A Fuzzy Model for Predicting Surface Roughness in Plasma Arc Cutting of AISI 4140 Steel

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

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

Soft Computing Techniques and Applications in Mechanical Engineering - Advances in Mechatronics and Mechanical Engineering ◽

10.4018/978-1-5225-3035-0.ch005 ◽

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.

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Factors Affecting Optimal Surface Roughness of AISI 4140 Steel in Turning Operation Using Taguchi Experiment

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/306/1/012099 ◽

2018 ◽

Vol 306 ◽

pp. 012099

Author(s):

O Novareza ◽

D H Sulistiyarini ◽

R Wiradmoko

Keyword(s):

Surface Roughness ◽

Turning Operation ◽

Factors Affecting ◽

Aisi 4140 Steel ◽

Aisi 4140 ◽

Optimal Surface

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Feed rate affecting surface roughness and tool wear in dry hard turning of AISI 4140 steel automotive parts using TiN+AlCrN coated inserts

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/307/1/012024 ◽

2018 ◽

Vol 307 ◽

pp. 012024 ◽

Cited By ~ 1

Author(s):

Phacharadit Paengchit ◽

Charnnarong Saikaew

Keyword(s):

Surface Roughness ◽

Tool Wear ◽

Feed Rate ◽

Hard Turning ◽

Aisi 4140 Steel ◽

Aisi 4140 ◽

Automotive Parts

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

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.576.3 ◽

2012 ◽

Vol 576 ◽

pp. 3-6 ◽

Cited By ~ 1

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.

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