Application of PCA-based hybrid methodologies for parameter optimization of E-jet based micro-fabrication process: a comparative study

Das, Raju; Ball, Amit Kumar; Roy, Shibendu Shekhar

doi:10.1007/s40430-018-1373-4

Cited by 9 publications

(4 citation statements)

References 58 publications

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“…The eigenvalues and eigenvectors were obtained using Equation 9, while the principal components (PCs) were determined using Equation 10. To perform a PCA, several steps need to be followed [26][27][28].…”

Section: Pcamentioning

confidence: 99%

Optimizing Laser Beam Welding Performance Parameters on Nimonic 80A Superalloy: A Study on Experimentation, TGRA, and PCA

Saurabh,

Chand,

Yadav

2024

Soldag. insp.

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This article describes the effect of CO 2 LBW performance parameters for the welded joint of 1.5 mm thin sheet of Nimonic 80A superalloy. Superalloy 80A used in high temperature application as aero-engine components-blade, rings, exhaust gas turbine part, nuclear tube support and automobile valve. The study focused on optimizing the welding process for the welded joints. Here, LP, WS, FD, and shielding GR will be optimised to improve the weld quality of Nimnic 80A material. Two different optimization techniques were used. The first method is SOO, which is based on the S/N ratio. The aim of this method is to find the Single-optimal values of process parameters. The second method employed MOO, combining the Taguchi grey relational analysis (TGRA) with the principal component analysis (PCA) technique. The researchers used these methods in an effort to identify the set of parameters for obtaining improved weld quality. Authors find best setting parameters p3-v3-f3-g1, with the specific parameter values are LP 2400 W, WS 1800 mm/min, FD 18 mm, and GR 10 lpm. The optimized parameters have yield significant improvements in the depth of penetration 6.03%, weld bead 8.74%, Vickers hardness 12.5%, and tensile strength 16.48% by using TGRA coupled with PCA.

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Section: Pcamentioning

confidence: 99%

Optimizing Laser Beam Welding Performance Parameters on Nimonic 80A Superalloy: A Study on Experimentation, TGRA, and PCA

Saurabh,

Chand,

Yadav

2024

Soldag. insp.

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“…Axial depth of cut is reported as the dominant process variable affecting tangential cutting force (49%) and axial cutting force (47%) while radial depth of cut contributed 70% variation in radial force. Application of hybrid optimization methodology employing principal component analysis (PCA) integrated with desirability function analysis (DFA) and grey function analysis (GRA) [19], PSO integrated with ANN [20] and fuzzy logic coupled with Taguchi technique [21] have been attempted. Desirability graph approach coupled with user's preference method is applied by Harmesh et al [22] for multi-response optimization of SR, cutting speed and spark gap in WEDM of Al/SiCp-MMC.…”

Section: Review Of Literaturementioning

confidence: 99%

Fuzzy logic-integrated PSO methodology for parameters optimization in end milling of Al/SiCp MMC

Devarajaiah

Chandrasekaran

2019

J Braz. Soc. Mech. Sci. Eng.

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This paper deals with a novel integrated parametric optimization in end milling of Al-SiC p metal-matrix composites using carbide tool. Fuzzy logic modeling combined with particle swarm optimization (PSO) technique is applied as intelligent optimization methodology to obtain optimal process parameters in end milling process. Fuzzy rules-based surface roughness prediction model is developed with SiC p percentage as one the input parameter is addition to spindle speed, feed and depth of cut. Comparison of fuzzy rule model predictions with confirmation data sets showed 95.44% average prediction accuracy. The effect of process parameters on surface roughness is also studied. Analysis of variance established feed rate as the most significant process variable with 69.93% contribution followed by SiC p (19%) and spindle speed (9.73%), respectively. The integrated PSO optimizer optimizes the process parameters for an objective to minimize the machining time satisfying desired surface roughness to be obtained. A number of problems with different values of desired surface roughness are solved and algorithm converged in less than ten iterations.

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“…In this context, a population-based optimization approach called teaching and learning-based optimization (TLBO) is applied in the present research to study the optimization problem of the EHD process. The application of TLBO for identifying the improved process environment of EHD is absent in traditional research [31,32]. Few case studies have been conducted using past literature data by the researchers [33][34][35].…”

Section: Introductionmentioning

confidence: 99%

An experimental investigation for parametric appraisal of electrohydrodynamic-driven microfabrication approach using teaching and learning-based optimization

Das

Roy

Murmu

2020

J Braz. Soc. Mech. Sci. Eng.

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Electrohydrodynamic (EHD)-based microfabrication process is a novel high-resolution pattern generation technology for micro/nanoscale system fabrication. Achieving tiny droplets during deposition has been a critical issue for the further development of this new emerging technology. It is imperative to identify the proper fabrication parameters to get the desired resolution operation. In the current study, first, an experimental EHD microfabrication setup is developed, and then experiments are carried out to search for an operating condition, which can promote high-resolution droplet generation. The experiments are planned by design of experiment scheme. The influence of the operating control parameters such as nozzle to substrate gap, voltage and the supply rate of the material on deposited droplets diameter is investigated in the current work. Characterization study reveals that nozzle to substrate gap and supply rate have a positive effect on deposition behavior, whereas voltage has a negative association with the droplet resolution. For better control of the EHD process, a causal relationship is developed between process control and performance parameter. A metaheuristic search algorithm named teaching and learning-based optimization (TLBO) is employed to find out the optimal operating environment of the EHD process. The results are compared with the traditional robust parameter design approach, and the authors found that TLBO performs more effectively for resolution improvement in the EHD-driven microfabrication process. Moreover, the sequence in which the control parameters govern the fabrication process is identified and reported.

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Application of PCA-based hybrid methodologies for parameter optimization of E-jet based micro-fabrication process: a comparative study

Cited by 9 publications

References 58 publications

Optimizing Laser Beam Welding Performance Parameters on Nimonic 80A Superalloy: A Study on Experimentation, TGRA, and PCA

Optimizing Laser Beam Welding Performance Parameters on Nimonic 80A Superalloy: A Study on Experimentation, TGRA, and PCA

Fuzzy logic-integrated PSO methodology for parameters optimization in end milling of Al/SiCp MMC

An experimental investigation for parametric appraisal of electrohydrodynamic-driven microfabrication approach using teaching and learning-based optimization

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