In the present study, experimental investigations were conducted to find out the effect of Abrasive Water Jet Machining (AWJM) process parameters on the surface roughness (Ra) of white Makrana Marble. The approach was based on Taguchi’, s method and analysis of variance (ANOVA) to optimize the AWJM process parameters for effective Machining. Nozzle transverse speed, Water pressure, and stand of distance were selected as the input parameters while the other was kept constant. It was found that the Water pressure and nozzle transverse speed were significant control factors and the stand of distance was the insignificant control factor in controlling the surface roughness (Ra).

The present work aims to investigate Abrasive Water Jet Machining parameters for Machining of Al-Al2O3 Metal Matrix Composite. Plan of experiments, based on Taguchi’s analysis technique were performed using L9 orthogonal array. A correlation was established between concentration of Al2O3, Stand-off distance, pressure and Transverse feed with Metal Removal Rate, Surface Roughness, Over-cut and Taper angle by regression analysis. On the basis of experimental results and S/N ratio analysis, ranking of the parameters has been done. The analysis of variance (ANOVA) has been used to find out the impact of individual parameters on response parameters. Al2O3 concentration plays a very significant role in determination of MRR and surface roughness. Also overcut is largely influenced by stand off distance. Furthermore, multi-objective optimization can be carried out using advanced optimization techniques. This work helped to generate technical database for industrial applications of MMC.

This paper addresses the concept of the expert system for Abrasive WaterJet Machining. For optimization of Abrasive WaterJet Machining, computer based concurrent engineering environment is used. The design specification is acquired through a feature based approach. The expert system links with feature base library. The expert system links with material database which holds attributes of more than 20 type of materials. It also links with Abrasive data base which hold attributes of 8 types of Abrasive, and also 4 type and size of machine. expert system also links with machine database which hold machine parameters. For each design feature, the expert system provides information needed for optimization of design and manufacturing. The expert system can be used as an advisory system for optimization of design and manufacturing. It can be used as a teaching program for new Abrasive WaterJet Machining operators. For each design feature, the expert system provides information such as Machining cycle time and cost and cutting rate. By changing machine parameters, we can optimize Machining cycle time and cost and cutting rate. Comparison results of the expert system and experimental CNC Abrasive WaterJet results for different design feature shows that Machining time and cost of expert system is 10% less than experimental.

This study aimed at the evaluation of wood Machining parameters and surface quality upon using a Water Jet without Abrasive material. Hence, wood species (beech, oak, and poplar), cutting velocity (200, 400 and, 600 m/s), and cutting direction (parallel and perpendicular to the grain) were chosen as variables. After cutting samples with a Water Jet, the samples were scanned from edge and surface using a 1200 dpi scanner. For analyzing the depth of cut and kerf width, ImageJ software was used. The surface quality was evaluated using a stylus profilometer, and the surface roughness parameters including Ra, and Rz were measured. The highest and lowest values of depth of cut and kerf width were measured for poplar and beech woods, respectively. According to the results, it can be stated that the cutting direction has a significant effect on the Machining parameters so that the maximum depth of cut and the lowest kerf width was observed in the direction parallel to the grain. Also, the results showed that with increasing cutting velocity, the depth of cut increases, and kerf width decreases. The highest and lowest values of surface roughness parameters were observed in poplar (Rz=136/8μ ), and beech (Rz=115/62μ ) woods, respectively. Based on the results, it can be concluded that high-speed Machining in woods with dense texture and parallel to grain can improve the surface quality in Water Jet cutting.

In this study, an Abrasive Water Jet Machining process was used to evaluate the machinability of Hardox 400 steel, as one of the most widely used materials in the sheet metal industry. In this regard, surface roughness and geometrical tolerances (flatness, parallelism, and perpendicularity) were considered as the Machining outputs, and Water Jet pressure, the weight percentage of Abrasive particles, nozzle gap and feed rate were considered as the process input parameters. Followed by Machining tests, the measurement of geometrical tolerances and surface roughness was performed through coordinate measuring machine (CMM) and surface roughness tester, respectively. The obtained results indicate that by the increase of Jet pressure, decrease of feed rate, decrease of nozzle gap and increase of Abrasives particles weight fraction, the surface quality improves and the geometrical errors reduce. Also, it was observed that the best surface roughness and geometrical tolerances have been obtained in the case of Water Jet pressure of 300 MPa, the feed rate of 10 mm/min, the Abrasive weight percentage of 30% and nozzle gap of 1 mm. By repeating the experimental tests, it was shown that the relative error of the obtained results is less than 10%, which indicates the high repeatability of the results.

A simulation method for Abrasive Water Jet Machining is presented in this work in order to convert the initial error profile existing on the surface to an ideal form by a CAM system. The work piece is an optical glass with a pre-polished surface.Several parameters are effective in Abrasive Water Jet Machining. In this paper, an algorithm for simulation of Abrasive Water Jet Machining process is developed with a removal spot profile obtained in a specific qualification of process parameter. According to the developed algorithm, a CAM system was developed in Auto CAD environment. Optimum values of the process parameters are predicted by the developed simulation CAM system and resulting in time-saving and economical real experimental method.This algorithm was applied for a sinusoidal error and their result was compared with experimental results. Base on the result, a sinusoidal error equal to 190 nm, was corrected and reduced to 35 nm by the parameter values predicted by the simulation CAM system.

On account of some complexities such as fluid-structure interaction and extra-large deformation problems, complete simulation of Abrasive Water Jet cutting process is very hard. The main goal of this paper is to overcome these difficulties through comprehensive simulation in LS-DYNA commercial software. For this purpose the Smoothed Particle Hydrodynamics (SPH) and Arbitrary Lagrangian Eulerian (ALE) methods are employed. Utilizing these methods, the depth of Water Jet penetration and mechanism of erosion are simulated for a certain test case. In addition, the effect of Water pressure and traverse speed on depth of penetration are examined. Comparison between the obtained results using both methods showed that the numerical results are in good agreement with available experimental data.

This paper proposes a hybrid approach based on the Artificial Neural network and Genetic algorithm to optimize surface roughness at the Abrasive Water Jet (AWJ) cutting of glass material. At first, Artificial Neural Network (ANN) was developed in order to model and predict surface roughness by considering the controllable cutting parameters such as Water pressure, Abrasive flow rate, Jet traverse rate and stand of distance. Then the results of the neural network were compared with corresponding experimental tests. According to the obtained results, it was shown that the ANN model is able to present a predictive model of the process in order to estimate the surface roughness successfully. After that, ANN model was combined by genetic algorithm to obtain suitable Machining parameters yield to minimal surface roughness. Finally, obtained results showed that, utilized hybrid technique in this paper was employed properly for optimizing AWJ cutting process.

Nowadays, the non-traditional processes such as LASER, EDM and AWJ, are used for cutting high thickness sheet metal. Hardox is hard and tough steel alloy and it has many industrial applications. One of the best processes to cut the Hardox is Abrasive Water Jet (AWJ) cutting. It can cut complex shapes with high quality and accurate tolerances. AWJ cutting offers certain unique benefits such as negligible heat affected zone, high degree of maneuverability in cutting process and less Machining force exertion. In this research work, first, the effective cutting process “AWJ” parameters were identified. Then, to determine optimum Hardox cutting parameters, some experimental tests were undergone.Finally, the experimental results were analysed using “ANOVA” technique in order to determine regression equations for achieving optimum parameters to setup equipment for Hardox steel cutting.