Parametric Optimization on Plasma Arc Cutting Machine for Aisi 1018 (original) (raw)
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Multi-Objective Optimization of Plasma Arc Cutting Process Using Moora Combined with Ga
ERJ. Engineering Research Journal, 2019
In this work, cutting parameters were optimized in plasma arc cutting process of mild steel by application of multi-objective optimization by ratio analysis (MOORA) method. Standard deviation (SDV) concept has been used to allocate the weight criteria of each objective being reflected. Cutting speed, arc current, and standoff distance were nominated as setting parameters for optimization the kerf characteristics in the straight-slit cutting (kerf taper, dross, surface roughness and maximization of material removal rate). MOORA was used to transform multiple responses into a single characteristic index known as multi performance characteristic index (MPCI). MPCI was modeled by the use of genetic algorithm (GA). With this action an attempt was made to find more precise dependence of MPCI with cutting parameters. Finally, this was followed by optimization of the MPCI in plasma arc cutting using genetic algorithm. This has also been that, SDV-MOORA-GA method has effectively optimized the plasma arc cutting process parameters used in this study.
2019
Modern industries depend on the manipulation of heavy metal with alloys. Differ-ent cutting methods are used to machine raw materials into specified pieces for making infrastructure and machine tools. Plasma arc cutting (PAC), developed in the mid 1950's was predominantly used to cut stainless steel and aluminium al-loys. Optimization of PAC has always been an open research area for researchers. The purpose of the present article is to highlight the application of a multi-criteria decision making (MCDM) based optimization methods employed by different re-searchers to obtain the best parametric combination of cutting parameters. It was observed that the results attained by using Combination of statistical and heuristi-cal method were better than those derived by past researchers who have used only statistical optimization techniques. Better most results can be achieved by using a hybrid optimization technique if a combination of two or more different optimiza-tions techniques used.
In current scenario, with the increase of demand in market for obtain high surface finish and machining of complex shape geometries, conventional machining process are replaced with Non-Conventional machining process. Plasma arc cutting (PAC) is one of the Non-Conventional machining process. This paper explores the effects and multi objective optimization of process variables in PAC, the process parameters considered for optimization are cutting current, cutting speed and Torch height. In this study, martensitic stainless steel (SS) 420 of 10 mm thickness has been used as work piece material. The experimental runs are carried out based on L9 orthogonal array (OA). Surface roughness (Ra) and Material removal rate (MRR) are taken as process responses. The objective of optimization is to achieve minimum surface roughness and high material removal rate simultaneously, for obtaining minimum surface roughness and maximum material removal rate process parameters are optimized based on Grey-Taguchi technique. Analysis of variance (ANOVA) has been carried out to get the contribution of each process parameters on the process responses and finally effects of process variables on Ra and MRR are plotted and studied by using response surface methodology (RSM).
PARAMETRIC OPTIMIZATION ON SS 304L USING PLASMA ARC CUTTING - A REVIEW
Plasma arc cutting is thermal cutting process that makes use of a constricted jet of high temperature plasma gas to melt and separate metal.In this study we choose plasma cutting machine as our main machine tool and SS304L material also used.with the start of globalization there are many company emerges .so there are more then one company make similar product to sustain this competitive market we must make product which quality is good and must have low price.so with the use of optimization technique we must make our product more economical and also save time coast.so that's why we consider some regression analysis RSM and some other optimize technique isused to find out optimim solution for the machine where it give its best performance.the main objective of our research paper is make more efficient operation condition where material removal rate (MRR) is at its higher stage with better surface finish.
VIVA-Tech International Journal for Research and Innovation, 2021
This paper presents an experimental investigation on the optimization and the effect of the cutting parameters on Material Removal Rate (MRR) in Plasma Arc Cutting (PAC) of EN-45A Material using Taguchi L 16 orthogonal array method. Four process variables viz. cutting speed, current, stand-off-distance and plasma gas pressure have been considered for this experimental work. Analysis of variance (ANOVA) has been performed to get the percentage contribution of each process parameter for the response variable i.e. MRR. Based on ANOVA, it has been observed that the cutting speed, current and the plasma gas pressure are the major influencing factors that affect the response variable. Confirmation test based on optimal setting shows the better agreement with the predicted values.
Multi-Response Optimization of Plasma Cutting Parameters using Grey Relational Analysis
Proceedings of the 28th International DAAAM Symposium 2017, 2017
In this paper was performed the optimization of the parameter of the plasma cutting process using Grey relational analysis. Design of experiments were carried out based on Taguchi L9 orthogonal array. Stainless steel X5CrNi18-10 plates with thickness of 5 mm were cut using different cutting speed and plasma gas pressure, while other process parameters were constant. The quality of the cut has been monitored by measuring surface roughness parameter Rz, cut perpendicularity and kerf width. Effect of each process parameter on quality characteristics of cut was shown. Optimal cutting parameters has been obtained by Grey relational analysis (GRA) method.
IOP Conference Series: Materials Science and Engineering, 2018
Plasma arc cutting (PAC) is a high temperature thermal cutting process employed for the cutting of extensively high strength material which are difficult to cut through any other manufacturing process. This process involves high energized plasma arc to cut any conducting material with better dimensional accuracy in lesser time. This research work presents the effect of process parameter on to the dimensional accuracy of PAC process. The input process parameters were selected as arc voltage, standoff distance and cutting speed. A rectangular plate of 304L stainless steel of 10 mm thickness was taken for the experiment as a workpiece. Stainless steel is very extensively used material in manufacturing industries. Linear dimension were measured following Taguchi's L16 orthogonal array design approach. Three levels were selected to conduct the experiment for each of the process parameter. In all experiments, clockwise cut direction was followed. The result obtained thorough measurement is further analyzed. Analysis of variance (ANOVA) and Analysis of means (ANOM) were performed to evaluate the effect of each process parameter. ANOVA analysis reveals the effect of input process parameter upon leaner dimension in X axis. The results of the work shows that the optimal setting of process parameter values for the leaner dimension on the X axis. The result of the investigations clearly show that the specific range of input process parameter achieved the improved machinability.
2017
Now a days, main challenges to metal cutting industries are productivity and quality of product or component. The machining parameter of any machining process highly affects the quality of product. Surface roughness is a key indicator to quality of product or component in turning process. In this paper, the effect of machining parameter on surface roughness (Ra, Rz, Rq) in turning of AISI 4340 steel with uncoated carbide tool is investigated. In addition, the optimum setting of machining parameter is found by using grey relational analysis. The machining parameter selected are cutting speed (100, 120, 140m/min), feed rate (0.15, 0.30, 0.45mm/rev) and nose radius (0.4, 0.8, 1.2mm). General full factorial design is used for experimental plan. Furthermore the experimental results are analyzed using Analysis of variance and modeling is carried out using regression analysis.
A Review on Optimization and Analysis Techniques in Machining
2015
The various techniques used by the researchers to measure the cutting zone temperature during turning through on-line basis are presented. Also, the various techniques used for monitoring the flank wear of cutting inserts by various researchers and scientists were discussed. The findings of the various researchers in the experimental analyses in turning, using Taguchi's DoE are incorporated in this study. The past researches with empirical modeling in metal cutting for the prediction of flank wear, surface roughness and cutting zone temperature and the findings are discussed. The review of the results obtained in optimization of selected parameters in turning using various non traditional optimization techniques are also presented in this chapter. The Taguchi method utilizes the orthogonal arrays from Design of Experiments theory to study a large number of variables with a small number of experiments. The Taguchi method can reduce research and development costs by improving the ...