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Carbon Fiber Reinforced Aluminum Laminated (CARALL) composites are widely used in aircraft structures due to their ability to be produced in different shapes with desired properties and their high impact resistance properties. As with other layered composite materials, processing of CARALL composites by conventional manufacturing methods results in many damage mechanisms such as fiber breakage, deformation in the hole region, stress concentration, resin‐fiber separation and microcracks. One of the modern manufacturing methods, Abrasive Water Jet (AWJ), is a processing method in which the material is removed by abrasion and almost any material can be cut without thermal degradation. There are no experimental studies in the literature on the drilling of CARALL composites by modern manufacturing methods. The aim of this study is to investigate the impact of machining parameters on the output variables (kerf taper angle (K), roundness error (Re) and material removal rate (MRR)) as well as the effect of fiber orientation on the drilling of CARALL composites with different fiber orientations on an AWJ machine. PROMETHEE‐GAIA weighted by Entropy Weighting Method were used to ascertain the optimum levels of control factors. CARALL composites with different fiber orientations were drilled with an 8 mm diameter AWJ with three different water pressures, three different nozzle feed rates. With PROMETHEE‐GAIA multi‐criteria optimization method, the optimum levels of the factors that provide both minimum Re and K values and maximum MRR value were obtained with twill woven material, 1680 mm/min feed rate and 1680 bar water pressure. Highlights: CARALL composite materials with two different fiber orientations (twill weave and UD) were used.CARALL composite materials were drilled at different machining parameters.Abrasive water jet was used in drilling experiments.Optimum drilling parameters were determined to achieve minimum roundness error, minimum kerf angle and maximum material removal rate.PROMETHEE‐GAIA was used as a multi‐criteria decision‐making method. [ABSTRACT FROM AUTHOR]

Although the abrasive water jet (AWJ) has proven to be a suitable process for machining composite materials, it has some limitations related to dimensional inaccuracy and surface defects. As the performance of the AWJ process mainly depends on the machining parameters, an optimal selection of them is crucial to achieving an improved quality of cut. In this context, the present study reports an experimental investigation to assess the influence of AWJ machining parameters on kerf taper angle (θ) and surface roughness (Ra) of E glass/Vinylester 411 resin laminates. The experiments are carried out using a full factorial design by varying the water pressure, traverse speed, abrasive flow rate, and standoff distance. A first-ever attempt is made in this paper to optimize the AWJ process using a hybrid approach combining artificial neural networks (ANNs) with a recently proposed metaheuristic algorithm known as multi-objective bonobo optimizer (MOBO). The results show that standoff distance and abrasive flow rate were the most significant control factors in influencing θ and Ra, respectively. The developed ANN models are capable to predict the output responses with high accuracy and the solutions from the Pareto front provide a sufficient performance with a trade-off between θ and Ra. The corresponding levels of the optimal process parameters are 430 g/min for the abrasive flow rate, the range of 140–180 mm/min for the traverse speed, 280 MPa for the pressure, and 1.5 mm for the standoff distance. [ABSTRACT FROM AUTHOR]

Abrasive water jet machining (AWJM) is the modern machining method used in various industrial applications. In this paper, an attempt has been made to determine optimum AWJM parameters using artificial neural network (ANN). Flow rate of abrasive, stand-off distance and traverse speed are used as input parameters for machining of AISI 1018 steel. Experimental data are used for training and testing of ANN. A feed forward ANN is established using the experimental data obtained during the AWJ machining of steel. Surface roughness (Ra) and kerf taper angle (ϴ) are estimated, on the basis of ANN performance and regression analysis. The regression plots of both responses show more than 97% of agreement among the estimated values and experimental data. Later on, novel approach of model optimisation is executed using univariate analysis on inputs to ANN to get the optimal AWJM process parameters. Optimal response solution is obtained as surface roughness (Ra) = 2.46 μm and taper angle (ϴ) = 1.25° at flow rate (Af) = 450 g/min; stand-off distance (Sd) = 3 mm and traverse speed (Tv) = 85 mm/min. The study shows that the ANN is proficient tool for deciding the optimum AWJ machining parameters. [ABSTRACT FROM AUTHOR]

Abrasive water jet machining has become an indispensable process for cutting Kevlar fiber-reinforced polymers used in applications such as ballistics protection, race cars, and protective gloves. The complex and diffuse action of a large number of input parameters leads to the need to evaluate the quality characteristics of the technological transformation as a result of the deployment of experimental studies adapted to the specific processing conditions. Thus, the paper focuses on identifying the influence of different factors and modeling their action on the characteristics that define the quality of the cut parts, such as the kerf taper angle and the Ra roughness parameter, by applying statistical methods of design and analysis of experiments. [ABSTRACT FROM AUTHOR]

The controversial issue in composite machining is usage of some nontraditional approaches to resolve the difficulty arising from composite machining. Thus, to obviate this difficulty, abrasive water jet machining could be applied. The purpose of this investigation is to study some responses such as material removal rate and kerf taper angle affected by some process parameters including traverse speed, water jet pressure, abrasive flow rate, various types of reinforcement particles, and their weight percentages via ANOVA analysis to evaluate their optimal level. Further, molecular dynamic simulations are applied to validate results obtained from experiments. For this purpose, the outcomes are described by temperature and potential energy of atomic to indicate the time for atomic equilibrium process and equilibrium phase of different simulated samples. In addition, to examine the effects of the process parameters, scanning electron microscopy and X-ray diffraction were used to determine the microstructure of machined surfaces and plastic deformation. The experimental results revealed that with reduction in the traverse speed (from 167.64 to 55.08 mm min−1, weight percentage ( 7.5 – 2.5 ), water pressure (270–200 bar), and using SiC as reinforcement particle in matrix and an increase in flow rate (from 305 to 470 g min−1), the kerf taper angle diminished, suggesting the high quality of machining. In this study, the results obtained from material removal rate and kerf taper angle showed that traverse speed is a substantial parameter in enhancing the quality of water jet machining. [ABSTRACT FROM AUTHOR]

The development of mathematical models by using experimental data is of great importance for modelling and optimization of the laser cutting process. Motivated by the lack of research regarding the use of genetic programming (GP) for deriving empirical mathematical models that describe the laser cutting process, the present study discusses the application of GP to the development of a kerf taper angle mathematical model. The aim was to quantify the relationship between three selected input parameters (cutting speed, laser power and assist gas pressure) and kerf taper angle using GP in the CO2 laser cutting of aluminium alloy AlMg3. To obtain the experimental database for the GP model evolution process, a laser cutting experiment was planned as per standard full factorial design where all three selected parameters were varied at three levels. The fit between the experimental and the GP model prediction values of kerf taper angle was found to be appropriate. Finally, by using the derived GP mathematical model, the analysis of the effects of input parameters on the change in kerf taper angle values was performed by generating 3D surface plots. [ABSTRACT FROM AUTHOR]

• Numerical Modeling for CO 2 laser machining with multipass approach. • Applying FEM model to simulate laser as a moving heat source. • Numerical simulation for kerf width, kerf angle and HAZ. • Numerical simulation of laser-polymer interaction based on thermophysical analysis. • Finite element analysis with DFLUX and USDFLD subroutines. Laser-assisted machining is an advanced manufacturing process that provides excellent cutting quality, flexibility, and precision. The current study used a CO 2 laser to create microchannels in polymethyl methacrylate (PMMA) sheets using a series of laser passes by varying parameters such as laser power (30–40 Watt), number of passes (1–4), and cutting speed (20–25 mm/s). A finite element analysis is performed using ABAQUS with subroutines such as Distributed Flux (DFLUX) and User Defined Field (USDFLD) to simulate and predict the upper and lower kerf width, kerf angle, and heat-affected zone (HAZ) during the process. Thermal analysis has been performed by considering the laser beam as body heat flux with a moving heat source. It has been observed that the HAZ tends to reduce with the increase of laser cutting speed. During the laser cutting process, the upper kerf width is found to increase with increasing laser power, as well as with increasing the number of passes at a given laser power and cutting speed. It is also predicted that when laser cutting speed increases, the kerf width for a given laser power decreases. The experimental and simulation results are in good agreement and the results demonstrated that the average percentage error in HAZ, kerf angle, upper kerf, and lower kerf width was 3.21 %, 5.06 %, 7.60 %, and 22.2 %, respectively. The results of this study have significance for the advancement of precise and state-of-the-art manufacturing for application in microfluidic devices. [ABSTRACT FROM AUTHOR]