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.
This article presents experimental data on oil palm biomass (oil palm leaves, oil palm trunk and empty fruit bunch) handsheet production characterization by biodelignification treatment using Bacillus cereus extracted from termite gut (Coptotermus curvignathus). It associates the lignocellulose chemical composition obtained via technical association pulp and paper industry TAPPI T 222 om-02 testing on lignin content reduction determination, holocellulose and hemicellulose content determination (Kurscher-Hoffner method). Several data obtained for handsheet characterization presents brightness, opacity, contrast ratio, din transparency, thickness, bursting and tearing indexes are collected. Handsheet surface morphology was also observed on ratio of gaps differences between fiber bonding conducted using scanning electron microscope (SEM) and ImageJ software. The raw data findings supplement chemical composition analysis for both untreated and treated substrates on handsheet quality performance check as presented in the research article "Bio-Mechanical Pulping of Bacteria Pre-Treatment on Oil Palm Biomass for Handsheet Production" [1]. For understanding correlations into the difference among lignocellulose content composition which affect the handsheet formation and mechanical strength refer to article from this research [1]. This dataset is made publicly available for optimizing alternative waste material reuse in the pulp and paper industrial section.