The Study of Surface Roughness and MRR of Mild Steel Using Manual Plasma Arc Cutting Machining

2012 ◽  
Vol 576 ◽  
pp. 3-6 ◽  
Author(s):  
R. Bhuvenesh ◽  
M.S. Abdul Manan ◽  
M.H. Norizaman
Keyword(s):  
Surface Roughness ◽  
Removal Rate ◽  
Cutting Process ◽  
Material Surface ◽  
Plasma Arc ◽  
Manufacturing Companies ◽  
Average Roughness ◽  
Plasma Arc Cutting ◽  
Before And After ◽  
Manual Plasma

Manufacturing companies define the qualities of thermal removing process based on the dimension and physical appearance of the cutting material surface. Therefore, the roughness of the surface area of the cutting material and the rate of the material being removed during the manual plasma arc cutting process was importantly considered. Plasma arc cutter Selco Genesis 90 was used to cut the specimens made from Standard AISI 1017 Steel manually based on the selected parameters setting. Two different thicknesses of specimens with 3mm and 6mm were used. The material removal rate (MRR) was measured by determining the weight of the specimens before and after the cutting process. The surface roughness (SR) analysis was conducted to determine the average roughness (Ra) value. Taguchi method was utilized as an experimental layout to obtain MRR and Ra values. The results reveal that for the case of manual plasma arc cutting machining, the SR values are inversely proportional to the MRR values. The quality of the surface roughness depends on the dross peak that occurred during the cutting process.

Optimization of Process Parameters in Plasma Arc Cutting Applying Genetic Algorithm and Fuzzy Logic

2018 ◽  
pp. 123-139
Author(s):  
Nehal Dash ◽  
Apurba Kumar Roy ◽  
Sanghamitra Debta ◽  
Kaushik Kumar
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
Fuzzy Logic ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Plasma Arc ◽  
Plasma Arc Cutting ◽  
Optimization Of Process Parameters

Plasma Arc Cutting (PAC) process is a widely used machining process in several fabrication, construction and repair work applications. Considering gas pressure, arc current and torch height as the inputs and among all possible outputs, in the present work Material Removal Rate and Surface Roughness would be considered as factors that determines the quality, machining time and machining cost. In order to reduce the number of experiments Design of Experiments (DOE) would be carried out. In later stages applications of Genetic Algorithm (GA) and Fuzzy Logic would be used for Optimization of process parameters in Plasma Arc Cutting (PAC). The output obtained would be minimized and maximized for Surface Roughness and Material Removal Rate respectively using Genetic Algorithm (GA) and Fuzzy Logic.

PREDICTIVE MODELING OF SURFACE ROUGHNESS, MATERIAL REMOVAL RATE AND KERF USING MULTIPLE REGRESSION ANALYIS IN PLASMA ARC CUTTING PROCESS OF HARDOX AND ABREX STEEL

2020 ◽  
Vol 27 (09) ◽  
pp. 1950206
Author(s):  
DEEPAK KUMAR NAIK ◽  
KALIPADA MAITY
Keyword(s):  
Surface Roughness ◽  
Multiple Regression ◽  
Material Removal Rate ◽  
Material Removal ◽  
Metal Cutting ◽  
Removal Rate ◽  
Cutting Speed ◽  
High Strength ◽  
Plasma Arc ◽  
Plasma Arc Cutting

Plasma arc cutting (PAC) process is widely used in metal cutting industries and modern fabrication units. Precise cutting of high strength material is still a challenging task to the industries. PAC process uses thermal energy to melt the material through highly energized plasma gas. Mostly, “hard-to-cut” type materials is used to cut through this process to meet the demands. The present work proposes an experimental investigation of PAC process of hardox 400 and abrex 400. Both the materials are high strength and high abrasion resistance in nature. Experiments were conducted based on Taguchi’s L[Formula: see text] orthogonal array design. The cutting parameters analyzed were arc current, cutting speed, stand-off distance and supply gas pressure whereas material removal rate, kerf and surface roughness were selected as responses. Also, a prediction model was developed to estimate the responses using multiple regression analysis. A comparison between experimental and predicted result shows the accuracy of the model. Analysis of variance (ANOVA) was used to verify the effect of each parameter on the surface quality to be assessed.

scholarly journals Effect of Process Parameters on the Surface Roughness and Kerf Width of Mild Steel during Plasma Arc Cutting Using Response Surface Methodology

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Ekhaesomi A Agbonoga ◽  
Oyewole Adedipe ◽  
Uzoma G Okoro ◽  
Fidelis J Usman ◽  
Kafayat T Obanimomo ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Analysis Of Variance ◽  
Process Parameters ◽  
Cutting Speed ◽  
Gas Pressure ◽  
Kerf Width ◽  
Plasma Arc ◽  
Plasma Arc Cutting

This study investigated the effects of process parameters of plasma arc cutting (PAC) of low carbon steel material using analysis of variance. Three process parameters, cutting speed, cutting current and gas pressure were considered and experiments were conducted based on response surface methodology (RSM) via the box-Behnken approach. Process responses viz. surface roughness (Ra) and kerf width of cut surface were measured for each experimental run. Analysis of Variance (ANOVA) was performed to get the contribution of process parameters on responses. Cutting current has the most significant effect of 33.43% on the surface roughness and gas pressure has the most significant effect on  kerf width of  41.99% . For minimum surface roughness and minimum kerf width, process parameters were optimized using the RSM. Keywords: Cutting speed, cutting current, gas pressure,   surface roughness, kerf width

Monitoring of plasma arc cutting process by cutting sound

2006 ◽  
Vol 11 (6) ◽  
pp. 701-706
Author(s):  
K. Kusumoto ◽  
Q. G. Chen ◽  
W. Xue
Keyword(s):  
Cutting Process ◽  
Plasma Arc ◽  
Plasma Arc Cutting

Study on Polishing Technology for Hard-Brittle Materials by a Micro Abrasive Water Jet

2014 ◽  
Vol 1027 ◽  
pp. 52-57 ◽  
Author(s):  
Zeng Wen Liu ◽  
R.Y. Liu
Keyword(s):  
Surface Roughness ◽  
Surface Quality ◽  
Silicate Glass ◽  
Material Removal ◽  
Brittle Materials ◽  
Material Surface ◽  
Abrasive Water Jet ◽  
Removal Mechanism ◽  
Material Removal Mechanism ◽  
Average Roughness

s: Abrasive jet micromachining is considered as a promising precision processing technology for brittle materials such as silicate glass and silicon nitride that are increasingly used in various applications. In this study, some polishing experiments are conducted for hard-brittle materials by a micro slurry jet. The results show that the morphology and the integrity of the material surface are improved greatly after polishing. The average roughness (Ra) value of the silicate glass decrease from 2.32μm to 0.35μm and the average roughness (Ra) value of the Si3N4 decrease from 2.63μm to 0.34μm. The material removal mechanism and the surface formation mechanism are studied. The factors to influence the surface morphology, the surface quality and the surface roughness are analyzed in order to take measures to improve the surface quality and reduce the surface roughness value.

scholarly journals THE INFLUENCE OF FEED RATE ON SURFACE ROUGHNESS OF TIC–WC CARBIDE AND AL2O3 CERAMICS SAWN-OFF WITH INNER EDGE OF DIAMOND DISC

2010 ◽  
Vol 2 (4) ◽  
pp. 88-90
Author(s):  
Raimundas Mikolaitis ◽  
Valdas Bukauskas ◽  
Vadim Mokšin ◽  
Vytautas Striška
Keyword(s):  
Surface Roughness ◽  
Grain Size ◽  
Tungsten Carbide ◽  
Feed Rate ◽  
Aluminium Oxide ◽  
Cutting Process ◽  
Feed Speed ◽  
Average Roughness ◽  
Cutting Machine ◽  
Diamond Disc

The paper presents results of measurements of surface roughness of titanium-tungsten carbide (T14K8) and aluminium oxide (Al2O3) ceramics surfaces sawn-off with inner edge of diamond disc. The cutting process was performed by cutting machine “АЛМАЗ-4” with 60/40 grain size disc. The dependence of average roughness Ra of the sawn-off surface on feed speed of the workpiece was established.

Study on Fuzzy-Neural Network for Inverted Plasma Arc Cutting Power Supply

2008 ◽  
Vol 392-394 ◽  
pp. 735-742
Author(s):  
Bo You ◽  
De Li Jia ◽  
Feng Jing Zhang
Keyword(s):  
Neural Network ◽  
Fuzzy Control ◽  
Power Supply ◽  
Fuzzy Neural Network ◽  
Cutting Process ◽  
Experimental Result ◽  
Plasma Arc ◽  
Cutting Power ◽  
Plasma Arc Cutting ◽  
Fuzzy Neural

A variable interval fuzzy quantification algorithm with self-adjustable factor in full domain is proposed in this paper. It focuses on digital inverted plasma arc cutting power and studies strong nonlinearity and uncertainty of power. The neural network is also introduced to decouple cutting parameters variables in the multi-parameters coupling cutting process. This algorithm avoids complex nonlinear system modeling and realizes real-time and effective online control of cutting process by combining advantages of fuzzy control and neural network control. Furthermore, the optimized fuzzy control improves steady-state precision and dynamic performance of system simultaneously. The experimental result shows that this control improves precision, ripples, finish and other comprehensive index of work piece cut, and plasma arc cutting power supply based on fuzzy-neural network has excellent control performance.

scholarly journals Pengaruh Kecepatan Pemotongan dan Ketebalan Bahan Terhadap Kekerasan dan Kekasaran Permukaan Baja AISI 1045 Menggunakan CNC Plasma Arc Cutting

2019 ◽  
Vol 4 (2) ◽  
pp. 93-98
Author(s):  
Ami Rima Rahmawati ◽  
Samsudin Anis ◽  
Rusiyanto Rusiyanto
Keyword(s):  
Surface Roughness ◽  
Cutting Speed ◽  
Surface Hardness ◽  
Hardness Test ◽  
Plasma Arc ◽  
Plasma Arc Cutting ◽  
Material Thickness ◽  
Aisi 1045 Steel ◽  
Aisi 1045 ◽  
1045 Steel

This experimental study aims to determine the effect of cutting speed and material thickness on the surface hardness and roughness resulting from the cutting of AISI-1045 steel using CNC Plasma Arc Cutting. The data analysis technique being used was descriptive statistics. The variables of cutting the AISI-1045 steel for the cutting speeds are 75 mm/min, 100 mm/min, and 125 mm/min. The variables for material thickness are 5 mm, 9 mm, and 13 mm. The experiment carried out were the hardness test using Micro-hardness Tester M800 and roughness test using Surfcorder SE-1700. The results show that the lower the cutting speed, the higher the surface hardness and roughness value, and vice versa. The great thickness of the material, the hardness produced and the roughness value is higher. When the cutting speed and thickness of the material value are high, the workpiece cannot be cut off. The lowest hardness and surface roughness values were 261.33 HV and 10.3 µm, respectively, using a cutting speed of 125 mm/min and the material thickness of 5 mm. The highest hardness value is 319.66 HV, using a cutting speed of 75 mm/min and a material thickness of 13 mm. The highest surface roughness value is 26.8 µm, which were obtained using a cutting speed of 75 mm/min and material thickness of 9 mm.Penelitian ini bertujuan untuk mengetahui pengaruh kecepatan pemotongan dan ketebalan bahan terhadap kekerasan dan kekasaran permukaan hasil pemotongan baja AISI-1045 menggunakan CNC Plasma Arc Cutting. Penelitian ini menggunakan metode eksperimen dan teknik analisis data yang digunakan adalah statistika deskriptif pada pemotongan baja AISI-1045 dengan kecepatan pemotongan 75 mm/min, 100 mm/min, 125 mm/min dan tebal bahan 5 mm, 9 mm, dan 13 mm. Pengujian kekerasan dilakukan menggunakan microhardness terster M800 dan pengujian kekasaran dilakukan menggunakan Surfcorder SE-1700. Hasil penelitian menunjukkan bahwa semakin rendah kecepatan pemotongan maka nilai kekerasan semakin tinggi dan nilai kekasaran permukaan semakin tinggi atau sebaliknya. Semakin besar ketebalan bahan yang digunakan maka nilai kekerasan yang dihasilkan semakin tinggi dan nilai kekasaran semakin tinggi atau sebaliknya. Semakin tinggi kecepatan pemotongan dan ketebalan bahan, benda kerja tidak dapat terpotong. Nilai kekerasan dan kekasaran permukaan paling rendah yaitu 261,33 HV dan 10,3 µm dengan kecepatan pemotongan 125 mm/min dan ketebalan bahan 5 mm. Nilai kekerasan yang paling tinggi yaitu 319,66 HV dengan menggunakan kecepatan pemotongan 75 mm/min dan ketebalan bahan 13 mm dan nilai kekasaran permukaan paling tinggi yaitu 26,8 µm dengan kecepatan pemotongan 75 mm/min dan ketebalan bahan 9 mm.

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