Analysis and optimization of laser drilling process during machining of AISI 303 material using grey relational analysis approach

Reddy, Venkatarami; Keerthi, Thota; Nishkala, T.; Yadav, Gunjan

doi:10.1007/s42452-021-04337-6

Cited by 15 publications

(4 citation statements)

References 35 publications

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“…Where γ ( x 0 i , x ij ) is the GRC; ζ is the resolution coefficient, with a range of ζ ∈ [0,1], the ζ taken as 0.5 to make the experimental results have better stability (Chengal Reddy et al , 2021); Δ ij , Δ min and Δ max are the absolute value of the difference between x 0j and x ij , the minimum value of Δ ij and the maximum value of Δ ij , respectively.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

Surface quality prediction and lapping process optimisation on the fixed-abrasive lapping plate of sapphire wafers

Yan

Wang²,

Liu³

2022

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Purpose Lapping is a vital flattening process to improve the quality of processed semiconductor wafers such as single-crystal sapphire wafers. This study aims to optimise the lapping process of the fixed-abrasive lapping plate of sapphire wafers with good overall performance [i.e. high material removal rate (MRR), small surface roughness (Ra) of the wafers after lapping and small lapping plate wear ratio (η)]. Design/methodology/approach The influence of process parameters such as lapping time, abrasive size, abrasive concentration, lapping pressure and lapping speed on MRR, Ra and η of lapping-processed sapphire wafers was studied, and the results were combined with experimental data to establish a regression model. The multi-evaluation index optimisation problem was transformed into a single-index optimisation problem via an entropy method and the grey relational analysis (GRA) to comprehensively evaluate the performance of each parameter. Findings The results revealed that lapping time, abrasive size, abrasive concentration, lapping pressure and lapping speed had different influence degrees on MRR, Ra and η. Among these parameters, lapping time, lapping speed and abrasive size had the most significant effects on MRR, Ra and η, and the established regression equations predicted the response values of MRR, Ra and η to be 99.56%, 99.51% and 93.88% and the relative errors between the predicted and actual measured values were <12%, respectively. With increased lapping time, MRR, Ra and η gradually decreased. With increased abrasive size, MRR increased nearly linearly, whereas Ra and η initially decreased but subsequently increased. With an increase in abrasive concentration, MRR, Ra and η initially increased but subsequently decreased. With increased lapping pressure, MRR and η increased nearly linearly and continuously, whereas Ra decreased nearly linearly and continuously. With increased lapping speed, Ra initially decreased sharply but subsequently increased gradually, whereas η initially increased sharply but subsequently decreased gradually; however, the change in MRR was not significant. Comparing the optimised results obtained via the analysis of influence law, the parameters optimised via the entropy method and GRA were used to obtain sapphire wafers lapping with an MRR of 4.26 µm/min, Ra of 0.141 µm and η of 25.08, and the lapping effect was significantly improved. Originality/value Therefore, GRA can provide new ideas for ultra-precision processing and process optimisation of semiconductor materials such as sapphire wafers.

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Section: Experimental Results and Analysismentioning

confidence: 99%

Surface quality prediction and lapping process optimisation on the fixed-abrasive lapping plate of sapphire wafers

Yan

Wang²,

Liu³

2022

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“…Since the values are normalized, Δ min and Δ max are always equal to 0 and 1, respectively. The GRG is estimated by taking the mean value of GRC for each and every trial [16].…”

Section: Methodsmentioning

confidence: 99%

Analysis of MRR, Thrust Force, and Torque in Drilling Al/BN/Al2O3 Composites using Hybrid Grey–Taguchi Technique

Babu

Dhanasekaran

Parthiban

et al. 2023

Journal of Nanomaterials

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The demand for hybrid composite materials has been expanding globally in all kinds of mechanical industries. Drilling is one of the basic operations required in manufacturing of various components and choosing optimum parameters of drilling is vital for getting good quality holes. The main objective of our work is to determine the ideal parameters of drilling and tool coatings required to minimize the thrust force and torque in drilling and to maximize the material removal rate (MRR) using Grey–Taguchi technique. Hybrid composite specimen made by reinforcing Al7075 alloy with 4% of aluminum oxide and 2% of boron nitride in stir casting process and drilling was carried out in a sequence at different drilling feed rates (40, 80, and 120 mm/min) and spindle speeds (1,200, 2,400, and 3,600 rpm) in a vertical machining center attached with drill tool dynamometer, using twist drills of diameter 5 mm and point angle 118° made of uncoated carbide, diamond-like carbon (DLC)-coated carbide and high carbon (HC)-coated carbide. The recorded thrust force and torque from the dynamometer and the computed MRRs during each drilling operation are tabulated as per Taguchi’s L27 orthogonal array and the results are analyzed using hybrid Grey–Taguchi technique. In our analysis, the optimum thrust force of 62.12 N and torque of 0.766 Nm were obtained when using a DLC-coated tool at a maximum speed of 3,600 rpm and minimum feed rate of 40 mm/min. An optimum MRR of 178.79 mm3/s was obtained while using DLC coated at a maximum speed of 3,600 rpm and a maximum feed rate of 120 mm/min.

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“…where γ represents the predicted value of the Grey Relational Grade of the optimized set of process parameters, γ m is the mean value of the Grey Relational Grade of all the tested parameters, o is the number of the process parameters involved in the optimization process, and γ i is the mean Grey Relational Grade of each process parameter at the optimal level [32,33].…”

Section: The Multiparametric Optimization Algorithmmentioning

confidence: 99%

Multi-Attribute Decision Making: Parametric Optimization and Modeling of the FDM Manufacturing Process Using PLA/Wood Biocomposites

Morvayová,

Contuzzi,

Fabbiano

et al. 2024

Materials

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The low carbon footprint, biodegradability, interesting mechanical properties, and relatively low price are considered some of the reasons for the increased interest in polylactic acid-based (PLA-based) filaments supplied with natural fillers. However, it is essential to recognize that incorporating natural fillers into virgin PLA significantly impacts the printability of the resulting blends. The complex inter-relationship between process, structure, and properties in the context of fused deposition modeling (FDM)-manufactured biocomposites is still not fully understood, which thus often results in decreased reliability of this technology in the context of biocomposites, decreased accuracy, and the increased presence of defects in the manufactured biocomposite samples. In light of these considerations, this study aims to identify the optimal processing parameters for the FDM manufacturing process involving wood-filled PLA biocomposites. This study presents an optimization approach consisting of Grey Relational Analysis in conjunction with the Taguchi orthogonal array. The optimization process has identified the combination of a scanning speed of 70 mm/s, a layer height of 0.1 mm, and a printing temperature of 220 °C as the most optimal, resulting in the highly satisfactory combination of good dimensional accuracy (Dx = 20.115 mm, Dy = 20.556 mm, and Dz = 20.220 mm) and low presence of voids (1.673%). The experimentally determined Grey Relational Grade of the specimen manufactured with the optimized set of process parameters (0.782) was in good agreement with the predicted value (0. 754), substantiating the validity of the optimization process. Additionally, the research compared the efficacy of optimization between the integrated multiparametric method and the conventional monoparametric strategy. The multiparametric method, which combines Grey Relational Analysis with the Taguchi orthogonal array, exhibited superior performance. Although the monoparametric optimization strategy yielded specimens with favorable values for the targeted properties, the analysis of the remaining characteristics uncovered unsatisfactory results. This highlights the potential drawbacks of relying on a singular optimization approach.

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Analysis and optimization of laser drilling process during machining of AISI 303 material using grey relational analysis approach

Cited by 15 publications

References 35 publications

Surface quality prediction and lapping process optimisation on the fixed-abrasive lapping plate of sapphire wafers

Surface quality prediction and lapping process optimisation on the fixed-abrasive lapping plate of sapphire wafers

Analysis of MRR, Thrust Force, and Torque in Drilling Al/BN/Al2O3 Composites using Hybrid Grey–Taguchi Technique

Multi-Attribute Decision Making: Parametric Optimization and Modeling of the FDM Manufacturing Process Using PLA/Wood Biocomposites

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