Response Surface Methods Used for Optimization of Abrasive Waterjet Machining of the Stainless Steel X2 CrNiMo 17-12-2

Deaconescu, Andrea; Deaconescu, Tudor

doi:10.3390/ma14102475

Cited by 12 publications

(11 citation statements)

References 19 publications

(19 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Response surfaces comply with the findings of A. Deaconescu and T. Deaconescu [ 22 ] by researching the impact of various AWJ process parameters. They analyzed similar material with higher thicknesses but without analysis of a cut surface at different depths.…”

Section: Resultssupporting

confidence: 76%

“…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 ]. From the presented literature overview, different approaches were used to investigate the AWJ cutting surface roughness [ 23 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

et al. 2021

View full text Add to dashboard Cite

The study’s primary purpose was to explore the abrasive water jet (AWJ) cut machinability of stainless steel X5CrNi18-10 (1.4301). The study analyzed the effects of such process parameters as the traverse speed (TS), the depth of cut (DC), and the abrasive mass flow rate (AR) on the surface roughness (Ra) concerning the thickness of the workpiece. Three different thicknesses were cut under different conditions; the Ra was measured at the top, in the middle, and the bottom of the cut. Experimental results were used in the developed feed-forward artificial neural network (ANN) to predict the Ra. The ANN’s model was validated using k-fold cross-validation. A lowest test root mean squared error (RMSE) of 0.2084 was achieved. The results of the predicted Ra by the ANN model and the results of the experimental data were compared. Additionally, as TS and DC were recognized, analysis of variance at a 95% confidence level was used to determine the most significant factors. Consequently, the ANN input parameters were modified, resulting in improved prediction; results show that the proposed model could be a useful tool for optimizing AWJ cut process parameters for predicting Ra. Its main advantage is the reduced time needed for experimentation.

show abstract

Section: Resultssupporting

confidence: 76%

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

View full text Add to dashboard Cite

show abstract

“…The Taguchi method is based on the analysis of the system's response to factor variability, by introducing the signal/noise ratio (Y/N). The optimization of the system is done by choosing the configuration that has the maximum S/N value [37,38].…”

Section: Methodsmentioning

confidence: 99%

Reduction of Cracks in Marble Appeared at Hydro-Abrasive Jet Cutting Using Taguchi Method

Barabas¹,

Florescu²

2022

Materials

View full text Add to dashboard Cite

The appearance of cracks in brittle materials in general and in marble, in particular, is a problem in the hydro-abrasive jet cutting process. In this paper is presented a method to reduce the appearance of cracks when cutting with a hydro-abrasive jet of marble by using statistical analysis. The Taguchi method was used, establishing the main parameters that influence the process. Research design was based on performing experiments by modifying the parameters that influence the process. In this way, it has been shown that the stochastic effects resulting from the marble structure can be reduced. A careful study was made of the behavior of marble under the action of the hydro-abrasive jet, and of the behavior of the whole process in the processing of brittle materials. Results of experiments confirmed the hypothesis that statistical analysis is a procedure that can lead to a decrease in the number of cracks in processing. The measurement was performed with precise instruments and analyzed with recognized software and according to the results obtained, the reduction of the number of cracks is achieved through use of low pressure, a minimum stand-off distance and a small tube diameter. In this way, the paper presents a new and effective tool for optimizing the cutting with a hydro-abrasive jet of marble.

show abstract

“…An important role in assessing the technological quality of the cutting process is played by surface roughness parameters considered in 2D and 3D systems. The most commonly used parameters for assessment of the surface texture in 2D, as presented in works by Srivastava et al [ 27 ], Deaconescu and Deaconescu [ 28 ], and Phokane et al [ 29 ] and defined in the ISO 4287:1997 standard [ 30 ], are the amplitude parameters Ra , Rq , and Rz . The 3D parameters are divided into five groups: amplitude parameters, surface and volume parameters, spatial parameters, hybrid parameters and functional parameters.…”

Section: Introductionmentioning

confidence: 99%

Sequential Smoothing Treatment of Glass Workpieces Cut by Abrasive Water Jet

2022

View full text Add to dashboard Cite

A centrifugal disc and vibratory finishing machines were applied to improve the surface texture of soda-lime workpieces cut by an abrasive water jet. This innovative method was denoted as sequential smoothing treatment. An experimental study of the effect of the smoothing process conditions on the surface roughness, surface texture and micro roughness of the surface of glass workpieces was conducted. The analysis of the results obtained from experimental research made it possible to determine the optimum conditions for the smoothing process of glass workpieces after abrasive water jet cutting process. The proper selection of the finishing machine, machining media (abrasive chips) and compounds (liquids and powders) made it possible to reduce the surface roughness of areas located in the lower part of the cutting zone from Sa = 4.81 μm to Sa = 1.9 μm. The experimental results obtained confirmed the validity of using finishing machines to improve the surface quality of the soda-lime glass components. An important problem that requires further research is the increase in productivity and the reduction in machining time.

show abstract

Response Surface Methods Used for Optimization of Abrasive Waterjet Machining of the Stainless Steel X2 CrNiMo 17-12-2

Cited by 12 publications

References 19 publications

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

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

Reduction of Cracks in Marble Appeared at Hydro-Abrasive Jet Cutting Using Taguchi Method

Sequential Smoothing Treatment of Glass Workpieces Cut by Abrasive Water Jet

Contact Info

Product

Resources

About