This novel study deals with the investigation of abrasive mixtures on abrasive water jet (AWJ) drilling of stainless steel 304 using multi objective soft computing techniques. In this study, the ...drilling parameters such as abrasive mixture, stand-off distance and feed rate were varied. The abrasive mixture was prepared with the composition of different types of abrasives such as silicon carbide & garnet, and aluminium oxide & garnet, and different mixture ratios. This mixing ratio was done based on the total mass of the abrasive mixture. The effect of abrasive water jet drilling parameters was examined on the hole features such as the hole diameter, circularity, cylindricity, and surface roughness. Multi objective optimization and algorithm techniques were employed in this study, namely Taguchi–Grey Relational Analysis (TGRA) and Krill Herd Algorithm (KHA). In this research work, the performance of KHA method was also compared with another recent metaheuristic technique i.e. grey wolf optimization (GWO) based on the quality measurement tools such as Spacing and Inverted generational distance. For this approach, the main parameters of metaheuristics algorithms were tuned using a robust design approach to acquire the best feasible solution. Besides, different multiple linear regression model equations were established to determine the best model for the KHA method based on the similarity between experimental and calculated attributes. With the assistance of these approaches, it is found that the abrasive mixtures have improved the performance of the AWJ drilling process in SS 304 rather than the use of a single type abrasive such as 100% Garnet. The results of this study proved that the KHA optimization technique is successfully utilized to find the best configuration parameter setting for AWJ drilling process, and that results are found to be efficient than the TGRA. To validate the predicted results of KHA, confirmation test was conducted. The results of the confirmation test showed that the predicted hole features of KHA were acceptable as that the error deviation was found as less than 2% with the experimental results. It is also noticed that the computational time and the selected quality metrics of KHA are found to be lower than the GWO method. Hence, it is confirmed that a new metaheuristic algorithm namely, KHA was found suitable for AWJ drilling process. The outcome of the present work explores a new paradigm to the AWJ machining to improve performance features in various operations.
•Abrasive mixtures based approach is done in the abrasive water jet drilling.•Abrasive mixture ratio achieves better hole features than a single type abrasive.•Application of Krill herd algorithm and Grey wolf optimization have explored.•Taguchi–grey relational analysis and parameters tuning are conducted.•Comparison of Krill herd algorithm with the Grey wolf optimization is made.
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This paper aims to optimize the accuracy of the Abrasive Water Jet (AWJ) cutting process. The AWJ technology is a fast-growing production technology that competes with conventional machining methods ...due to its ability to cut various materials and conduct precise cutting of complex contours. In this research, the AWJ cutting process was tested on 18CrNiMo7-6 steel using almandine garnet type J80A as the abrasive material. The Taguchi method was used to optimize the process parameters. As control parameters chosen abrasive flow rate, pressure, and traverse speed. The output parameters measured were surface roughness and taper angle. The results shown managed to find the optimal combinations of control process parameters causing the lowest surface roughness and taper angle. The study provides insights into how the Taguchi method can be used to optimize the AWJ cutting process to achieve greater accuracy.
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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.
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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.
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The kerf taper and cutting front drag are crucial factors limiting the abrasive waterjet (AWJ) machining of ultra-thick CFRP laminates. Therefore, this study investigated the variation patterns of ...kerf width and maximum cutting front drag with process parameters and established predictive models. The models accurately predicted kerf entrance width, kerf exit width, and maximum cutting front drag with R-squares of 0.9881, 0.9761, and 0.9791. Moreover, the influence of the key kinematic parameter of complex structure manufacturing - the jet impact angle on the kerf profile was analyzed from a geometric analysis. A numerical regression approach was employed to derive an energy dissipation function for CFRP laminate processing. A semi-analytical mathematical model was established based on energy balance theory. Under arbitrary jet impact angle, the kerf profiles on both sides are predicted with R-square of 0.9455 and 0.9525 respectively, and the cutting front drag profile is predicted with R-square of 0.9078.
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•Potential of laser shock and water jet peened DMLS AlSi10Mg alloy are assessed.•Acicular grain structure refined for the laser shock peened DMLS AlSi10Mg alloy.•Residual stress formation had ...significant effects on hardness and wear resistance.•Significance of roughness on the work of adhesion is explored.•Friction and wear resistance of laser shock peened DMLS AlSi10Mg alloy is improved.
The present study explored the impact of laser shock peening (LSP) and abrasive water jet peening (WJP) on the physical, surface and wear properties of direct metal laser sintered (DMLS) AlSi10Mg alloy. The microstructure, phase composition, hardness, roughness, work of adhesion, residual stresses and wear properties of As-built AlSi10Mg, laser shock peened AlSi10Mg and water jet peened AlSi10Mg were evaluated. The results showed that both WJP and LSP could improve the hardness and wear resistance of DMLS AlSi10Mg alloy. Amongst, LSP was more effective than WJP in reducing the wear rate and coefficient of friction due to refined microstructure. Wear mechanisms were transformed from abrasive to fatigue after the LSP. Furthermore, the influences of roughness, residual stresses and hardness on the wear properties were discussed in detail.
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The issue of wear failure in High-Pressure Abrasive Water Jet (HP-AWJ) nozzles is an unavoidable challenge, and studying methods to enhance and predict the effective lifetime of nozzles is worth deep ...exploration. This paper employs a CFD-DEM coupling numerical approach to investigate wear phenomena inside the HP-AWJ nozzle, aiming to capture the realistic particle wear and erosion failure issues at the focusing tube region, which is a high-wear area of the HP-AWJ nozzle. Furthermore, the study considers realistic particles and nozzle wall constitutive models, incorporating material properties into the physical model, and employs computer-aided design methods to reflect wear failure conditions at different time intervals in the inner wall of the focusing tube at the nozzle. The results demonstrate that the number of realistic particles and initial inlet velocity has no impact on the particle exit kinetic energy. However, the particle-wall restitution coefficient affects the average particle kinetic energy at the outlet in the AWJ nozzle. The equivalent model of the realistic particles reflects the influence of the particle roundness on particle kinetic energy, acceleration, and stress concentration variations in the nozzle. These variations further affect the particle erosion rate on the nozzle wall and the actual wear failure problems on the wall surface. Finally, by combining the proposed erosion and wear model, a representative erosion profile at the AWJ focusing tube location comparable to experimental results is obtained, and the wear depth of the focusing tube changing with time is also studied. The results and methodologies presented in this paper provide valuable guidance for controlling the effective service lifetime of the AWJ nozzle, improving machining efficiency, and extending the lifespan of the AWJ nozzle.
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•A numerical CFD-DEM coupling approach to study wear in the HP-AWJ nozzle.•Three particle equivalent models based on nozzle wall contact for abrasive shapes.•The results and methods guide AWJ nozzle lifetime control.•The Finnie wear model with a stress model analyzes realistic wear locations.•Investigate nozzle wear depth in high-stress areas using Archard's wear law.
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The abrasive water jet (AWJ) cutting technique is one of the promising techniques used in machining of composite materials due to lack of thermal damage, lower tool wear and higher productivity. In ...this study, the AWJ cutting of a cross-ply CFRP laminate was investigated experimentally and numerically. The purpose is to understand the underlying physics of the AWJ cutting of a composite plate, which can be later used to control the process as well as optimizing its parameters. In the performed tests of the plate with a stacking sequence of 0°/90°/0°/90° and having a total thickness value of 0.84 mm, where the pressure of particles and impact angle were varied, different failure characteristics such as fiber pull-out, fiber breakage, fiber debonding, matrix cracking and delamination were noticed. A three-dimensional FE model of the process was developed using ABAQUS finite element software to understand the underlying physics. In the model, the pure water jet particles following the linear Hugoniot form of the Mie-Grüneisen equation of state and highly rigid abrasive particles were modelled using smooth particle hydrodynamics. While the three dimensional Hashin damage model was used to simulate the intra ply damage, cohesive zone elements were used to predict the delamination. The damage characteristics in the composite plate was investigated for different process parameters. When the speed of the AWJ particles increased from 300 m/s to 600 m/s, the amount of delamination decreased from 6.44% to 5.69% at the top interface with no more delamination observed at the middle and bottom interfaces. The delamination performance of 0°/90°/0°/90° orientation was found to be better than those of 0°/90°/90°/0° and 0°/0°/90°/90° orientations. The impact angle of the particles affected the material removal rate in the process significantly. The failure behaviour of the laminate subjected to AWJ and pure water jet cuttings (PWJ) were also compared.
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Abrasive water jet (AWJ) has gained an important place among the machining technologies due to its capacity to cut complex shapes in various materials without thermal effects and with low cutting ...forces, but it also has a reduced environmental impact. A key element for the quality of the cut is the amount of energy contained in the abrasive jet. The dissipaton of energy leads to kerf taper, high values of surface roughness, surface striations, the deviation of the water jet (jet drag), and even insufficient penetration. The current paper investigates the influence of process parameters on the quality of the cut for a S235 steel alloy. The quality of the cut was assessed by four parameters: entrance width of cut (Li), exit width of cut (Le), perpendicularity (u) and kerf angle (α). The experiments were organized according to a D-optimal Response Surface Method. Analysis of variance (ANOVA) was used for the development of a mathematical model that correlates the influence of process parameters on the quality of the cut. Finally, an optimization of the process parameters was proposed.
Overlapping adjacent passes of abrasive slurry jets can be used to fabricate micro-pockets or blind micro-slots. This study investigates the propagation of surfaces milled using overlapping passes of ...a high-pressure abrasive slurry jet on a ductile 6061-T6 target over a wide range of aspect ratios. Features such as shallow pockets with low aspect ratios to deep slots with aspect ratios ∼1.5 were fabricated to investigate the correlations between the aspect ratio, degree of pass overlap, and number of repeating passes with the machined surface evolution characteristics. A comprehensive model was presented that combined computational fluid dynamics (CFD) with surface evolution to predict the evolving machined feature topography after each of the overlapping and repeating passes, and to provide insights into experimental observations. The model explicitly considered the CFD-predicted local particle impact angles and velocities as well as effects due to secondary impacts, high sidewall slopes, and stagnation effects. For larger degrees of overlap, measurements revealed a more than linear rate of increase in depth after each repeat of two adjacent overlapped passes, as opposed to a linear depth increase for smaller overlaps and blind pockets. Large overlaps were found to result in asymmetric features. Up to a critical aspect ratio of ∼0.65, the model predicted the surface evolution of the features to within <8.6% of those measured. Beyond that, randomness in the machined feature shape and size made the process challenging to control and the surface evolution difficult to predict. Nevertheless, the model was able to elucidate the reasons for the randomness and other observed phenomena such as the more than linear growth in etch rate, and the occurrence of feature asymmetry. The findings emphasize that flow confinement, increases in the jet's turbulent kinetic energy, and the formation of vortices at the bottom of the machined features are critical factors influencing the machining process, and that in these cases explicit modeling approaches like the one presented in this study must be used.
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•Topography of features milled with overlapping passes predicted and analyzed.•3D CFD used to study effect of slurry confinement within pre-eroded features.•Increased turbulence results in reduced repeatability at high aspect ratios.•Milled features with large overlaps exhibit asymmetry at high aspect ratios.•Feature depth increases faster than linear rate per pass due to flow confinement.
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