Advances in Manufacturing ›› 2024, Vol. 12 ›› Issue (4): 810-831.doi: 10.1007/s40436-024-00484-2
Tuhin Kar, Swarup S. Deshmukh, Arjyajyoti Goswami
Received:2023-06-21
Revised:2023-09-20
Online:2024-12-06
Published:2024-12-06
Contact:
Arjyajyoti Goswami,E-mail:agoswami.me@nitdgp.ac.in
E-mail:agoswami.me@nitdgp.ac.in
Tuhin Kar, Swarup S. Deshmukh, Arjyajyoti Goswami. Fabrication of micro holes using low power fiber laser: surface morphology, modeling and soft-computing based optimization[J]. Advances in Manufacturing, 2024, 12(4): 810-831.
| [1] Sahu AK, Jha S (2020) Microchannel fabrication and metallurgical characterization on titanium by nanosecond fiber laser micromilling. Mater Manuf Process 35:279-290 [2] Kar T, Goswami A (2022) Mathematical modeling approaches and new development in laser micro machining process: a review. Lasers Manuf Mater Process 9:532-568 [3] Deshmukh SS, Goswami A (2022) Microlens array through induction-aided hot embossing: fabrication, optimization, and characterization. Mater Manuf Process 37:1540-1554 [4] Deng D, Xie Y, Chen L et al (2019) Experimental investigation on laser micromilling of SiC microchannels. Int J Adv Manuf Tech 101:9-21 [5] Al Siyabi I, Khanna S, Sundaram S et al (2018) Experimental and numerical thermal analysis of multi-layered microchannel heat sink for concentrating photovoltaic application. Energies 12:122. https://doi.org/10.3390/en12010122 [6] Zhang S, Wei Q, Cheng L et al (2014) Effects of scan line spacing on pore characteristics and mechanical properties of porous Ti6Al4V implants fabricated by selective laser melting. Mater Des 63:185-193 [7] Anjum A, Shaikh AA, Tiwari N (2023) Comparative assessment of the developed algorithm with the soft computing algorithm for the laser machined depth. Infrared Phys Technol 129:104545. https://doi.org/10.1016/j.infrared.2023.104545 [8] Chatterjee S, Mahapatra SS, Bharadwaj V et al (2021) Prediction of quality characteristics of laser drilled holes using artificial intelligence techniques. Eng Comput 37:1181-1204 [9] Sibalija TV, Petronic SZ, Majstorovic VD et al (2011) Multi-response design of Nd:YAG laser drilling of Ni-based superalloy sheets using Taguchi’s quality loss function, multivariate statistical methods and artificial intelligence. Int J Adv Manuf Tech 54:537-552 [10] Moustafa EB, Elsheikh A (2023) Predicting characteristics of dissimilar laser welded polymeric joints using a multi-layer perceptrons model coupled with archimedes optimizer. Polymers (Basel) 15:233. https://doi.org/10.3390/polym15010233 [11] Zhou H, Wu C, Tang D et al (2021) Tribological performance of gradient Ag-multilayer graphene/TC4 alloy self-lubricating composites prepared by laser additive manufacturing. Tribol T 64:819-829 [12] Parmar V, Kumar A, Prakash GV et al (2019) Investigation, modelling and validation of material separation mechanism during fiber laser machining of medical grade titanium alloy Ti6Al4V and stainless steel SS316L. Mech Mater 137:103125. https://doi.org/10.1016/j.mechmat.2019.103125 [13] Liu C, Zhang X, Gao L et al (2021) Study on damage characteristics and ablation mechanism in fiber laser trepan drilling of 2.5D Cf/SiC composites. Int J Adv Manuf Tech 117:3647-3660 [14] Saini SK, Dubey AK, Upadhyay BN et al (2018) Study of hole characteristics in laser trepan drilling of ZTA. Opt Laser Technol 103:330-339 [15] Kar T, Deshmukh SS, Goswami A (2022) Investigation of fiber laser micro-channel depth on silicon wafer. Mater Today Proc 60:2105-2110 [16] Abdo BMA, El-Tamimi AM, Anwar S et al (2018) Experimental investigation and multi-objective optimization of Nd: YAG laser micro-channeling process of zirconia dental ceramic. Int J Adv Manuf Tech 98:2213-2230 [17] Elsheikh AH, Shehabeldeen TA, Zhou J et al (2021) Prediction of laser cutting parameters for polymethylmethacrylate sheets using random vector functional link network integrated with equilibrium optimizer. J Intell Manuf 32:1377-1388 [18] Muthuramalingam T, Akash R, Krishnan S et al (2021) Surface quality measures analysis and optimization on machining titanium alloy using CO2 based laser beam drilling process. J Manuf Process 62:1-6 [19] Asghari M, Mollabashi M, Razi S (2020) The role of the femtosecond laser induced nano/micro structures on the optical features of the steel surface; experimental polarimetry study. Surf Topogr 8:025024. https://doi.org/10.1088/2051-672X/ab8d85 [20] Moradi M, Mohazabpak A (2018) Statistical modelling and optimization of laser percussion microdrilling of Inconel 718 sheet using response surface methodology (RSM). Laser Eng 39:313-331 [21] Khoshaim AB, Elsheikh AH, Moustafa EB et al (2021) Experimental investigation on laser cutting of PMMA sheets: effects of process factors on kerf characteristics. J Mater Res Technol 11:235-246 [22] Najjar IMR, Sadoun AM, Abd Elaziz M et al (2022) Predicting kerf quality characteristics in laser cutting of basalt fibers reinforced polymer composites using neural network and chimp optimization. Alex Eng J 61:11005-11018 [23] Elsheikh AH, Muthuramalingam T, Abd Elaziz M et al (2022) Minimization of fume emissions in laser cutting of polyvinyl chloride sheets using genetic algorithm. Int J Environ Sci Tech 19:6331-6344 [24] Elsheikh AH, Shanmugan S, Muthuramalingam T et al (2021) Modeling of the transient temperature field during laser heating. Lasers Manuf Mater Process 8:97-112 [25] Sharma P, Chakradhar D, Narendranath S (2021) Measurement of WEDM performance characteristics of aero-engine alloy using RSM-based TLBO algorithm. Measurement 179:109483. https://doi.org/10.1016/j.measurement.2021.109483 [26] Li B, Tian X, Zhang M (2020) Modeling and multi-objective optimization of cutting parameters in the high-speed milling using RSM and improved TLBO algorithm. Int J Adv Manuf Tech 111:2323-2335 [27] Rao RV, Savsani VJ, Vakharia DP (2011) Teaching-learning-based optimization: a novel method for constrained mechanical design optimization problems. Comput Aided Design 43:303-315 [28] Dixit SR, Das SR, Dhupal D (2019) Parametric optimization of Nd:YAG laser microgrooving on aluminum oxide using integrated RSM-ANN-GA approach. J Ind Eng Int 15:333-349 [29] Parthiban K, Duraiselvam M, Manivannan R (2018) TOPSIS based parametric optimization of laser micro-drilling of TBC coated nickel based superalloy. Opt Laser Technol 102:32-39 [30] Gautam GD, Mishra DR (2019) Dimensional accuracy improvement by parametric optimization in pulsed Nd:YAG laser cutting of Kevlar-29/basalt fiber-reinforced hybrid composites. J Braz Soc Mech Sc 41:284. https://doi.org/10.1007/s40430-019-1783-y [31] Gopinath C, Lakshmanan P, Palani S (2022) Fiber laser microcutting on duplex steel: parameter optimization by TOPSIS. Mater Manuf Process 37:985-994 [32] Sanuf SM, Sreejith NK, Kumar RD et al (2021) Parametric optimization of hole geometry in laser drilled Inconel 825 by grey based response surface methodology. Mater Today Proc 47(15):5410-5415 [33] Farasati R, Ebrahimzadeh P, Fathi J et al (2019) Optimization of laser micromachining of Ti-6Al-4V. Int J Lightweight Mater Manuf 2(4):305-317 [34] Alsoruji G, Muthuramalingam T, Moustafa EB et al (2022) Investigation and TGRA based optimization of laser beam drilling process during machining of nickel Inconel 718 alloy. J Mater Res Technol 18:720-730 [35] Kar T, Deshmukh SS, Datta S et al (2023) An experimental study of low power fiber laser micro drilling of aluminium 6061 alloy. Mater Today Proc 82:96-102. https://doi.org/10.1016/j.matpr.2022.11.483 [36] Kar T, Mandal NK, Singh NK (2020) Multi-response optimization and surface texture characterization for CNC milling of Inconel 718 alloy. Arab J Sci Eng 45:1265-1277 |
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