Evidence map›Paper›PMID 36296099›Full record

ArticleMicromachines2022

Estimation of Surface Roughness on Milled Surface Using Capacitance Sensor Based Micro Gantry System through Single-Shot Approach.

Rajendran Mathiyazhagan, SenthamaraiKannan SampathKumar, Palanisamy Karthikeyan

Abstract read
In one paragraph

Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Rajendran MathiyazhaganDepartment of Production Technology, Madras Institute of Technology Campus, Anna University, Chennai 600044, Tamil Nadu, India.ORCID 0000-0001-7420-5939
SenthamaraiKannan SampathKumarDepartment of Mechanical Engineering, College of Engineering Campus, Anna University, Chennai 600025, Tamil Nadu, India.
Palanisamy KarthikeyanDepartment of Production Technology, Madras Institute of Technology Campus, Anna University, Chennai 600044, Tamil Nadu, India.ORCID 0000-0001-9944-5250

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The profile generation is highly complex for roughness measurement using a capacitive sensor because of the small peak-to-peak width of the machined surface and the close proximity of the sensor setting with the machining setup which has the chance of damaging the sensor. Considering these shortcomings, a higher sensor sensing diameter with an appropriate resolution has been selected for a single-shot approach. An automated micro gantry XYZ system is integrated with a capacitive sensor to precisely target, move, and measure the roughness. For investigation, a vertical milled surface with a wide roughness range has been prepared. A Stylus profilometer has been used to measure the roughness (

Indexed as

capacitance techniqueFEA analysismicro gantryroughness estimation

Identifiers

PMID36296099
PMCPMC9607500

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.