Sheet thinning prediction method based on localized friction effect in deep-drawing

Abstract

The paper investigated the effect of localized friction on sheet thinning under lubricated conditions in the deep-drawing process. The Finite Element Analysis (FEA) was used to evaluate the sheet thinning of the AISI 304 sheet under six segmented blank-sheet interfaces. Different values of variable coefficient of friction (VCOF) in each segmented area were investigated, and the sheet thickness values at the considered areas were measured. The regression analysis models (Linear Regression, Response Surface Method, and Polynomial Regression) was used to determine the relationships between VCOF and sheet thinning. The results showed that the Linear Regression showed the best fit. The significant factor analysis was also carried out to determine how the localized friction affected the sheet thinning. The contributions of VCOF from at least two segmented areas affected the sheet thinning at any particular location. The obtained relationships of the VCOF and sheet thinning could be beneficial for the localized friction control for highly complex shapes.

Numerical Prediction of the Influence of Process Parameters and Process Set-Up on Damage Evolution during Deep Drawing of Rectangular Cups

“…In the past, many investigations were conducted to identify influencing factors of the deep drawing process, e.g., friction, blank holder force, blank shape, and punch velocity [20]. Most of the work is aimed at producing a component that is free of defects at the macroscopic level for instance considering wrinkling [21,22], sheet thinning [23], and springback [24,25]. Besides that, efforts have been made to numerically predict damage occurrence during deep drawing.…”

Numerical analysis of the load paths and the resulting damage evolution during deep drawing of dual-phase steel

“…in Chen et al [8], sheet thinning, e.g. in Preedawiphat et al [9], or springback, e.g. in Durmaz et al [10] or Nanu et al [11].…”

Predicting and improving the novel process parameters involved in deep drawing process of Inconel 718 sheet at room temperature using hybrid DNN-SSO approach

“…Mostafapour et al 25 proposed a systematic methodology for developing a second order statistical model and showed the relationship between drawing depth and input variables such as frequency of blank holder, amplitude of blank holder movement, and velocity of punch movement. Preedawiphat et al 26 carried out significant factor analysis to explain how localized friction coefficient impacts the sheet thinning. The obtained relationship of the variable coefficient of friction and sheet thinning was found beneficial for forming highly complex parts.…”