A soft computing approach for controlling the quality of cut with abrasive waterjet cutting system experiencing orifice and focusing tube wear

Abstract In abrasive waterjet (AWJ) cutting system, the orifice and focusing tube undergo continuous wear due to which the quality and effectiveness of the process are affected. The present paper reports the experimental studies carried out to investigate the influence of orifice and focusing tube bore variation on the performance of abrasive waterjets in cutting 6063-T6 aluminum alloy. The performance was assessed in terms of different parameters such as depth of cut, kerf width and surface roughness. This study made use of Taguchi's design of experiments and analysis of variance (ANOVA) to analyze the performance of AWJs in cutting. These experimental data was used to build empirical models. An hybrid strategy combining the response equations of the empirical model with fuzzy model is proposed to arrive at suitable set of process parameters for achieving desired cutting performance considering the variation in orifice and focusing tube bore. The adequacy of the model is confirmed with suitable experiments.

[1]  Radovan Kovacevic,et al.  State of the Art of Research and Development in Abrasive Waterjet Machining , 1997 .

[2]  J. John Rozario Jegaraj,et al.  535 Fuzzy based control strategy for condition monitoring of abrasive waterjet using vacuum sensor , 2003 .

[3]  Dwayne Arola,et al.  The influence of abrasive waterjet cutting conditions on the surface quality of graphite/epoxy laminates , 1994 .

[4]  M. Hashish,et al.  An Investigation of Milling With Abrasive-Waterjets , 1989 .

[5]  M. Hashish,et al.  Optimization factors in abrasive-waterjet machining , 1991 .

[6]  M. Hashish,et al.  Pressure Effects in Abrasive-Waterjet (AWJ) Machining , 1989 .

[7]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[8]  Ian Masters,et al.  Design optimisation of aluminium recycling processes using Taguchi technique , 2002 .

[9]  Madhan Shridhar Phadke,et al.  Quality Engineering Using Robust Design , 1989 .

[10]  N. Ramesh Babu,et al.  A New Approach for Selection of Optimal Process Parameters in Abrasive Water Jet Cutting , 1999 .

[11]  M. Hashish.  A Modeling Study of Metal Cutting With Abrasive Waterjets , 1984 .

[12]  T. R. Bement,et al.  Taguchi techniques for quality engineering , 1995 .

[13]  Suat Tanaydin.  Robust Design and Analysis for Quality Engineering , 1996 .

[14]  M. Kantha Babu,et al.  Studies on abrasive waterjet machining of black granite through design of experiments , 2003 .

[15]  M. Hashish,et al.  Characteristics of Surfaces Machined With Abrasive-Waterjets , 1991 .

[16]  J. Davim.  Design of optimisation of cutting parameters for turning metal matrix composites based on the orthogonal arrays , 2003 .

[17]  Y. S. Tarng,et al.  Design optimization of cutting parameters for turning operations based on the Taguchi method , 1998 .

[18]  Radovan Kovacevic,et al.  Surface texture in abrasive waterjet cutting , 1991 .

[19]  Radovan Kovacevic,et al.  Modeling of the influence of the abrasive waterjet cutting parameters on the depth of cut based on fuzzy rules , 1994 .