Papers by Keyword: Response Surface Methodology

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Authors: K. Rajkumar, L. Poovazhgan, P. Saravanamuthukumar, S. Javed Syed Ibrahim, S. Santosh
Abstract: Aluminium reinforced with SiC, Al2O3 and B4C etc. possesses an attractive combination of properties such as high wear resistance, high strength to weight ratio and high specific stiffness. Among the various reinforced materials used for aluminium, B4C has outperformed all others in terms of hardening effect. Particle size reduction of B4C is found to have positive impact on the material hardness. In the view of physical properties, B4C has less density than that of SiC and Al2O3, which makes it an attractive reinforcement for aluminium and its alloys for light weight applications. In this work, Al nano B4C composite prepared by ultrasonic cavitation method was machined by Abrasive assisted electrochemical machining using cylindrical copper tool electrodes with SiC abrasive medium. In this paper, attempts have been made to model and optimize process parameters in Abrasive assisted Electro-Chemical Machining of Aluminium-Boron carbide nano composite. Optimization of process parameters is based on the statistical techniques using Response Surface Methodology with four independent input parameters such as voltage, current, abrasive concentration and feed rate were used to assess the process performance in terms of material removal rate and surface finish. The obtained results were compared with abrasive assisted electro chemical machining of Aluminium-Boron carbide micro composite and the effect of particle size on the process parameters was analyzed.
Authors: Swapan Barman, Asit Baran Puri, Nagahanumaiah
Abstract: Efficiency of any machining process depends on the effectiveness of final outcomes. Surface integrity plays an important role in functional performance of a part or component. Traditionally, surface roughness is considered to be the principal parameter to assess the surface integrity of a machined surface. In this paper, the influences of machining parameters like gap voltage, capacitance and depth of hole on the surface finish parameters like Ra and Sa of micro holes have been studied in micro electrical discharge drilling. The high aspect ratio blind micro holes were drilled on titanium alloy (Ti-6Al-4V) with cylindrical tungsten tool electrodes. The experimentation was carried out adopting a full factorial design (33). The simultaneous effects of machining parameters on responses were analysed using response surface methodology. Multiple linear regression models were developed for responses to obtain the correlation between machining parameters and machining outputs. Multi-objective optimization has been performed with the aid of the desirability function approach.
Authors: S.T. Selvamani, S. Divagar, M. Vigneshwar
Abstract: In this research work, the friction welding of AISI 1020 grade steel joints are fabricated to predict the minimum Vickers hardness in the joints. The response surface methodology was used to optimize the friction welding parameters in this study. RSM is a collection of mathematical and statistical techniques that are helpful for designing a set of experiments, analyzing the optimum combination of input process parameters, developing a mathematical model, and expressing the values graphically. Therefore, the response surface methodology has been utilized to optimize the friction welding process parameter with the help of ANOVA design matrix. The microstructures analyzed were carried out for the optimized condition joint.
Authors: Nguyen Phu Thuong Nhan, Tran Thien Hien, Le Thi Hong Nhan, Phan Nguyen Quynh Anh, Le Tan Huy, Thi Cam Trinh Nguyen, Duy Trinh Nguyen, Long Giang Bach
Abstract: Response Surface Methodology (RSM) is used to optimize the conditions of the saponification reaction (Concentration of alkaline solution (%), temperature (°C) and reaction time (hour)). Level of foaming and durability of the emulsion (cleaning ability) from the product of the saponification reaction are two factors to evaluate the optimization process by RSM. After optimization, the alkaline solution concentration is 11%, the reaction was carried out for 2.5-3 hours at 85°C for the highest level of foaming and the most prolonged durability of the emulsion. This parameter was compared with the experiment, and the results showed that there was no significant error, this proves that the RSM model has good repeatability, can optimally correct and is essential in optimizing the survey parameters.
Authors: Alejandro Regalado-Méndez, Juan Mentado-Morales, Ever Peralta-Reyes, Carlos Estrada-Vázquez, Gerardo Martínez-Villa, Mario E. Cordero, Luis G. Zárate
Abstract: The application of Response Surface Methodology (RSM) and Central Composite Rotatable Design (CCRD) for modeling and optimization of the influence of three operating variables (mass of catalyst, MeOH/Oil molar ratio, and temperature) on performance of Reactive Vacuum Distillation (RVD) to increase biodiesel yield is discussed in this work. Changes in RVD performance during biodiesel production were evaluated by using RSM and CCRD. A mathematical equation to model biodiesel production by RVD was derived from computer simulation programming by applying a least squares method using MATLAB® v. R2016a. Predicted values were found to be in good agreement with experimental values (with R2 = 0.934). Optimal conditions for the production of ethyl esters were: Temperature: 31.2 °C, MeOH/Oil molar ratio: 5.65:1, and mass of catalyst: 0.1344 g.
Authors: Akindele Okewale, Olusola A. Adesina, Mustapha Oloko-Oba
Abstract: This work focused on optimization of production of ethanol from saw dust using two empirical methods, the ANN and the RSM. It further investigated the modeling and optimization efficiencies of RSM and ANN in separate hydrolysis and fermentation of sawdust for ethanol production. Box - Behnken Design (BBD) was used to generate 17 individual experiments which were carried out, RSM and Genetic Algorithm (GA) of ANN which were used to optimize the production which was then compared. The optimum concentrations of ethanol yield predicted were 56.968 wt. % and 57. 387263 wt. % for RSM and ANN models respectively. R2 value obtained for ANN model was 0.9989 while R2 value of 0.9046 was obtained for RSM model. The Root Mean Square Error (RMSE) value for ANN was found to be 0.143 while the RMSE value for RSM was 2.17. It showed that ANN had relatively higher predictive model ability and thus shows to be a better optimization tool for the ethanol from saw dust compared to RSM which also a good modelling tool.
Authors: Noraiham Mohamad, Mazlin Aida Mahamood, Jeeferie Abd Razak, Rose Farahiyan Munawar, Muhammad Zaimi Zainal Abidin, Mohd Asyadi Azam, Mohd Shahir Kasim, Mohd Shahrizan Othman, Mohammed Iqbal Shueb
Abstract: Natural Rubber/EPDM blends were successfully prepared by direct melt compounding method using an internal mixer. The significance of MAH grafted EPM (MAH-g-EPM) and compounding parameters were studied via the response surface methodology (RSM) using the two-level full factorial design. The MAH-g-EPM loading, mixing temperature, rotor speed and mixing time were selected as four independent variables. Cure characteristics of scorch time, cure time and maximum torque were selected as the responses. The statistical significance of all variables and their interactions during compounding were analysed using ANOVA. The degree of agreement between experimental results with those predicted by the statistical model was confirmed using constant of determination, R2 with values approaching ~0.99. It was observed in the results, that the incorporation of high loading (10 phr) of MAH-g-EPM has predominantly enhanced the scorch safety time of NR/EPDM blends, as well as increased the modulus of NR/EPDM blends to some extent compared to low loading (5 phr and 7.5 phr). These finding were further supported by the Differential Scanning Calorimetry (DSC) analysis.
Authors: Aphichad Phophoung, Viboon Tangwarodomnukun
Abstract: Defects in glassware are unacceptable in terms of product strength and aesthetics. The unsmooth cut rim of glassware can often be found in the laser trimming of excessive part after blow molding process. Such defect is basically not safe to use and has to be rejected from the production, thereby inevitably increasing the manufacturing cost and time. Hence, this research aims to reduce the defect in glassware rim induced by the laser cutting process. A wine glass was used as a workpiece sample in this study. Laser power, laser cutting time and workpiece rotational speed were tested and optimized to reduce the defects by using the response surface methodology. The optimum condition for the laser cutting of wine glass was found to be 225-W laser power, 2.4-s cutting duration and 335-rpm rotational speed.
Authors: S.M. Ravikumar, P. Vijian
Abstract: Welding input process parameters are playing a very significant role in determining the weld bead quality. The quality of the joint can be defined in terms of properties such as weld bead geometry, mechanical properties and distortion. Experiments were conducted to develop models, using a three factor, five level factorial design for 304 stainless steel as base plate with ER 308L filler wire of 1.6 mm diameter. The purpose of this study is to develop the mathematical model and compare the observed output values with predicted output values. Welding current, welding speed and nozzle to plate distance were chosen as input parameters, while depth of penetration, weld bead width, reinforcement and dilution as output parameters. The models developed have been checked for their adequacy. Confirmation experiments were also conducted and the results show that the models developed can predict the bead geometries and dilution with reasonable accuracy. The direct and interaction effect of the process parameters on bead geometry are presented in graphical form.
Authors: Nipun Gosai, Anand Joshi
Abstract: Ti–6Al–4V is widely used in the aerospace, automobile, and biomedical fields, but is a difficult to machine material. Electrical discharge machining (EDM) is regarded as one of the most effective approaches to machining Ti–6Al–4V alloy, since it is a noncontact electro-thermal machining method, and it is independent from the mechanical properties of the processed material. In electro discharge machining (EDM), dielectric plays an important role during machining operation. The machining characteristics are greatly influenced by the nature of dielectric used during EDM machining. In present paper silicon powder suspended kerosene as dielectric is used to explore the influence of these dielectrics on the performance criteria such as material removal rate (MRR), tool wear rate (TWR) and surface roughness (Ra) during machining of titanium alloy (Ti-6Al-4V). Peak current, pulse on time, pulse off time and concentration of powders added into dielectric fluid of EDM were chosen as process parameters to study the PMEDM performance in terms of MRR, TWR and Ra. The experiments were carried out in planning mode on a specially designed experimental set up developed in laboratory. Response surface methodology, employing a face-centered central composite design scheme has been used to plan and analyze the experiments.
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