Optimization of Parameters in CNC milling of P20 steel using Response Surface methodology and Taguchi Method

Vardhan, M. Vishnu; Sankaraiah, G.; Yohan, M.; Rao, Hanumantha

doi:10.1016/j.matpr.2017.07.273

Cited by 36 publications

(14 citation statements)

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“…A good UAG experiment can not only collect experimental data in different grinding situations but also aid in constructing a high-precision prediction model. The main parameters that affect the CNC machining results are considered in this experiment, including cutting speed, feed rate, axial depth of cut, and radial depth of cut [28]- [29]. In addition, different materials and ultrasonic power will also cause different surface roughness results [30]- [31].…”

Section: B Uag Processing Parameter Designmentioning

confidence: 99%

Parameter Selection and Optimization of an Intelligent Ultrasonic-Assisted Grinding System for SiC Ceramics

2020

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Ceramic grinding processing technology continues to advance rapidly. Recent studies are increasingly adopting ultrasonic-assisted grinding (UAG) for obtaining improved surface quality and reduced surface roughness. Because different grinding parameters could lead to different machining quality, operators may find it difficult to select grinding parameters on the basis of the expected machining quality alone. In this paper, an intelligent UAG system (IUAGS) that provides suitable grinding parameters for the operator is proposed. This IUAGS employs a proposed one-dimensional convolutional neuro-fuzzy network (1DCNFN) to establish a surface roughness prediction model, and then a particle swarm optimization algorithm is used to optimize the grinding parameters. The experimental results demonstrate that our proposed 1DCNFN has a lower mean absolute percentage error (MAPE) in surface roughness prediction than other methods do. Moreover, our IUAGS can provide appropriate UAG parameters on the basis of the specific requirements of the operator. INDEX TERMS Intelligent ultrasonic-assisted grinding system, ultrasonic-assisted grinding, grinding processing, convolutional neural fuzzy network, particle swarm optimization

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Section: B Uag Processing Parameter Designmentioning

confidence: 99%

Parameter Selection and Optimization of an Intelligent Ultrasonic-Assisted Grinding System for SiC Ceramics

2020

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“…The Taguchi Method is a statistical technique used to find the optimum values for the parameters in the experiments and reduce the number of experiments that have to be done [12,13 ]. Optimization of process parameters is done to make a great control to the quality, cost aspects and productivity of the process.…”

Section: 6optimization the Process Parameters Of Hot-wire Cuttingmentioning

confidence: 99%

“…The results have been analyzed by using S/N ratio to obtain the optimal level for each process parameter that has larger effect of the surface quality. The main effect of each parameter with four level on the S/N ratio and mean for material removal are calculated in the tables (6,7), the plot of the S/N ratio and mean is shown in the figure (12,13). Note: there are 4 experiments failed through cutting ,so they neglected in all calculations .…”

Section: Signal To Noise Ratio (S/n)mentioning

confidence: 99%

“…From the tables (12,13 ), the effect of each factor (Rank) can be seen which mean the effect degree of each factor on the result . In addition, the optimal level of the parameters with Dragline is calculated according to the large value of the S/N ratio and mean, so in this case the optimal parameters which effected on the DRAGLINE is density (D), followed by velocity of cut (C) then the wire diameter (B), and wire temperature (A).…”

Section: 13analysis Of the Dragline With The Hot-wire Cutting Parmentioning

confidence: 99%

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Optimization the Parameters of Hotwire Cutting Process to Enhance the Properties of Polystyrene Foam

2019

ISDE

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Hot -Wire cutting process is one of the important method to produce different shapes and prototypes of Extruded Polystyrene (XPS) and Expanded Polystyrene (EPS) material . The study and analysis of Hot-Wire cutting parameters play an important role to enhance the quality and accuracy of the process and products . The effect on the surface has been investigated by using the experimental test which designed according to the Taguchi orthogonal array (OA). In this study, four parameters,(temperature of wire(A) (°C), diameter of wire (B) (mm) , velocity of cutting (C) (mm/min), and density of foam (D)(gm/cm3) , with five levels for each parameter have been used. A full process would require (45 =625) experiments .The design of experiments(DOE)n performed L25(45 ) orthogonal array , which suggested by Taguchi to reduce the high required number of experiments to 25 effected tests. In the present study, the signal to noise (s/n) ratio have been performed for analysis the results , by statistical software(MINITAB17) to establish the optimum condition for a process and estimate the contributions and response under optimum condition. In addition , the analysis of variance (ANOVA) has been performed to identify the significant parameters affected on accuracy and quality.

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“…High stresses in the vicinity of poorly detailed base anchors can rupture the panel wall. Base shear can overcome friction causing the panel to slide [7].…”

Section: Introductionmentioning

confidence: 99%

Seismic Analysis of Electrical Panel

Vardhan*,

Dhanraj,

Reddy

et al. 2019

IJRTE

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Equipments used at nuclear power plants require robust and reliable designs because in case of disaster, such as earthquake, small damage can turn into an unpredictable result. The analysis has been done using Finite Element Method (FEM), a common tool used for the analysis of structures. To conduct seismic analysis, it is necessary to perform modal analysis and calculate response spectrum from the Floor Response Spectrum. In the present project, data is obtained from the modal analysis using ANSYS software for panel assembly structure model. The Floor Response Spectrum (FRS) data for the geographical region where this structure will be mounted is collected. The collected data is given as input to response spectrum analysis where it subjected to these conditions. The output of this analysis determines whether the structure that has been designed is within the safety limit or not. In the present project a 3d model of the Electronic panel assembly structure is modeled using UNIGRAPHICS modeling software. The model is converted to parasolid and imported into Ansys. As a first step modal analysis has been performed to predict the fundamental frequency of the structure. Later dynamic analysis has been performed to evaluate the seismic response of the system under Operation Basis Earthquake (OBE). The response spectra used for OBE in X, Y, Z directions are given as input. The dynamic analysis has been performed to determine the stresses developed in the beam and results obtained have been compared to ASME standards. Based on the results obtained design optimization of the structure has been carried out.

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Optimization of Parameters in CNC milling of P20 steel using Response Surface methodology and Taguchi Method

Cited by 36 publications

References 1 publication

Parameter Selection and Optimization of an Intelligent Ultrasonic-Assisted Grinding System for SiC Ceramics

Parameter Selection and Optimization of an Intelligent Ultrasonic-Assisted Grinding System for SiC Ceramics

Optimization the Parameters of Hotwire Cutting Process to Enhance the Properties of Polystyrene Foam

Seismic Analysis of Electrical Panel

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