scholarly journals Prediction and Analysis of Multi-Response Characteristics on Plasma Arc Cutting of Monel 400™ Alloy Using Mamdani-Fuzzy Logic System and Sensitivity Analysis

Materials ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 3558
Author(s):  
Rajamani Devaraj ◽  
Emad Abouel Nasr ◽  
Balasubramanian Esakki ◽  
Ananthakumar Kasi ◽  
Hussein Mohamed
Keyword(s):  
Sensitivity Analysis ◽  
Fuzzy Logic ◽  
Metal Cutting ◽  
Removal Rate ◽  
Cutting Speed ◽  
Average Error ◽  
Plasma Arc ◽  
Plasma Arc Cutting ◽  
Response Characteristics ◽  
Monel 400

Nickel-based alloys, especially Monel 400™, is gaining its significance in diverse applications owing to its superior mechanical properties and high corrosion resistance. Machining of these materials is extremely difficult through the traditional manufacturing process because of their affinity to rapid work hardening and deprived thermal conductivity. Owing to these difficulties a well-established disruptive metal cutting process namely plasma arc cutting (PAC) can be widely used to cut the sheet metals with intricate profiles. The present work focuses on an intelligent modeling of the PAC process and investigation on the multi-quality characteristics of PAC parameters using the fuzzy logic approach. The Box-Behnken response surface methodology is incorporated to design and conduct the experiments, and to establish the relationship between PAC parameters such as cutting speed, gas pressure, arc current, and stand-off distance and responses which include the material removal rate (MRR), kerf taper (KT), and heat affected zone (HAZ). The quadratic regression models are developed and their performances are assessed using the analysis of variance (ANOVA). Fuzzy set theory-based models are formulated to predict various responses using the Mamdani approach. Fuzzy logic and regression results are compared with the experimental data. A comparative evaluation predicted an average error of 0.04% for MRR, 0.48% for KT, and 0.46% for HAZ, respectively. The effect of variations in PAC process parameters on selected responses are estimated through performing the sensitivity analysis.

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.

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.

Measurement and optimization of multi-response characteristics in plasma arc cutting of Monel 400™ using RSM and TOPSIS

Measurement ◽  
2019 ◽  
Vol 135 ◽  
pp. 725-737 ◽  
Author(s):  
K. Ananthakumar ◽  
D. Rajamani ◽  
E. Balasubramanian ◽  
J. Paulo Davim
Keyword(s):  
Plasma Arc ◽  
Plasma Arc Cutting ◽  
Response Characteristics ◽  
Monel 400

scholarly journals A Hybrid Approach of ANFIS—Artificial Bee Colony Algorithm for Intelligent Modeling and Optimization of Plasma Arc Cutting on Monel™ 400 Alloy

Materials ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 6373
Author(s):  
Mahalingam Siva Kumar ◽  
Devaraj Rajamani ◽  
Emad Abouel Nasr ◽  
Esakki Balasubramanian ◽  
Hussein Mohamed ◽  
...  
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Hybrid Approach ◽  
Cutting Speed ◽  
Gas Pressure ◽  
Plasma Arc ◽  
Plasma Arc Cutting ◽  
Response Characteristics ◽  
Bee Colony ◽  
Arc Current

This paper focusses on a hybrid approach based on genetic algorithm (GA) and an adaptive neuro fuzzy inference system (ANFIS) for modeling the correlation between plasma arc cutting (PAC) parameters and the response characteristics of machined Monel 400 alloy sheets. PAC experiments are performed based on box-behnken design methodology by considering cutting speed, gas pressure, arc current, and stand-off distance as input parameters, and surface roughness (Ra), kerf width (kw), and micro hardness (mh) as response characteristics. GA is efficaciously utilized as the training algorithm to optimize the ANFIS parameters. The training, testing errors, and statistical validation parameter results indicated that the ANFIS learned by GA outperforms in the forecasting of PAC responses compared with the results of multiple linear regression models. Besides that, to obtain the optimal combination PAC parameters, multi-response optimization was performed using a trained ANFIS network coupled with an artificial bee colony algorithm (ABC). The superlative responses, such as Ra of 1.5387 µm, kw of 1.2034 mm, and mh of 176.08, are used to forecast the optimum cutting conditions, such as a cutting speed of 2330.39 mm/min, gas pressure of 3.84 bar, arc current of 45 A, and stand-off distance of 2.01 mm, respectively. Furthermore, the ABC predicted results are validated by conducting confirmatory experiments, and it was found that the error between the predicted and the actual results are lower than 6.38%, indicating the adoptability of the proposed ABC in optimizing real-world complex machining processes.

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

Grey-Based Taguchi Analysis Approach for Optimization of Multi-Objective Problem

2014 ◽  
pp. 219-239
Author(s):  
Nirmal S Kalsi ◽  
Rakesh Sehgal ◽  
Vishal S. Sharma
Keyword(s):  
Feed Rate ◽  
Metal Cutting ◽  
Cutting Tool ◽  
Removal Rate ◽  
Cutting Speed ◽  
Optimization Techniques ◽  
Depth Of Cut ◽  
Multi Objective ◽  
Analysis Technique ◽  
Grey Relation

Due to the increase in complexity and expectations of more reliable solutions for a problem, the importance of multi-objective problem solutions is increasing day by day. It can play a significant role in making a decision. In the present approach, many combinations of the optimization techniques are proposed by the researchers. These hybrid evolutionary methods integrate positive characteristics of different methods and show the advantage to reach global optimization. In this chapter, Taguchi method and the GRA (Grey Relation Analysis) technique are pronounced and used to optimize a multi-objective metal cutting process to yield maximum performance of tungsten carbide-cobalt cutting tool inserts in turning. L18 orthogonal array is selected to analyze the effect of cutting speed, feed rate, and depth of cut using cryogenically treated and untreated inserts. The performance is evaluated in terms of main cutting force, power consumption, tool wear, and material removal rate using main effect plots of S/N (Signal to Noise) ratios. This chapter indicates that the grey-based Taguchi technique is not only a novel, efficient, and reliable method of optimization, but also contributes to satisfactory solution for multi-machining objectives in the turning process. It is concluded that cryogenically treated cutting tool inserts perform better. However, the feed rate affects the process performance most significantly.

Effect of WEDM process parameters on machinability of Nimonic75 alloy using brass wire

2020 ◽  
Vol 17 (3) ◽  
pp. 389-397
Author(s):  
Harvinder Singh ◽  
Vinod Kumar ◽  
Jatinder Kapoor
Keyword(s):  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Content Type ◽  
Response Characteristics ◽  
Nickel Based Alloy ◽  
Pulse On Time ◽  
Pulse Off Time

Purpose This study aims to investigate the influence of process parameters of wire electrical discharge machining (WEDM) of Nimonic75. Nimonic75 is a Nickel-based alloy mostly used in the aerospace industry for its strength at high temperature. Design/methodology/approach One factor at a time (OFAT) approach has been used to perform the experiments. Pulse on time, pulse off time, peak current and servo voltage were chosen as input process parameters. Cutting speed, material removal rate and surface roughness (Ra) were selected as output performance characteristics. Findings Through experimental work, the effect of process parameters on the response characteristics has been found. Results identified the most important parameters to maximize the cutting speed and material removal rate and minimize Ra. Originality/value Very limited research work has been done on WEDM of Nickel-based alloy Nimonic75. Therefore, the aim of this paper to conduct preliminary experimentation for identifying the parameters, which influence the response characteristics such as material removal rate, cutting speed, Ra, etc. during WEDM of Nickel-based alloy (Nimonic75) using OFAT approach and found the machinability of Nimonic75 for further exhaustive experimentation work.

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.

A Numerical Simulation for Temperature Field of Plasma Arc Cutting Ceramics

2007 ◽  
Vol 280-283 ◽  
pp. 1811-1814
Author(s):  
Wen Ji Xu ◽  
Jian Cheng Fang ◽  
T. Wang ◽  
F. Liu
Keyword(s):  
Temperature Field ◽  
Influence Factors ◽  
Cutting Speed ◽  
Processing Parameters ◽  
Difficult Problem ◽  
Ceramic Plate ◽  
Plasma Arc ◽  
Conduction Model ◽  
Plasma Arc Cutting ◽  
Arc Power

To solve the difficult problem of selecting processing parameters of plasma arc cutting ceramic (PACC), the heat conduction model of PACC has been established and the calculating formulations of temperature field have been derived. Then, the distributions and influence factors, such as arc power, cutting speed and workpiece thickness, of temperature field of the ceramic plate and the anode plate have been studied. Based on the work above, the required arc power can be calculated. Moreover, the relation between thickness of ceramic plate and anode plate can be determined, which provides a helpful reference for selecting the thickness of additional anode plate.

scholarly journals An Experimental Analysis of Cutting Quality in Plasma Arc Machining

2020 ◽  
Vol 45 (1) ◽  
pp. 1-8
Author(s):  
Marin Gostimirović ◽  
Dragan Rodić ◽  
Milenko Sekulić ◽  
Andjelko Aleksić
Keyword(s):  
Cutting Speed ◽  
Kerf Width ◽  
Machining Accuracy ◽  
Maximum Height ◽  
Machining Parameters ◽  
Plasma Arc ◽  
Low Carbon ◽  
Plasma Arc Cutting ◽  
Machining Quality

Plasma arc cutting (PAC) is an unconventional process widely used in manufacturing of heavy plate products. This work reports on the research results of machining quality of the workpiece in the plasma arc cutting on the low carbon low alloy steel. An experimental investigation of the characteristics of machining accuracy and surface integrity was carried out for basic machining parameters (cutting speed, arc current, arc voltage, plasma gas pressure, stand-off distance and nozzle diameter). The kerf geometry was determined with three accuracy parameters (top kerf width, bottom kerf width and kerf taper angle). The parameters of deviation present due to plasma curvature were defined by drag and pitch of drag line. The surface roughness was determined with two main roughness parameters through scanning the surface topography (roughness average and maximum height of the profile). The surface properties were determined over microstructure in heat affected zone (HAZ). The results show an acceptable machining quality of the PAC, so that this process is an excellent choice for fast and efficient material removal. However, the plasma arc cutting is not suitable for the final machining because of the metallurgical variations in the HAZ.

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