The aim of this work is to improve the accuracy of cold stamping product by accommodating springback. This is a numerical approach to improve the accuracy of springback analysis and die compensation process combining the displacement adjustment (DA) method and the spring forward (SF) algorithm. This alternate hybrid method (HM) is conducted by firstly employing DA method followed by the SF method instead of either DA or SF method individually. The springback shape and the target part are used to optimize the die surfaces compensating springback. The hybrid method (HM) algorithm has been coded in Fortran and tested in two- and three-dimensional models. By implementing the HM, the springback error can be decreased and the dimensional deviation falls in the predefined tolerance range.

Commercially pure (cp) titanium is a relative soft metal and easily broken on friction-wear applications. To improve the hardness of the surface while maintaining the original properties, plasma nitrocarburizing process has been conducted. The effects of the treatment in different temperatures to the surface harness are then studied. In this study, cp titanium plasma nitrocarburizing process is conducted at different temperatures with different process time, i.e. at 350 °C for 3, 4, and 5 hours, and at 450 °C for 2, 3, and 4 hours respectively. Hardness tests are then performed on each specimen by using Micro Vickers Hardness Tester. The hardness values for the plasma specimens nitrocarburizing processes at temperature of 350 °C for process duration of 3 hours, 4 hours, and 5 hours are 74.16 HV, 92.25 HV and 94.41 HV, respectively, while for processes at temperature of 450 °C, the hardness values are 103.70 HV, 121.31 HV, and 126.17 HV for process duration of 2 hours, 3 hours, and 4 hours respectively. Hardness value of specimens which are resulted from the plasma nitrocarburizing process at temperature of 450 °C is higher compared with specimens that are processed at temperature of 350 °C.

One of the surface treatments to improve the hardness of the surface is by ion implantation process. This paper presents an equation to predict the surface hardness with the variable of the process time in ion implantation surface treatment. The hardness of three surfaces data were collected experimentally from various process times, i.e. 140 minutes, 280 minutes and 560 minutes. Lagrange polynomial interpolation was then used to generate quadratic mathematical formula of the surface hardness based on experimental data. The verification results show that the proposed equation accurately predict the surface hardness of commercially pure (cp) titanium under ion implantation process with the error less than 0.5 %. This equation can be used to set the appropriate treatment process time to achieve the expected surface hardness without costly trial experimental settings.