A new model for predicting the depth of cut in abrasive waterjet contouring of alumina ceramics

2009 ◽  
Vol 209 (5) ◽  
pp. 2314-2320 ◽  
Author(s):  
J. Wang
Keyword(s):  
Abrasive Waterjet ◽  
Depth Of Cut ◽  
Alumina Ceramics ◽  
New Model

scholarly journals Profile Cutting on Alumina Ceramics by Abrasive Waterjet. Part 2: Cutting Performance Models

2006 ◽  
Vol 220 (5) ◽  
pp. 715-725 ◽  
Author(s):  
J Wang ◽  
H Liu
Keyword(s):  
Performance Measures ◽  
Predictive Models ◽  
Cutting Performance ◽  
Abrasive Waterjet ◽  
Depth Of Cut ◽  
Alumina Ceramics ◽  
Predictive Capability ◽  
Performance Models ◽  
Kerf Taper ◽  
Model Predictions

Predictive models for the major cutting performance measures, such as the kerf taper and depth of cut, are developed for both straight-slit cutting and profile cutting by an abrasive waterjet. The plausibility and predictive capability of the models are assessed and verified by comparing the model predictions with the corresponding experimental data. Very good correlations between the predicted and experimental results have been found, which confirm the adequacy of the models for use in process planning.

scholarly journals Profile Cutting on Alumina Ceramics by Abrasive Waterjet. Part 1: Experimental Investigation

2006 ◽  
Vol 220 (5) ◽  
pp. 703-714 ◽  
Author(s):  
J Wang ◽  
H Liu
Keyword(s):  
Experimental Investigation ◽  
Performance Measures ◽  
Process Parameters ◽  
Cutting Performance ◽  
Cutting Process ◽  
Abrasive Waterjet ◽  
Depth Of Cut ◽  
Curvature Radius ◽  
Alumina Ceramics ◽  
Awj Cutting

An experimental investigation is presented of the various cutting performance measures, such as the kerf taper and depth of cut, in profile cutting on an 87 per cent alumina ceramic by abrasive waterjet (AWJ) over a wide range of process parameters. It is found that the taper angles on the two kerf walls produced in cutting AWJ of profiles are different in magnitude and exhibit different trends as the profile curvature radius varies. Moreover, the depth of cut increases with an increase in the curvature radius and approaches its maximum in straight cutting. The other process variables affect the cutting process in a way similar to that in straight cutting. Recommendations are finally made for the selection of process parameters in AWJ profile cutting of alumina ceramics. Predictive mathematical models for the major cutting performance measures that are essential for the optimization of the AWJ cutting process are reported in the subsequent part of this investigation.

Machining Capabilities of Abrasive Waterjet on Stainless Steel 304

2019 ◽  
Vol 895 ◽  
pp. 313-318
Author(s):  
S.B. Supriya ◽  
S. Srinivas
Keyword(s):  
Stainless Steel ◽  
Stainless Steels ◽  
Cutting Tool ◽  
High Hardness ◽  
Abrasive Waterjet ◽  
Depth Of Cut ◽  
Machined Surface ◽  
Sem Images ◽  
Enhanced Production ◽  
Work Material

Stainless Steels are possessing fabrication flexibility, high hardness, durability, low maintenance, high strength and resistance to heat and corrosion. This alloy steel is extensively used in various engineering applications. Some of the conventional machining techniques results in loss of original properties of stainless steel work material and makes it to behave like ordinary material within the machined surface. Machining of Stainless steels is more challenging due to its high alloying content. Problems such as application of huge coolant supply and poor chip breaking while machining, work hardening in work material, use of cutting tools with varying tool signature, results in enhanced production cost and time. Further, it is important to ensure that there is no machine tool-cutting tool vibration leading to edge chipping of cutting tool. To avoid all these problems, Abrasive water jet machining (AWJM) is used. This paper presents the machining capabilities of AWJ on Stainless Steel304. Influence of dynamic input parameters such as jet pressure, speed of traverse and abrasive flow rate on the depth of cut is investigated. An empirical model is proposed for depth of cut and an error analysis is done with measured and modeled values of depth of cut. It was found that traverse speed influences more than other parameters. SEM images indicated smooth surface at entrance and waviness at exit side. The model proposed predicts the depth of cut more or less accurately.

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