Evidence map›Paper›PMID 36614680›Full record

ArticleMaterials (Basel, Switzerland)2022

Experimental and RSM-Based Process-Parameters Optimisation for Turning Operation of EN36B Steel.

Ramesh Kumar, Ashwani Kumar, Laxmi Kant, Arbind Prasad, Sandeep Bhoi, Chandan Swaroop Meena, Varun Pratap Singh, Aritra Ghosh

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Materials (Basel, Switzerland), 2022. 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

8 authors.

Ramesh KumarDepartment of Mechanical Engineering, Saharsa College of Engineering, Saharsa 852201, Bihar, India.
Ashwani KumarTechnical Education Department Uttar Pradesh Kanpur, Kanpur 208024, Uttar Pradesh, India.ORCID 0000-0003-4099-935X
Laxmi KantDepartment of Mechanical Engineering, Government Engineering College Bhojpur, Patna 800024, Bihar, India.
Arbind PrasadDepartment of Mechanical Engineering, Katihar Engineering College (under Department of Science & Technology, Government of Bihar), Katihar 854109, Bihar, India.ORCID 0000-0002-2604-113X
Sandeep BhoiDepartment of Mechanical Engineering, Parala Maharaja Engineering College, Berhampur 761003, Odisha, India.
Chandan Swaroop MeenaCSIR-Central Building Research Institute, Roorkee 247667, Uttarakhand, India.ORCID 0000-0002-3274-6275
Varun Pratap SinghDepartment of Mechanical Engineering, School of Engineering, University of Petroleum and Energy Studies, Dehradun 248007, Uttarakhand, India.ORCID 0000-0002-2148-5604
Aritra GhoshFaculty of Environment, Science and Economy (ESE), Renewable Energy, Electric and Electronic Engineering, University of Exeter, Penryn, Cornwall TR10 9FE, UK.ORCID 0000-0001-9409-7592

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The main objective of this article is to perform the turning operation on an EN36B steel work-billet with a tungsten carbide tool, to study the optimal cutting parameters and carry out an analysis of flank-wear. Experimental and simulation-based research methodology was opted in this study. Experimental results were obtained from the lab setup, and optimisation of parameters was performed using RSM (response surface methodology). Using RSM, cutting-tool flank-wear was optimised, and the cutting parameters which affect the flank wear were determined. In results main effect plot, contour plot, the surface plot for flank-wear and forces (Fx, Fy and Fz) were successfully obtained. It was concluded that tool flank-wear is affected by depth of cut, and that flank-wear generally increases linearly with increasing cutting-speed, depth of cut and feed-rate. To validate the obtained results, predicated and measured values were plotted and were in very close agreement, having an accuracy level of 96.33% to 98.92%.

Indexed as

cutting-tool wearEN36B steeloptimisationprocess parametersresponse-surface methodturning operation

Identifiers

PMID36614680
PMCPMC9822334

What OpenQuestion holds

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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.