Abstract
Tube spinning technology is one of the effective methods of manufacturing large diameter thin-walled shapes. In this research, effects of major parameters of thermo mechanical tube spinning process such as preform's thickness, percentage of thickness reduction, mandrel rotational speed, feed rate, solution treatment time and aging treatment time on the wall thickness changes and process time in thermo-mechanical tube spinning process for fabrication of 2024 aluminum spun tubes using design of experiments (DOE), are studied. The statistical results are verified through some experiments. Results of experimental evaluation are analyzed by variance analysis and mathematic models are obtained. Finally using these models, input parameters for optimum production are achieved.
Highlights
Tube spinning is advanced metal forming process which is used for reducing the wall thickness and increasing the length of tubes without changing their inside diameters
Thinner of initial thickness, small percentage of thickness reduction, slower mandrel rotational speed, lower solution treatment time and higher of feed rate of rollers lead to smaller wall thickness changes
The design of experiments is not correct and there is need to consider the mean input parameters in 3 or more levels. Another parameter which is very important in table analysis of variance (ANOVA) is the lack of fitness which shows the correctness of regression analysis of the process time
Summary
Tube spinning is advanced metal forming process which is used for reducing the wall thickness and increasing the length of tubes without changing their inside diameters. There are two different methods, forward and backward tube spinning, depending upon the relative directions of the material flow and the roller travel. The influences of perform's thickness, percentage of thickness reduction, mandrel rotational speed, feed rate, solution and aging treatment time on process time and wall thickness changes for fabricating 2024 aluminum tubes using DOE has been studied. The DOE is a statistical method which is used to find the significance of interactive effects among variables and relations among process parameters using variance analysis Using this model and suitable time of process, input parameters has been achieved for optimum production
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