Evidence map›Paper›PMID 34203468›Full record

ArticleSensors (Basel, Switzerland)2021

Measurement of Micro Burr and Slot Widths through Image Processing: Comparison of Manual and Automated Measurements in Micro-Milling.

Fatih Akkoyun, Ali Ercetin, Kubilay Aslantas, Danil Yurievich Pimenov, Khaled Giasin, Avinash Lakshmikanthan, Muhammad Aamir

Open access · goldAbstract read
In one paragraph

Article in Sensors (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
4.2field-weighted citation impact, top 5% of its field
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, 48 citations in OpenAlex.

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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

7 authors at 6 institutions in 4 countries.

Fatih AkkoyunDepartment of Mechanical Engineering, Faculty of Engineering, Adnan Menderes University, Aydın 09010, Turkey.
Ali ErcetinDepartment of Mechanical Engineering, Faculty of Engineering and Architecture, Bingol University, Bingol 12000, Turkey.ORCID 0000-0002-7631-1361
Kubilay AslantasDepartment of Mechanical Engineering, Faculty of Technology, Afyon Kocatepe University, Afyonkarahisar 03200, Turkey.ORCID 0000-0003-4558-4516
Danil Yurievich PimenovDepartment of Automated Mechanical Engineering, South Ural State University, Lenin Prosp. 76, 454080 Chelyabinsk, Russia.ORCID 0000-0002-5568-8928
Khaled GiasinSchool of Mechanical and Design Engineering, University of Portsmouth, Portsmouth PO1 3DJ, UK.ORCID 0000-0002-3992-8602
Avinash LakshmikanthanDepartment of Mechanical Engineering, Nitte Meenakshi Institute of Technology, Bengaluru 560064, India.
Muhammad AamirSchool of Engineering, Edith Cowan University, Joondalup, WA 6027, Australia.ORCID 0000-0003-0733-919X
Adnan Menderes University · TRAfyon Kocatepe University · TRBingöl University · TREdith Cowan University · AUSouth Ural State University · RUUniversity of Portsmouth · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, the burr and slot widths formed after the micro-milling process of Inconel 718 alloy were investigated using a rapid and accurate image processing method. The measurements were obtained using a user-defined subroutine for image processing. To determine the accuracy of the developed imaging process technique, the automated measurement results were compared against results measured using a manual measurement method. For the cutting experiments, Inconel 718 alloy was machined using several cutting tools with different geometry, such as the helix angle, axial rake angle, and number of cutting edges. The images of the burr and slots were captured using a scanning electron microscope (SEM). The captured images were processed with computer vision software, which was written in C++ programming language and open-sourced computer library (Open CV). According to the results, it was determined that there is a good correlation between automated and manual measurements of slot and burr widths. The accuracy of the proposed method is above 91%, 98%, and 99% for up milling, down milling, and slot measurements, respectively. The conducted study offers a user-friendly, fast, and accurate solution using computer vision (CV) technology by requiring only one SEM image as input to characterize slot and burr formation.

Indexed as

Image Processing, Computer-Assistedcharacterizationcomputer visionimage processingmeasurementmicro-machiningslot and burrs

Identifiers

PMID34203468
PMCPMC8271581
OpenAlexW3174221070

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.