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Luoyang QIBR Bearing Co.,LtdCall us : +86 − −(0379)63968877 // Email us : [email protected]
This paper includes the study of machinability properties of Al6061 alloy by performing various experiments under vertical milling machine using HSS end mill cutter Full-factorial approach was used to conduct the experimentation a regression model was developed using Least Absolute Shrinkage and Selection Operator (Lasso) between the input
Statistical regression modeling and machinability study of hardened AISI 52100 steel using cemented carbide insert International Journal of Industrial Engineering Computations 2017 Multi-attribute decision making parametric optimization and modeling in hard turning using ceramic insert through grey relational analysis: A case study
The developed serrated saw tooth chip of burnt blue colour adversely affects the surface quality Adequacy of the developed statistical regression model has been checked using ANOVA analysis (depending on F value P value and R2 value) and normal probability plot at 95% confidence level The results of optimal parametric combinations may be adopted while turning hardened AISI 52100 steel
2015-6-17The aim of this research is to construct a multivariate adaptive regression splines (MARS) model to identify central segregation in continuous cast steel slabs Multivariate adaptive regression splines (MARS) technique is a form of regression analysis introduced by Jerome Friedman in
2014-12-14Benardos Vosnaikos (2003) classified Modeling techniques broadly into three groups i e experimental models analytical models and Artificial Intelligence (AI)-based models Experimental and analytical models can be developed by using conventional approaches such as the Statistical Regression
Based on statistical analysis multiple quadratic regression model for cutting forces was derived with satisfactory -squared correlation This model proved to be highly preferment for predicting cutting forces 1 Introduction The machinability of composites in turning is studied in terms of tool wear cutting forces temperature and surface
2014-12-14capable of predicting the surface roughness and cutting forces with good accuracy The statistical analysis multiple regression modeling and neural network prediction were performed on MINITAB 16 and MATLAB nntoolbox Keywords: surface roughness ANOVA ANN 1 Introduction Surface Roughness is often a good predictor of
Statistical analysis was conducted to assess the effect of process parameters on the performance characteristics Cutting speed feed rate and radial depth of cut were selected as process parameters while the performance characteristics were cutting forces bouncing-back material removal rate (MRR) and surface integrity in terms of surface
Modeling and analyzing the effects of air-cooled turning on the machinability of Ti-6Al-4V titanium alloy using the cold air gun coolant system Int J Adv Manuf Technol 67 1053-1066 Rusnaldy Paryanto Tony Suryo Utomo Yusuf Umardani 2011
2017-9-1Free Online Library: Multivariate Empirical Modeling of Interaction Effects of Machining Variables on Surface Roughness in Dry Hard Turning of AISI 4140 Steel with Coated CBN Insert Using Taguchi Design by Mechanika Engineering and manufacturing Boron nitride Analysis Hardness Hardness (Materials)
2019-12-17MACHINABILITY STUDIES ON EN47 SPRING STEEL BY OPTIMIZATION TECHNIQUE DURING DRY AND WET CONDITION regression models for the responses are developed From the experimental work concludes that feed rate Modeling and optimization of turning process parameters during the cutting of polymer (POM C)
2016-8-22Machinability studies i e flank wear surface roughness and morphology analysis of chip has been investigated and statistical regression modeling has been developed The test has been conducted based on Taguchi L16 OA taking machining parameters like cutting speed feed and depth of cut
Based on statistical analysis multiple quadratic regression model for cutting forces was derived with satisfactory -squared correlation This model proved to be highly preferment for predicting cutting forces 1 Introduction The machinability of composites in turning is studied in terms of tool wear cutting forces temperature and surface
2014-12-14capable of predicting the surface roughness and cutting forces with good accuracy The statistical analysis multiple regression modeling and neural network prediction were performed on MINITAB 16 and MATLAB nntoolbox Keywords: surface roughness ANOVA ANN 1 Introduction Surface Roughness is often a good predictor of
2020-1-1Regression modeling and comparative analysis on CNC wet-turning of AISI-1055 AISI-4340 steels cutting condition using conventional cutting fluid (flood coolant) and using L9 Taguchi orthogonal array (OA) design A statistical analysis method analysis of variance (ANOVA) was employed to investigate the influence of cutting-parameters on
Statistical regression modeling and machinability study of hardened AISI 52100 steel using cemented carbide insert International Journal of Industrial Engineering Computations 2017 Multi-attribute decision making parametric optimization and modeling in hard turning using ceramic insert through grey relational analysis: A case study
2015-6-17The aim of this research is to construct a multivariate adaptive regression splines (MARS) model to identify central segregation in continuous cast steel slabs Multivariate adaptive regression splines (MARS) technique is a form of regression analysis introduced by Jerome Friedman in
2018-11-1Employed the Taguchi method and Regression analysis to evaluate machinability of AISI A standard statistical technique ANOVA is used for defining the relationship between two or this method is the fundamental modeling technique It is possible for the logic rule of a human being to be formed utilizing fuzzy logic
2018-11-1Employed the Taguchi method and Regression analysis to evaluate machinability of AISI A standard statistical technique ANOVA is used for defining the relationship between two or this method is the fundamental modeling technique It is possible for the logic rule of a human being to be formed utilizing fuzzy logic
2014-12-14capable of predicting the surface roughness and cutting forces with good accuracy The statistical analysis multiple regression modeling and neural network prediction were performed on MINITAB 16 and MATLAB nntoolbox Keywords: surface roughness ANOVA ANN 1 Introduction Surface Roughness is often a good predictor of
2012-12-5composite using regression modeling and optimization by simulated annealing The process parameters considered include cutting speed feed rate and depth of cut The predicted values radial cutting force model is compared with the The results
2012-10-24statistical multiple regression method to derive predictive models for surface roughness in machining of UD-GFRP In this paper Taugchi's DOE approach is used to analyze the effect of turning process parameters - (cutting speed depth of cut cutting environment (dry and wet) and feed rate) are considered 2 EXPERIMENT DETAIL
cutting of carbon fibre-reinforced composites and found that the machinability and surface integrity are mainly controlled by fibre- linear regression modeling is used Also these techniques are effectively used a means of improving the quality of products through the application of statistical and engineering concepts It is a method based
Statistical regression modeling and machinability study of hardened AISI 52100 steel using cemented carbide insert International Journal of Industrial Engineering Computations 2017 Multi-attribute decision making parametric optimization and modeling in hard turning using ceramic insert through grey relational analysis: A case study
TC11 is an α+β heat resistance titanium alloy with high strength to weight ratio good corrosion resistance and high service temperature up to 500C Response Surface Methodology (RSM) is an empirical statistical modeling technique employed for multiple regression analysis using quantitative data obtained from properly designed experiments to solve multivariable equations simultaneously
2019-7-31on statistical analysis multiple quadratic regression model for cutting forces was derived with satisfactory R2-squared correlation This model proved to be highly preferment for predicting cutting forces 1 Introduction The machinability of composites in turning is studied in terms of tool wear cutting forces temperature and surface quality
2017-11-22machinability of Hadfield steel using RMS and ANOVA techniques was presented by Horng et al [13] The study revealed that the flank wear is influenced by the cutting speed while the interaction effect of the feed rate with the nose radius and the corner radius of the tool have statistical significance on obtained surface roughness
cutting of carbon fibre-reinforced composites and found that the machinability and surface integrity are mainly controlled by fibre- linear regression modeling is used Also these techniques are effectively used a means of improving the quality of products through the application of statistical and engineering concepts It is a method based
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