Abstract
Flexibly-reconfigurable roll forming (FRRF) is a novel sheet metal forming technology by which sheet metal is shaped into a desired curvature using reconfigurable rollers and gaps. FRRF is conducive to producing multi-curvature surfaces by controlling the longitudinal strain distribution. However, it is difficult to predict the forming results since FRRF technology forms a secondary surface from the primary curvature. This study investigates the use of regression analysis as a basis for a model that can predict the longitudinal curvature of sheet metal. The following variables were considered as input parameters: Maximum compression value, radius of curvature in the transverse direction, and initial blank width. Regression model samples are obtained by performing experiments using FRRF equipment whilst the experimental design was generated by a three-level, three-factor full factorial design. The experimental surfaces are of a convex and of a saddle-type shape, with a total sample size of 54. Through regression analysis it has been shown that the longitudinal curvature can be expressed by means of a quadratic equation. The matching quadratic function was verified with R-squared values and root-mean-square errors, whilst the normality of the sample data was also verified. To apply the model to the actual forming process, the regression model was converted to deduce the compression characteristics for forming the target surface. Throughout the study, the proposed analytical procedure was validated, and a statistical formula for estimating the longitudinal curvature produced by the FRRF apparatus established.
Highlights
The aerospace and automobile industries are developing rapidly and are well suited to multi-product, small-volume production systems
The maximum and minimum percentage errors were 59.0% and 1.6% respectively. The former value was very high but, even when this was included in the analyses, the mean percentage error resulted in 16.2%, which was lower than the acceptance threshold, indicating that the regression model might still follow the general trend of the Flexibly-reconfigurable roll forming (FRRF) process
A statistical model was developed utilizing a regression analysis to predict the outcome of the FRRF process
Summary
The aerospace and automobile industries are developing rapidly and are well suited to multi-product, small-volume production systems. Metals 2019, 9, 896 mold surface [8,9] In this technique, the size of the product is limited by the size of the forming apparatus, as it is not possible to form a product larger than the experimental machine itself. The FRRF technology utilizes a method to create curved surfaces by using a flexible flexure roller and multiple curvature adjustment punches. Due to the difficulty to picture the target surface in the method employed, a statistical prediction model using a regression analysis is used in this study to predict the forming results of the FRRF process. The regression model is employed to deduce the compression characteristics according to the shape of the target surface, by utilizing the numerical analysis method. This model is compared with the conventional regression model under the same conditions
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