Optimization of drilling processes of aluminium metal matrix composites using the robust ordinal priority approach

Chakraborty, Santonab; Raut, Rakesh D.; Rofin, T. M.; Chakraborty, Shankar

doi:10.1016/j.dajour.2023.100258

Cited by 7 publications

(4 citation statements)

References 28 publications

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“…Average surface roughness (Ra), cutting force, and torque are compromised in the first case when drilling parameters are combined as cutting speed = 87.96 mm min −1 , feed rate = 0.050 mm min −1 , and point angle = 140. The most desired values of thrust force, Ra, and burr height, on the other hand, can be attained in the second case at an ideal parametric intermix of spindle speed = 2000 rpm, feed rate = 0.2 mm rev −1 , Al2219 work material, and carbide drill bit [31]. Using a carbide cutter and a variety of machining parameter combinations, the MMC has been machined.…”

Section: Introductionmentioning

confidence: 99%

Investigation on the machinability of Biochar reinforced AA5083 Metal Matrix composites fabricated by stir casting technique

Praveen,

Raja,

Jannet

et al. 2023

Eng. Res. Express

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Over the past two decades, there has been a significant rise in the demand for Aluminum Metal Matrix Composites (AAMCs) due to their notable advantages such as lightweight properties, increased strength, and enhanced hardness. In this study, three distinct AAMC samples based on Al5083 alloy, each varying in reinforcement levels at 4%, 8%, and 12% by weight were used. These composites were produced through a stir-casting process. The biochar used in our research was obtained through a pyrolysis process, adding an environmentally friendly and sustainable aspect to the composite materials. In the machining aspect of the study, A systematic L27 Taguchi Design of Experiment approach was used to investigate the influence of input parameters, namely cutting speed, feed rate, depth of cut, and weight percentage of reinforcement material, on the machining process. Further regression models were developed to gain insights into the relationships between these parameters and the resulting surface roughness. Turning operations at a cutting speed of 1050 rpm, a feed rate of 60 mm, and a depth of cut of 0.75 mm were idle for superior surface roughness and to assess the impact of the reinforcement material on the machined surface.

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Section: Introductionmentioning

confidence: 99%

Investigation on the machinability of Biochar reinforced AA5083 Metal Matrix composites fabricated by stir casting technique

Praveen,

Raja,

Jannet

et al. 2023

Eng. Res. Express

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“…Stir casting produces outstanding characteristics in Al-Si 3 N 4 with regulated process conditions, and its low material density of 3.3 g/cm 3 and heat conductivity of 170-230 W/mk make it excellent for applications where weight is an issue [3,8]. The presence of agglomerated reinforcing components in the matrix causes a non-uniform metallurgical structure, which leads to poor machinability of Al-MMCs during drilling operations, resulting in a shorter tool life, poor surface integrity, higher energy consumption, increased cutting force and so on [9]. Due to the poor quality of the hole created during drilling, mechanical assemblies are susceptible to failure over time.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Process Parameters on Quality Characteristics in the Drilling of Aluminium–Metal Matrix Composites

Vinay,

Prakash,

Gowda

et al. 2023

RAiSE-2023

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“…To explore the concept of multiple attributes decision-making, researchers often employ various techniques, including the Analytic Hierarchy Process (AHP) (11) , data envelopment analysis (DEA), and grey relational analysis (GRA) (12) . Santonab Chakraborty proposed application of a newly developed multi-criteria decision-making tool, in the form of ordinal priority approach (OPA), for solving two parametric optimization problems for drilling operations of Al-MMCs (13) . One of the prominent techniques utilized in situations where information is incomplete and uncertain is grey relational analysis (GRA), which was introduced by Deng in 1989 (14) .…”

Section: Introductionmentioning

confidence: 99%

GRA & DFA Approach for Optimum Material Selection of Aluminium Metal Matrix Composites: A Comparative Study

Bai,

Kumar

2023

IJST

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Objective: To draw the best combination of material parameters which gives optimized tensile strength, hardness and density properties of the aluminium metal matrix composite. Methods: In this study, three parameters (i.e., base material: Al5083, Al6082 and Al7075, reinforcement material: Fly-ash, SiC, and Al 2 O 3 , and percent of reinforcement material: 2.5%, 5% and 7.5%) were chosen, each with three levels, for the fabrication of AMMC samples in accordance with the Taguchi experimental design L 9 in order to evaluate the tensile strength, hardness and density properties. With the considered set of material combinations, the AMMC samples are fabricated by using stir casting process. Findings: The optimum material combinations are chosen to get optimized properties of AMMC samples using GRA &DFA approach. Since, grey relational analysis is one of the foremost techniques applied when the nature of information is incomplete and uncertain. The experimental results are analyzed using GRA & DFA and drawn the optimum combination of material parameter such as Al6082 (base material), SiC (reinforcement material) and 7.5% (per cent of reinforcement material) with GRA and Al6082 (base material), SiC (reinforcement material) and 5% (per cent of reinforcement material) with DFA to get optimized properties of AMMC sample. It also found that the confirmation experiment results are adequate. Novelty: The use of flyash reinforcement as secondary reinforcement has widely increased due to their low cost and easily available as waste in thermal power plants. From the experimental results, it is observed that the tensile strength, hardness and density properties of aluminium alloy samples are improved due to the addition of reinforcement materials using stir casting process.

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Optimization of drilling processes of aluminium metal matrix composites using the robust ordinal priority approach

Cited by 7 publications

References 28 publications

Investigation on the machinability of Biochar reinforced AA5083 Metal Matrix composites fabricated by stir casting technique

Investigation on the machinability of Biochar reinforced AA5083 Metal Matrix composites fabricated by stir casting technique

The Effect of Process Parameters on Quality Characteristics in the Drilling of Aluminium–Metal Matrix Composites

GRA & DFA Approach for Optimum Material Selection of Aluminium Metal Matrix Composites: A Comparative Study

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