Experimental Investigation of Minimum Quantity Lubrication on Tool Wear in Aluminum Alloy 6061-T6 using Different Cutting Tools

The present study focused on the wear performance of AA6061/ SiCp (1, 1.5 and 2 wt. %) of nanocomposites at dry sliding condition. The nanocomposite specimens were fabricated through ultrasonic assisted stir casting technique. The wear experiments were conducted under normal atmospheric conditions using a pin-on-disc apparatus. Three different applied normal loads on nanocomposite pin (10 N, 15 N, and 20 N); at various sliding velocities of (1 m/s, 1.5 m/s, and 2 m/s); and at sliding distances of (1000 m, 2000 m, and 3000 m) were considered. The influences of applied normal load on nanocomposite pin, wt. % of SiCp reinforcement particles, sliding velocity, and sliding distance on both friction coefficient and wear loss were studied. The changes of wear loss and friction coefficient with varying applied normal loads, sliding velocities, and sliding distances were plotted. It was observed that the wear loss increased linearly with increasing sliding distance and sliding velocity. This was due to the increase of oxidation layer on the pin surface. The average friction coefficient at sliding velocity 1 m/s for 1 wt. % of SiCp, 1.5 wt. % of SiCp, and 2 wt. % of SiCp reinforced nanocomposites at sliding distance 3000 m, at 20 N normal loads was 0.29, 0.43, and 0.46, respectively. The average friction coefficient at 2 m/s sliding velocity for the same load and sliding distance was 0.26, 0.27, and 0.28, respectively. The increase of SiCp reinforcement in the matrix increased the friction coefficient due to its cubic crystal structure. The increase of sliding velocity and sliding distances reduced the friction coefficient. The worn surfaces of the samples were examined using SEM and EDX analyses. SEM micrograph analysis of the wear surfaces of the nanocomposites exhibited the abrasion wear and oxidative wear with severe plastic deformation. The shallower scratches, circular grooves, and deeper grooves were identified at different conditions on the worn surfaces.

Section: Introductionmentioning

confidence: 99%

Dry sliding wear behaviour of ultrasonically-processed AA6061/SiCp nanocomposites

Reddy¹,

Krishna²,

Rao³

2017

“…Aluminum alloys are currently used in various sectors because of their higher quality characteristics like low specific gravity, corrosion resistance and recyclability [1][2][3]. Nowadays, their application is still expanding, mostly in the automobile and aerospace industries [4][5][6]. As shown in the study by Fortain and Gadrey [7], the main applications of aluminum products have been in transportation (27%), construction (20%), packaging (16%), electricity supply (10%), machinery and equipment (8%) and also in sectors relating to sustainable products (7%) where extraordinary growth reaching 60 million tons by 2020 has been predicted.…”

Section: Introductionmentioning

confidence: 99%

Effect of Filler on Weld Metal Structure of Aa6061 Aluminum Alloy by Tungsten Inert Gas Welding

Ishak¹,

Noordin²,

Razali³

et al. 2015

Innovative welding technology in joining aluminum alloys in the automobile, aviation, aerospace and marine industries would achieve weight reduction and high specific strength as well as increasing fuel efficiency and reducing environmental pollution. This study presents an appropriate welding filler to join similar AA6061 aluminum alloys using the tungsten inert gas (TIG) process. The TIG welding of AA6061 was butt joined with three different fillers: ER5356 (4.5-6% Mg), ER4043 (4.5-6% Si) and ER4047 (11-13% Si). The experiments were conducted in order to investigate the macrostructure and microstructure of the samples as well as the mechanical properties. The effect of preheating was also investigated. The effects of the different fillers used on the weld joints were analyzed by their visual appearance, microstructures, hardness and strength. It was found that welding by using filler ER5356 produced a finer grain size and the highest strength of 171.53 MPa compared to the weld joints using fillers ER4047 and ER4047 with values of 167.34 MPa and 168.03 MPa, respectively.

“…Only the near-dry machining process, also termed as minimum quantity lubrication (MQL), can offer a near-term solution to the problem [2][3][4]. Minimum quantity lubrication is a technique of sustainable manufacturing that incorporates all the issues related to machining [5,6]. It aims to reduce the hazardous effects of coolants on the atmosphere and to minimize the resource consumption during a product life cycle which includes design, processing, production, packaging, transport, the use of the product and its disposal [7].…”

Section: Introductionmentioning

confidence: 99%

“…In MQL a small amount of lubricant atomized in a compressed air flow is supplied to the cutting zone. Since the cooling capacity of the MQL flow largely depends on the air flow, complete replacement of the flood cooling medium with MQL is still considered complex [5,[32][33][34][35][36] and its application scope is still uncertain. Since a very minute amount of cutting fluid is used in MQL, its heat-carrying capacity and lubrication capability is inadequate [37].…”

Section: Introductionmentioning

confidence: 99%

Parametric optimization of end milling process under minimum quantity lubrication with nanofluid as cutting medium using pareto optimality approach

Najiha¹,

Rahman²,

Kadirgama³

2022

Self Cite

In this paper a genetic algorithm based multi-objective optimization approach is applied in order to predict the optimal machining parameters for the end milling process of aluminium alloy 6061 T6 combined with minimum quantity lubrication (MQL) conditions using waterbased TiO2 nanofluid as cutting fluid. The optimization is carried out employing a parametric model (in terms of input cutting parameters, i.e., cutting speed, feed rate, depth of cut, MQL flow rate and % volume concentration of nanofluid) and exploiting the capabilities of the MOGA-II algorithm applied to the constrained machining problem. The objective functions selected to optimize are: to minimize the surface roughness; to maximize the material removal rate; and to minimize the flank wear of the cutting tool. The output of the optimization includes several alternative optimal solutions, i.e., Pareto frontier, and the best compromised configuration of the cutting parameters is selected subject to weighted preference.