S. Thirumalai Kumaran

Machinability of Nickel-Based Superalloy by Abrasive Water Jet Machining

This paper deals with the machinability of nickel-based superalloys using abrasive water jet machining process. The machining studies were carried out with three different parameters such as water jet pressure, traverse speed of jet nozzle, and standoff distance at three different levels. The performances of the process parameters are evaluated by measuring difference in kerf width, kerf wall inclination, and material removal rate (MRR). Further, the surface morphology and material removal mechanisms are analyzed through scanning electron microscope (SEM) images. It is found that water jet pressure is the most influencing factor related to surface morphology and surface quality.

Electrical Discharge Machining of Al(6351)–SiC–B4C Hybrid Composite

Metal matrix composites are found to have many applications in the materials and structural engineering field. In this work, an investigation is carried out to find the influence of process parameters such as pulse current (I), pulse on time (T on), pulse duty factor (τ), and voltage (V) on the machining of Al(6351)—5 wt% silicon carbide (SiC)—5 wt% boron carbide (B4C) hybrid composite through electrical discharge machining. The individual parameters were analyzed with an objective to minimize electrode wear ratio (EWR), surface roughness (SR), and power consumption (PC). The experimental result shows that the output responses were greatly influenced by pulse current, with a contribution of 33.08% to EWR, 76.65% to SR, and 48.08% to PC. The surface characteristics were also examined through scanning electron microscope and the presence of craters and recast layers was observed.

Investigation on the dry sliding friction and wear behavior of AA6351-SiC-B4C hybrid metal matrix composites:

In the present study, the effect of wear test parameters on dry sliding wear behavior of aluminum matrix alloy (AA6351) with 5 wt% silicon carbide and 5 wt% boron carbide-reinforced hybrid metal matrix composites was investigated. Wear performance of the hybrid composites was evaluated over an applied load range of 20–100 N and sliding velocities ranging from 1 to 5 m/s. The experimental results show that the hybrid composites retain the wear resistance properties up to load of 60 N and sliding velocities ranges 1–3 m/s. Metallurgical examinations were also carried out to assess the effect of silicon carbide and boron carbide particles on the wear mechanisms. The enhancement of wear resistance was achieved with the addition of small amount of silicon carbide and boron carbide reinforcement particles with aluminum matrix alloy.

Machining behavior of AA6351–SiC–B4C hybrid composites fabricated by stir casting method

ABSTRACT This study presents an effective approach to assess the machinability of 6351 aluminum alloy matrix, reinforced with 5 wt.% silicon carbide (SiC) and (0, 5, and 10 wt.%) boron carbide (B4C) particles. The turning tests are carried out with a polycrystalline diamond (PCD) tool to identify the effect of the B4C particles addition to the composite, with an objective to improve the material removal rate (MRR) and to reduce the surface roughness (Ra) and power consumption (P). The significant level of each factor, which contributes to affect the output response, is found through analysis of variance (ANOVA). The results show that the inclusion of B4C particles in the hybrid composite significantly affects the machinability, with a contribution to the surface roughness by 7.87% and P by 6.36%. The increase in MRR affects the quality of the material, irrespective of the composites.

Effect of Abrasive Grain Size of the AWJM Performance on AA(6351)-SiC-B4C Hybrid Composite

In this work, Abrasive Water Jet Machining (AWJM) on aluminum based hybrid composite with Silicon Carbide (SiC) and Boron Carbide (B4C) reinforcement particles are investigated. Two different abrasive grain sizes of 80 mesh and 120 mesh are selected to carry out the experiments. The cutting parameters namely pressure, standoff distance (SOD) and traverse speed are assessed in terms of the kerf angle, Material Removal Rate (MRR) and Surface Roughness (Ra). The result shows that the coarse abrasive particle has a favorable effect on the MRR, while the fine grained abrasive particle produced minimum kerf angle and good surface finish.

Electrical discharge machining of Al (6351)-5% SiC-10% B 4 C hybrid composite: a grey relational approach

The goal of the present experimental work is to optimize the electrical discharge machining (EDM) parameters of aluminum alloy (Al 6351) matrix reinforced with 5 wt.% silicon carbide (SiC) and 10 wt.% boron carbide (B4C) particles fabricated through the stir casting route. Multiresponse optimization was carried out through grey relational analysis (GRA) with an objective to minimize the machining characteristics, namely electrode wear ratio (EWR), surface roughness (SR) and power consumption (PC). The optimal combination of input parameters is identified, which shows the significant enhancement in process characteristics. Contributions of each machining parameter to the responses are calculated using analysis of variance (ANOVA). The result shows that the pulse current contributes more (83.94%) to affecting the combined output responses.

Performance Evaluation of Abrasive Water Jet Machining on Banana Fiber Reinforced Polyester Composite

ABSTRACT This work deals with the investigation of Abrasive Water Jet Machining (AWJM) on banana fiber reinforced polyester composite. The composite is prepared with 20 wt. % of fiber through hand layup method followed by compression molding. Experiments are conducted to assess the influence of each input parameters on the output responses namely surface roughness (Ra) and kerf angle. The study is performed by varying the water pressure, traverse speed (TS), and standoff distance (SD). From the experiments, it is observed that the standoff distance contributes more on affecting Ra by 60.63% and kerf angle by 74.80%. The suitable cutting parameters are suggested for achieving quality output and the cut surface morphology is observed through Scanning Electron Microscopic (SEM) images.

Dry sliding wear behavior of SiC and B4C-reinforced AA6351 metal matrix composite produced by stir casting process

In the present study, the influence of Boron Carbide (B4C) particles on the dry sliding wear behavior of aluminum matrix alloy (AA6351) – Silicon Carbide (SiC) composite – produced by the stir casting method is investigated. The wear test is carried out by pin-on-disc apparatus over an applied load range of 20–100 N and sliding velocity ranging from 1 to 5 m/s. The worn surfaces are discussed in detail with the Scanning Electron Microscopic (SEM) image. The experimental results show that the maximum wear rate of 21.91 × 10−3 mm3/m is achieved for the AA-5 wt. % SiC composite at 100 N load and 2 m/s sliding velocity. However, the inclusion of B4C particles on the composite reduced the wear rate significantly. Thus, the increased wt. % of B4C particles in the composite exhibits a good wear resistance behavior at higher load and sliding velocity conditions.

Electrical discharge machining of Al (6351) alloy: role of electrode shape

In this work, an investigation is made in order to identify the influence of machining parameters such as pulse current (I), pulse on time (Ton) and pulse duty factor (τ) on the electrical discharge machining (EDM) of aluminium (6351) alloy. The effect of electrode shape viz. circular and square configuration on the machining characteristics namely electrode wear ratio (EWR), surface roughness (SR) and over cut (OC) were analysed. The experimental results revealed that the circular electrode exhibits lower EWR, better surface finish and minimised OC when compared to the square electrode. The surface characteristics of the aluminium alloy machined by both the electrodes are also examined by using scanning electron microscope (SEM). The mechanism of crater formation and the surface texture of the machined area are also discussed.

Parametric Optimization of AWJM in AA6351-SiC-B4C Hybrid Composite Using Grey Relational Analysis

In the present study, the aluminum based hybrid composite with Silicon Carbide (SiC) and Boron Carbide (B4C) particles are prepared through the stir casting process and subjected to Abrasive Water Jet Machining (AWJM). The pressure, standoff distance and traverse speed are considered as the input process parameters and the output response such as Kerf angle, Material Removal Rate (MRR) and Surface Roughness (Ra) are measured and optimized using Grey Relational Analysis (GRA). The Analysis of Variance (ANOVA) and the F-test are performed to understand the contribution and the significant level of importance of each input parameter over the output response. The experimental result shows that the traverse speed and the standoff distance contributed more on affecting the performance, with a contribution of 62.14% and 18.43% respectively.