scholarly journals Multi-regression prediction model for surface roughness and tool wear in turning novel aluminum alloy (LM6)/fly ash composite using response surface and central composite design methodology

Author(s):  
Smita Rani Panda ◽  
Ajit Kumar Senapati ◽  
Purna Chandra Mishra
2020 ◽  
Vol 10 (19) ◽  
pp. 6951
Author(s):  
Aurel Mihail Țîțu ◽  
Andrei Victor Sandu ◽  
Alina Bianca Pop ◽  
Ștefan Țîțu ◽  
Dragos Nicolae Frățilă ◽  
...  

For many years, surface has quality received a serious attention due to its influence on various mechanical properties. The main contribution made in this scientific paper is the performance of actual experiments, as well as the experimental processing obtained in order to develop a model for predicting the surface roughness based on the optimization of cutting parameters. The novelty of this paper is brought by the method of obtaining the regression equation of the surface roughness, resulted from a standard end-milling process (standard milling tools, standard milling parameters, recommended by the tool manufacturer, 3 axis CNC machine and standard vice), on aluminum alloy 7136 in temper T76511, through two statistical methods of data analysis. This material is used for the production of extruded parts and is poorly understood for the proposed line of research. This study’s aim is to determine the surface roughness equation obtained by the milling of aluminum alloy 7136 in two ways: using Taguchi′s experimental design once and the other, using the central composite design. The Taguchi method and the central composite design are used to develop an efficient mathematical model to predict the optimal level of certain processing parameters. Using ANOVA analysis, a comparative study of calculated and experimental surface roughness values is carried out. The initial characteristics (surface roughness) and the controlled factors (cutting speed, depth of cut and feed) are analyzed with the Minitab program. Finally, an analysis of the advantages and disadvantages of the two methods used is presented. This study has a great industrial application, since the main task of every manufacturer is to achieve a better quality of the final product with minimal processing time.


Author(s):  
Shao-Hsien Chen ◽  
Chih-Hung Hsu

AbstractThe nickel alloy has good mechanical strength and corrosion resistance at high temperature; it is extensively used in aerospace and biomedical and energy industries, as well as alloy designs of different chemical compositions to achieve different mechanical properties. However, for high mechanical strength, low thermal conductivity, and surface hardening property, the nickel alloy has worse cutting tool life and machining efficiency than general materials. Therefore, how to select the optimum machining parameters will influence the workpiece quality, cost, and machining time. This research will be using a new experimental design methodology to the cutting parameter planning for nickel-based alloy cutting test, and used the uniform design methodology to cutting test to reduce the number of experiments. Three independent variable parameters are set up, including cutting speed, feed rate, and cutting depth, and four dependent variable parameters are set up, including cutting tool wear, surface roughness, machining time, and cutting force. A nickel alloy turning parameter model is built by using regression analysis to further predict the I/O relationship among various combinations of variables. The errors between actual values and prediction values are validated. When the cutting tool wear (VB) is 2.72~6.18%, the surface roughness (Ra) is 4.10~7.72%, the machining time (T) is 3.75~8.82%, and the cutting force (N) is 1.54~7.42%; the errors of various dependent variables are approximately less than 10%, so a high precision estimation model is obtained through a few experiments of uniform design method.


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