Optimization of Process Variables in the Drilling of LM6/B4C Composites through Grey Relational Analysis

Rubi, C. Sarala; Prakash, J. Udaya; Čep, Róbert; Elangovan, Muniyandy

doi:10.3390/ma15144860

Cited by 13 publications

(8 citation statements)

References 50 publications

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“…2 Values within the parentheses are the experimental values reported in [40]. 3 Negative values indicate that the current results are poorer than [40]. 1 For unbiased comparison, Fa, Mc and Ra values by the current metamodels are used.…”

Section: Discussionmentioning

confidence: 99%

“…2 Values within the parentheses are the experimental values reported in [43]. 3 Negative values indicate that the current results are poorer than [43]. A1 Experimental data for case study 1 [40] Exp.…”

Section: Discussionmentioning

confidence: 99%

“…Basavarajappa et al [2] identified that during drilling of MMCs, the major factor influencing drilling force had been feed rate rather than cutting speed. It is also reported in the literature that surface roughness of the drilled holes on MMCs would increase with increase in feed rate and decrease with increase in cutting speed [3,4]. But, many other researchers are against these observations [5,6].…”

Section: Introductionmentioning

confidence: 99%

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A novel MOALO-MODA ensemble approach for multi-objective optimization of machining parameters for metal matrix composites

Kalita

Kumar

Chakraborty

2023

Multiscale and Multidiscip. Model. Exp. and Des.

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Machining of metal matrix composites (MMCs) has now become an essential task in shaping them to their final usable forms for various industrial applications. These machining operations may range from drilling of simple through holes to cutting and shaping the composites into complex shapes.Determination of the optimal process parameters during their machining presents a combinatorial optimization problem, which may turn out to be more complex due to involvement of various material dependent parameters of the MMCs, like particle size, reinforcement percentage etc. The importance of optimization increases manifold due to conflicting settings of different process parameters for attaining the desired quality characteristics. In this paper, two nature-inspired optimization algorithms, i.e. multi-objective antlion optimization (MOALO) and multi-objective dragonfly algorithm (MODA) are applied for multi-objective optimization of various process parameters during machining of MMCs. To mitigate uncertainties in global optimality of the predicted Pareto optimal fronts arising due to stochastic nature of the metaheuristics, an ensemble approach integrating MOALO and MODA techniques is proposed here. It is demonstrated with the help of two case studies that MOALO-MODA ensemble is far superior to its individual counterparts and thus, can be employed for development of robust and reliable Pareto optimal fronts.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A novel MOALO-MODA ensemble approach for multi-objective optimization of machining parameters for metal matrix composites

Kalita

Kumar

Chakraborty

2023

Multiscale and Multidiscip. Model. Exp. and Des.

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“…The feed rate (F), the spindle speed (S), the drill material (D), and the reinforcing percentage (R) were determined. Finally, the predicted GRG was 0.846, whereas the experimental GRG was 0.865, with a 2.2% error indicating that the optimization process was valid [19].…”

Section: Introductionmentioning

confidence: 92%

“…C. Sarala Rubi et al [19] investigated the effects of machining parameters during the drilling of LM 6/B4C composite materials. The optimization process aimed to attain the lowest thrust force (TF), surface roughness (SR), and burr height (BH).…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of Nd: YAG Laser Drilling of Optical-Grade Acrylic Plate Using Taguchi-Based Grey Relational Analysis

Tsai

2022

Materials

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This study proposed an effective method for optimizing laser drilling processing (LDP) by using grey relational analysis (GRA) for multiple performance requirements. First, we developed a system using a Quantel Brilliant Neodymium-doped Yttrium Aluminum Garnet (Nd: YAG) laser with a pulse width of 5–6 ns and F-theta lenses to deliver a focused laser beam with a diameter of 0.2 mm. The developed system was first employed to drill holes in a 3-mm-thick optical-grade acrylic polymethyl methacrylate (PMMA) plate on a safe window with a high optical density and a grade of OD 7+ @ 950~1085 nm. To avoid errors in the experimental data due to unstable power, a laser power (energy) meter was used to measure the energy stability of the Quantel Brilliant Pulse Laser. Given the stability of 5.6%, this is an effective method for LDP. Four control factors were investigated, including laser pulse energy, repetition rate, focusing position offset, and drilling time. Then, nine experiments were performed using the Taguchi method with orthogonal arrays in L9 (34). The experimental results with multiple quality characteristics were measured and used to optimize the control factors by using GRA with equal weighting of the four qualities (roundness, Hillock ratio, taper, and HAZ). The results show that A1B3C1D1 is the optimal combination of the control factors, and the maximal variation of 0.406 is obtained from the control factor B (focusing position offset) which has the greatest contribution to the drilling time. We then performed confirmation experiment and obtained a better result from the combination of the control factors, A1B3C1D1. GRA helps us determine the best laser drilling parameters to meet the desired multiple drilling qualities.

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ANOVA analysis for estimating the accuracy and surface roughness of precisely drilled holes of steel 42CrMo4 QT

Řehoř

Fulemová

Kutlwašer

et al. 2023

Int J Adv Manuf Technol

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The presented publication is focused on increasing the productivity and efficiency of machine production of precision holes. Considerable attention was paid to the influence of the pre-preparation and drilling technology on the quality of the reamed hole. The material selected for machining was chromium-molybdenum steel 42CrMo4 QT. The cluster analysis is implemented to evaluate the experimental results obtained by measuring the cylindricity and surface roughness of the drilled and reamed holes. The factor of hole pre-preparation technology was selected in two quality levels, and the factor of drilling technology in four quality levels. The constant factors were carefully controlled during the experiment, i.e., other possible influences were excluded or minimised. Under constant cutting conditions, the experiment of the subject machining process was carried out. The cutting process parameters investigated were the cylindricity and the roughness of the machined surface Ra. The novelty and contribution of this research lie in confirming the assumption that drilling technology influences hole quality primarily, whereas hole pre-preparation technology has a secondary effect.

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Optimization of Process Variables in the Drilling of LM6/B4C Composites through Grey Relational Analysis

Cited by 13 publications

References 50 publications

A novel MOALO-MODA ensemble approach for multi-objective optimization of machining parameters for metal matrix composites

A novel MOALO-MODA ensemble approach for multi-objective optimization of machining parameters for metal matrix composites

Multi-Objective Optimization of Nd: YAG Laser Drilling of Optical-Grade Acrylic Plate Using Taguchi-Based Grey Relational Analysis

ANOVA analysis for estimating the accuracy and surface roughness of precisely drilled holes of steel 42CrMo4 QT

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