Evidence map›Paper›PMID 42547792›Full record

ArticleScientific reports2026

Performance Optimization of Novel Laser Hybrid Ultrasonic Vibration Assisted Micro Milling for Inconel 718.

Ahmad Waqar Tehami, Muhammad Rizwan Ul Haq, Syed Hussain Imran Jaffery, Muhammad Salman Khan, Shahid Ikramullah Butt, Ghulam Hussain, Muhammad Bilal Khan, Mohammed Alkahtani

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Ahmad Waqar TehamiSchool of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan.
Muhammad Rizwan Ul HaqSchool of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan. muhammad.rizwan@smme.nust.edu.pk.
Syed Hussain Imran JafferySchool of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan.
Muhammad Salman KhanSchool of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan.
Shahid Ikramullah ButtSchool of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan.
Ghulam HussainMechanical Engineering Department, College of Engineering, University of Bahrain, Isa Town, 32038, Kingdom of Bahrain.
Muhammad Bilal KhanDepartment of Civil Engineering, Zhejiang University, Hangzhou, 310058, China.
Mohammed AlkahtaniDepartment of Industrial Engineering, College of Engineering, King Saud University, P.O.Box 800, Riyadh, 11421, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Miniaturization drives advanced manufacturing essential for next-generation systems using superalloys in aerospace, biomedical and microelectronics. Hybrid machining combines distinct processes to harness their individual strengths and overcome limitations. This experimental research explored the machinability of Inconel 718 through novel laser hybrid ultrasonic vibration-assisted micro-milling (L-UVAMM), utilizing fiber laser for preparing slots followed by micro-milling on the corresponding laser-generated pilot slots with uncoated and three different coated tools. Cutting speed, feed, depth of cut, tool coatings and amplitude considered as input variables across four discrete levels to design experiments using Taguchi L-16 orthogonal array to investigate their effect on key responses including surface roughness, tool wear, and burr formation. Analysis of Variance (ANOVA) and Grey Relational Analysis (GRA) identified the most significant parameters and determined the best input combinations. Uncoated tools displayed the least tool wear, TiSiN minimized burr height while TiAlN improved surface roughness and reduced burr width. ANOVA for the regression model revealed the tool type as the most crucial factor influencing responses with a contribution ratio of 45.76%. Response surface method optimized the regression model for optimum conditions, resulted in 43.96%, 27.18%, and 19.65% average reduction of surface roughness, tool wear, and burr formation, respectively.

Indexed as

Burr-formationInconel-718LaserMicro-millingSurface-roughnessTool-wearUltrasonic-assisted

Identifiers

PMID42547792
PMCPMC13433990

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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.