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

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.

A hybrid approach to artificial bee colony algorithm

2015 ◽  
Vol 27 (2) ◽  
pp. 387-409 ◽  
Author(s):  
Lianbo Ma ◽  
Yunlong Zhu ◽  
Dingyi Zhang ◽  
Ben Niu
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Hybrid Approach ◽  
Bee Colony

Path Planning of Mobile Robot Using Improved Artificial Bee Colony Algorithm

2020 ◽  
Vol 38 (9A) ◽  
pp. 1384-1395
Author(s):  
Rakaa T. Kamil ◽  
Mohamed J. Mohamed ◽  
Bashra K. Oleiwi
Keyword(s):  
Mobile Robot ◽  
Comparative Research ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Dynamic Control ◽  
Computational Time ◽  
Bee Colony ◽  
Shortest Distance ◽  
Minimum Number ◽  
Cubic Polynomial

A modified version of the artificial Bee Colony Algorithm (ABC) was suggested namely Adaptive Dimension Limit- Artificial Bee Colony Algorithm (ADL-ABC). To determine the optimum global path for mobile robot that satisfies the chosen criteria for shortest distance and collision–free with circular shaped static obstacles on robot environment. The cubic polynomial connects the start point to the end point through three via points used, so the generated paths are smooth and achievable by the robot. Two case studies (or scenarios) are presented in this task and comparative research (or study) is adopted between two algorithm’s results in order to evaluate the performance of the suggested algorithm. The results of the simulation showed that modified parameter (dynamic control limit) is avoiding static number of limit which excludes unnecessary Iteration, so it can find solution with minimum number of iterations and less computational time. From tables of result if there is an equal distance along the path such as in case A (14.490, 14.459) unit, there will be a reduction in time approximately to halve at percentage 5%.

Artificial bee colony algorithm with modified search strategy

2013 ◽  
Vol 32 (12) ◽  
pp. 3326-3330
Author(s):  
Yin-xue ZHANG ◽  
Xue-min TIAN ◽  
Yu-ping CAO
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Search Strategy ◽  
Bee Colony
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