The Predictive Model of Surface Texture Generated by Abrasive Water Jet for Austenitic Steels

Abstract

Austenitic stainless steel belongs to the best oxidation-resistant alloys, which must function effectively and reliably when used in a corrosion environment. Their attractive combination of properties ensures their stable position in the steel industry. They belong to a group of difficult-to-cut materials, and the abrasive water jet cutting technology is often used for their processing. Samples made of stainless steel AISI 304 has been used as the experimental material. Data generated during experiments were used to study the effects of AWJ process parameters (high-pressure water volume flow rate, the diameter of the abrasive nozzle, the distance of the nozzle from the material surface, cutting head feed rate, abrasive mass flow, and material thickness) on surface roughness. Based on the analysis and interpretation of all data, a prediction model was created. The main goal of the long-term research was to create the simplest and most usable prediction model for the group of austenitic steels, based on the evaluation of the practical results obtained in the company Watting Ltd. (Budovateľská 3598/38, Prešov, Slovakia) during 20 years of operation and cooperation with customers from industrial practice. Based on specific customer requirements from practice, the publication also contains specific recommendations for practice and a proposal for the classification of the predicted cut quality.

Prediction of Surface Roughness of an Abrasive Water Jet Cut Using an Artificial Neural Network

“…The material of the machined workpiece used in the experiments was X5CrNi18-10 ( ) stainless steel plates of three different thicknesses, mm, mm, and mm. The material was austenitic stainless steel, which is difficult to machine from a traditional cutting process standpoint and is often processed with an AWJ [ 23 ]. After evaluating the process parameters, we selected those with the most significant influence on the cut quality for the design of experiments (DOE).…”

“…Most researchers are trying to control and optimize the process parameters for various materials and with various methods [ 22 ]. From the presented literature overview, different approaches were used to investigate the AWJ cutting surface roughness [ 23 ]. Most researchers are trying to control and optimize the process parameters for various materials and with various methods [ 22 ].…”

“…Most researchers are trying to control and optimize the process parameters for various materials and with various methods [ 22 ]. From the presented literature overview, different approaches were used to investigate the AWJ cutting surface roughness [ 23 , 24 ]. Because of the many process variables and complex physical phenomena taking place during the AWJ cutting, machine learning methods for modeling the process are appropriate.…”

Recent Progress Trend on Abrasive Waterjet Cutting of Metallic Materials: A Review

“…Impacts of abrasive mass flow rate: In AWJ cutting operation, increasing the abrasive mass flow rate increases the erosion efficiency, containing a higher number of abrasives which relatively increases the depth of cut and decreases surface roughness value [36]. An increased rate of waterjet pressure denotes a parallel performance with abrasive flow rate [92].…”

“…Impacts of nozzle and orifice diameter: Variation in the nozzle diameter and orifice leads to machining inconsistency due to the ascending airflow rate, jet deviating, and path size, hence impacting the material removal rate, surface roughness, and geometric accuracy in the broad-spectrum [6]. Furthermore, Kmec et al [36] have investigated cutting austenitic steel AISI 304, which has recently been the most prevalent type of anti-corrosion material in various industrial applications. They used different abrasive nozzle diameter sizes including 0.76 mm and 1.02 mm.…”