Evidence map›Paper›PMID 36431576›Full record

ArticleMaterials (Basel, Switzerland)2022

Optimization of Selective Laser Melting Parameter for Invar Material by Using JAYA Algorithm: Comparison with TLBO, GA and JAYA.

Hiren Gajera, Faramarz Djavanroodi, Soni Kumari, Kumar Abhishek, Din Bandhu, Kuldeep K Saxena, Mahmoud Ebrahimi, Chander Prakash, Dharam Buddhi

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

9 authors.

Hiren GajeraDepartment of Mechanical Engineering, L D College of Engineering, Ahmedabad 380015, India.ORCID 0000-0001-5183-5436
Faramarz DjavanroodiDepartment of Mechanical Engineering, College of Engineering, Prince Mohammad Bin Fahd University, Al Khobar 31952, Saudi Arabia.ORCID 0000-0002-1526-4688
Soni KumariDepartment of Mechanical Engineering, GLA University, Mathura 281406, India.
Kumar AbhishekDepartment of Mechanical and Aero-Space Engineering, Institute of Infrastructure, Technology, Research and Management (IITRAM), Ahmedabad 380026, India.ORCID 0000-0002-6914-1448
Din BandhuDepartment of Mechanical Engineering, Indian Institute of Information Technology Design and Manufacturing (IIITDM), Kurnool 518008, India.ORCID 0000-0001-9163-353X
Kuldeep K SaxenaDepartment of Mechanical Engineering, GLA University, Mathura 281406, India.ORCID 0000-0003-4064-5113
Mahmoud EbrahimiNational Engineering Research Center of Light Alloy Net Forming and Key State Laboratory of Metal Matrix Composites, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0000-0003-2105-9944
Chander PrakashDivision of Research and Development, Lovely Professional University, Phagwara 144011, India.
Dharam BuddhiDivision of Research & Innovation, Uttaranchal University, Dehradun 248007, India.ORCID 0000-0001-7305-0795

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, the hardness and surface roughness of selective laser-melted parts have been evaluated by considering a wide variety of input parameters. The Invar-36 has been considered a workpiece material that is mainly used in the aerospace industry for making parts as well as widely used in bimetallic thermostats. It is the mechanical properties and metallurgical properties of parts that drive the final product's quality in today's competitive marketplace. The study aims to examine how laser power, scanning speed, and orientation influence fabricated specimens. Using ANOVA, the established models were tested and the parameters were evaluated for their significance in predicting response. In the next step, the fuzzy-based JAYA algorithm has been implemented to determine which parameter is optimal in the proposed study. In addition, the optimal parametric combination obtained by the JAYA algorithm was compared with the optimal parametric combination obtained by TLBO and genetic algorithm (GA) to establish the effectiveness of the JAYA algorithm. Based on the results, an orientation of 90°, 136 KW of laser power, and 650 mm/s scanning speed were found to be the best combination of process parameters for generating the desired hardness and roughness for the Invar-36 material.

Indexed as

ANOVADMLSGAhardnessinvarJAYAsinteringsurface roughnesstaguchiTLBO

Identifiers

PMID36431576
PMCPMC9693503

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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.