In this paper, a new approach proposed for modelling the three-dimensional (3D) topography produced on abrasive water jet (AWJ) cut surface is presented. It makes use of the trajectory of jet, predicted from the theory of ballistics and Bitter's theory of erosion for material removal, for numerically simulating the cutting front. The 2D topography at different depths of the cut surface is generated by considering the trajectories on the cutting front and the abrasive particles impacting the walls of cut surface randomly. For realistic generation of topography on cut surfaces, several instantaneous profiles generated in each region of cut are superimposed to obtain an effective profile. The nature of effective profiles thus predicted is analyzed and validated using power spectral density analysis. The effective profiles predicted at different depths are in turn used to generate the 3D topography of AWJ cut surface. Results obtained with the proposed model are validated with the experimental results. © 2002 Elsevier Science Ltd. All rights reserved.

N. Ramesh Babu

Department of Mechanical Engineering

Computer simulation

Jets

Surface topography

Water

Abrasive water jet cutting

Abrasive cutting

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Modelling and analysis of abrasive water jet cut surface topography

International Journal of Machine Tools and Manufacture

This paper presents a modified model to predict the total depth of cut in abrasive waterjet cutting (AWJC). For predicting the depth of cut in the cutting wear region, the interaction of cylindrical waterjet with the target material and the deflection of jet in lateral direction perpendicular to the direction of traverse of jet in cutting are considered. Several researchers have suggested neglecting the threshold velocity, since its effect on material removal is negligible due to high velocity of jet. Therefore, the depth of cut in the deformation wear region is predicted with and without considering the threshold velocity to show that the effect of threshold velocity on material removal is negligible. The effectiveness of the model is demonstrated with the experimental data. Copyright © 2009, Inderscience Publishers.

International Journal of Abrasive Technology

An analytical model for predicting depth of cut in abrasive waterjet cutting of ductile materials considering the deflection of jet in lateral direction

Abrasive water jet cutting (AWJC) is one of the important non-traditional machining processes used for cutting of difficult-to-cut materials and intricate profiles. Cutting of Kevlar fibre reinforced polymer composites is a complex process, making it difficult to model, predict and improve the cut surface quality. This paper presents a detailed approach of the usage and effectiveness of a back-propagation neural network (NN) for modelling and prediction of three cut surface characteristics namely top kerf width, bottom kerf width and surface roughness (Ra) in AWJC of aerospace grade Kevlar-epoxy composites. Statistically designed full factorial experiments based on three process parameters [water jet pressure (WJP), abrasive flow rate (AFR) and quality level (QL)] at three levels each were conducted to generate the NN training database. The results demonstrate that the NN model was able to successfully model and predict the two kerf widths and surface roughness closely matching the experimental results. Copyright © 2010 Inderscience Enterprises Ltd.

International Journal of Machining and Machinability of Materials

Predictive modelling of surface roughness and kerf widths in abrasive water jet cutting of Kevlar composites using neural network

Abrasive water jet cutting (AWJC) is particularly useful for difficult-to-cut materials like composites, super alloys and ceramics. However, the surface finish produced is often poor, necessitating finishing operations like grinding, etc., which lead to delamination in case of polymer composite laminates. Therefore, optimum selection of process parameters is important in AWJC. This paper presents the influence of three process parameters (water jet pressure, abrasive flow rate and quality level) on surface roughness (Ra) in AWJC of Kevlar composites. The optimal parameter setting was determined using a hybrid Taguchi and response surface method (HTRSM). The experimental results and ANOVA analysis indicate that quality level and water jet pressure have more significant effect on Ra. A second order response surface model was developed using the central composite rotatable design CCRD). Finally, confirmation experiments were conducted to verify the predicted and experimental results at optimal settings, and an excellent agreement was obtained between the two. © 2008, Inderscience Publishers.

Optimisation of surface finish in abrasive water jet cutting of Kevlar composites using hybrid Taguchi and response surface method

The effective profile of the grinding wheel is of importance in the production of ground surfaces. The analysis of individual sectional profiles of the grinding wheel taken using a stylus instrument and of the effective profile taken with a replica technique is presented. © 1979.

Journal	International Journal of Machine Tools and Manufacture
ISSN	08906955
Open Access	No