangram MazumderDepartment of Materials Science and Engineering, University of North Texas, Denton, TX 76207, USA.
Yuqi JinCenter for Agile and Adaptive Additive Manufacturing, University of North Texas, Denton, TX 76207, USA.ORCID 0000-0001-7798-8086
Brian SquiresDepartment of Physics, University of North Texas, Denton, TX 76203, USA.
Mathew SofieldDepartment of Physics, University of North Texas, Denton, TX 76203, USA.
Mangesh V PantawaneDepartment of Materials Science and Engineering, University of North Texas, Denton, TX 76207, USA.
Narendra B DahotreDepartment of Materials Science and Engineering, University of North Texas, Denton, TX 76207, USA.
Arup NeogiCenter for Agile and Adaptive Additive Manufacturing, University of North Texas, Denton, TX 76207, USA.ORCID 0000-0003-3075-8683

Funding

National Science Foundation 1741677
6 · The paper itself

Abstract

Additive manufacturing technologies based on metal are evolving into an essential advanced manufacturing tool for constructing prototypes and parts that can lead to complex structures, dissimilar metal-based structures that cannot be constructed using conventional metallurgical techniques. Unlike traditional manufacturing processes, the metal AM processes are unreliable due to variable process parameters and a lack of conventionally acceptable evaluation methods. A thorough understanding of various diagnostic techniques is essential to improve the quality of additively manufactured products and provide reliable feedback on the manufacturing processes for improving the quality of the products. This review summarizes and discusses various ex-situ inspections and in-situ monitoring methods, including electron-based methods, thermal methods, acoustic methods, laser breakdown, and mechanical methods, for metal additive manufacturing.

Indexed as

additive manufacturingdefectelectron-based characterizationex-situ inspectionin-situ monitoringlaser-induced breakdown spectroscopymechanical testmetal 3D printingmicrostructurethermal imagingultrasonic elastographyultrasonic evaluationultrasonic test

Identifiers

PMID34501016
PMCPMC8434273

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.