Machining silicon carbide (SiC) is challenging due to its brittle and maximum tensile nature. Lapping or laser beam are done with a high cost of manufacturing and low material removal rates. Water ...abrasive jet cutting is a promising candidate since the machining temperatures and processing force of ceramics are extremely low. Investigation into the abrasive water jet machining of silicon carbide is carried out in the present work.The variations in traverse speed while abrasive water jet cutting of silicon carbide and its effect on the surface roughness and kerf characteristics are studied. Silicon Carbide abrasive material is used as garnet consisting of 80 mesh. The surface roughness was calculated along with the depth of the cut made during the processing.The outcomes demonstrated that the traverse speed is more effective upon the surface roughness and is an important factor that damages the top kerf width and the kerf taper angle.Based on the hardness and thickness of the SiC plate, the taper angle is high, and for a feed rate of 10 mm/min, the surface roughness is low. Less thickness of the SiC plate could have a lower taper angle than with high thickness. The erosive force is provided by abrasive material along with the jet stream.Water abrasive fine jet could effectively machinate silicon carbide ceramic material with a better surface finish accurately. Suitable surface roughness with higher productivity can be attained with medium traverse speed.The effect of process parameters on kerf taper angle and top kerf width in the abrasive water jet machining of silicon carbide is explored, considering surface roughness as an important output parameter.
The present article focuses on mechanism of delamination and kerf geometry in abrasive water jet machining of carbon epoxy composite. In the present study, four process parameters of abrasive water ...jet machining namely hydraulic pressure, traverse rate, stand-off distance, and abrasive mass flow rate are considered. The experiments are performed on the basis of response surface methodology as a statistical design of experiment approach. Delamination in machined samples is observed by using scanning electron microscope. Analysis of variance is performed in order to investigate the influence of process parameters on delamination, kerf taper ratio, and kerf top width. It is found that delamination decreases with increase in pressure and abrasive mass flow rate and decrease in stand-off distance and traverse rate. Kerf taper ratio decreases with increase in pressure and decrease in traverse rate and stand-off distance. Kerf top width decreases with decrease in stand-off distance and increase in traverse rate. Based on analysis, mathematical models are developed to predict the maximum delamination length, kerf taper ratio, and kerf top width. Further, a multi-response optimization is performed on the basis of desirability function to minimize delamination, kerf taper ratio, and kerf top width.
Hole making is an important phase in composite machining as structural applications of composites require assemblage. To do so, abrasive waterjet machining (AWM) is recommended by several fabricators ...and researchers. The quality of the holes produced in composites severely affects the durability of assembled structures. Hence, exploring this aspect is important. In this context, the current study investigates the influence of the AWM variables on GFRP composites. Here, cutting speed (V
c
), and abrasive flow rate (Q
ab
) are selected as input variables whereas the output attributes are the material removal rate (MRR), surface roughness (R
a
), roundness (R
o
), and cylindricity (C
y
). Initially, mathematical models (objective functions) are derived using statistics of nonlinear regression for correlating the aforementioned variables and output attributes. In the next phase, the study utilizes recently developed Rao algorithms i.e. Rao 1, Rao 2, and Rao 3 to determine the ideal machining condition as V
c
= 100 cm/min, and Q
ab
= 300 gm/min. The results were also compared with the JAYA and TLBO approaches in order to show the effectiveness of the proposed methodology and it was observed that exploration of Rao 1, Rao 2, and Rao 3 algorithms appears more fruitful in terms of computational time and effort.
This study applied evolutionary optimization techniques and neural networks to predict optimum machining parameters of Abrasive Water Jet Machining (AWJM) for machining Glass-Carbon Fiber Reinforced ...Composite (GCFRC) materials. Several researchers have employed different optimization techniques; however, evolving computational capabilities further open avenues to optimize such parameters. Five evolutionary techniques, namely Artificial Neural Network (ANN), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), and Nonlinear Least Square Error (LSE), were applied to minimize surface roughness (Ra) and maximize kerf width (Kw) and material removal rate (MRR). The output performance parameters (Ra, Kw, and MRR) were formulated as a linear mathematical function of machining parameters: tool feed rate (TFR), cutting speed rate (CSR), and stand-off distance (SOD). Though this study solves linear optimization problems, the proposed technique will be a strong tool for solving complex associations of machining and performance parameters in the future. A dataset of machining parameters and subsequent performance parameters was adopted from the available literature. The results indicated that the LSE method outperformed other techniques, yielding the lowest Root Mean Square Error (RMSE) in predicting Ra, Kw, and MRR, thus ensuring high machining accuracy. LSE technique reported relatively least RMSE values of 0.37 µm, 0.149Mm, and 237.23 mm3/min for Ra, Kw, and MRR, respectively. SA and PSO displayed identical and competitive RMSE values, slightly higher than LSE (up to 20 % higher). ANN and GA techniques were not effective relative to other considered techniques. LSE, SA, and PSO provide superior performance in optimizing AWJM parameters. The significant contribution of this research is the proposed optimization technique, offering a clear direction for solving complex associations between the performances and machining parameters of AWJM. This work also provides a foundation for future research to optimize such associations for other machining setups.
•LSE method outperformed other techniques, yielding the lowest Root Mean Square Error (RMSE) in predicting surface roughness, kerf width and material removal rate, thus ensuring high machining accuracy.•SA and PSO displayed identical and competitive RMSE values, slightly higher than LSE.•ANN and GA techniques were not effective relative to other considered techniques.•LSE, SA, and PSO provide superior performance in optimizing AWJM parameters.
The evolution of industrial development enabled massive improvements in the lightweight materials for products with high strength to weight ratios and superior corrosion resistance used in turbine ...and aerospace structures. Titanium and its alloys possess excellent service properties especially in the biomedical field, due to inherent difficulties arise while cutting these alloys using conventional processing operations. Therefore, in this research, abrasive water jet machining (AWJM) is employed as a nontraditional process to investigate the post-processing surface characteristics of Ti6Al4V alloy. The effects of process factors including water pressure, abrasive flow rate, feed rate and stand-off distance on the characteristics of the cut surfaces have been investigated. Comprehensive experimentation is carried out to determine parametric ranges involving lesser heat affected regions and improved surface characteristics. Through Taguchi based design of experiments, it is observed that abrasive flow rate and stand-off distance are the most significant parameters that affect the surface roughness and material morphology.
This paper presents an experimental investigation to ascertain the parametric impact of abrasive water jet machining on the surface quality of Inconel 718 material. Experiments were designed ...according to response surface methodology-box Behnken design by maintaining three levels of four process parameters-abrasive flow rate, water pressure, stand-off distance and traverse speed. The surface irregularity is measured during machining. The design expert software was used to establish an optimized mathematical model of process parameters for achieving the required surface roughness. Desirability function has also been used to optimize the process parameters. The confirmation experiments validate the reliability and capability of the developed model. Further, the surface characteristics were analyzed through scanning electron microscope images and energy-dispersive X-ray spectroscopy.
In the current scenario, the applications of natural fibers are increasing enormously due to their biodegradability, low-density and better mechanical properties. This research explains the machining ...nature of pineapple (P) and flax (F) fibers by the incorporation of cellulose micro filler (CMF). These epoxy-based composites were manufactured using compression moulding. In the machining process using abrasive water jet machining (AWJM), lower kerf angle of 1.31° and surface roughness of 5.1 µm were observed in 30% PF/2% cellulose micro filler hybrid epoxy combination. Agglomeration at higher filler incorporation causes decrease in machinability of hybrid 30% PF. Pineapple and flax hybrid fibers with 30 and 35 wt % showed better machinability at 2 and 3% cellulose micro filler addition. Scanning electron microscopy analysis after machining process showed reduction in flush off and pullouts of fiber by improved compaction with the epoxy matrix due to filler addition.
Abrasive water jet machining is a process that removes material using sand and water. This versatile process uses a high-pressure water jet loaded with abrasive particles of mineral origin. It allows ...the machining of all materials and is particularly suitable for machining or stripping applications on hard metal sheets. Due to a local action, the abrasive water jet limits heating and deformation. During machining, the removal of material occurs abrasion and erosion 1. The identification of the respective importance of this abrasion and this erosion conditions the precision of the modeling of the machined depth. In this study, these mechanisms are presented and characterized for machining on 6mm thickness TiAl6V titanium alloys sheets with or without inclination of the jet. It is possible to model an elementary passage and it allows predicting the pocket bottom profile obtained after a succession of passages. During machining, two mechanisms appear. Abrasion occurs when machining an elementary pass. Erosion will characterize the effect of repetition of passages. The analysis of the machined profiles makes it possible to characterize the influence of the abrasion mechanism and abrasion mechanism. The variation of the coefficients associated with these mechanisms can be characterized as a function of the angle of inclination of the jet.Keywords: Abrasive water jet machining, Material removal mechanism, Abrasion, Erosion, Titanium alloy, Abrasive particles
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