High strength to weight ratio of aluminium reinforced as metal matrix composites is a well known material used in automotive application. The effects of recycled aluminium chips AA7075 with amorphous silica by rice husk ash on the physical properties and microstructure were investigated. Recycled aluminium chip AA7075 was reinforced with agro waste of amorphous silica rice husk ash i. e., 2.5 %, 5 %, 7.5 %, 10 % and 12.5 %. Samples of these metal matrix composites were prepared by cold compaction method due to the lower energies consumption and operating cost compared to conventional recycling by casting. Physical testing of density, apparent porosity, water absorption and hardness tests of the metal matrix composites samples were examined in the current study. The density of metal matrix composites was increased up to 5 % of amorphous silica, and then decreased with increasing mass fraction of amorphous silica. Porosity and water absorption of metal matrix composites were significantly consistent at increasing mass fraction of amorphous silica, while the hardness of metal matrix composites was increased at increasing amorphous silica. Consequently, the microstructures of metal matrix composites were observed via optical microscope to analyze the dispersion of the reinforced composites. The microstructures of metal matrix composites were found non‐homogeneous and random distribution of amorphous silica and aluminium chip AA7075 compared to 100 % recycled aluminium chip AA7075. Based on investigation to aluminium reinforced rice husk ash composites, it has good potential to improve the material behavior of metal matrix composites by appropriate composition amorphous silica to composite.
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.
One of manufacturing problems in sheet metal forming is springback. This elastic recovery occurs when unloading the formed part off the tooling dies, resulting in shape inaccuracies. Optimizing the geometry surfaces of the tools can be used to accommodate the springback, so that after the unloading process, the formed part meets the target shape. This paper presents an optimization method to modify the geometry surfaces of the tooling dies based on springforward simulations assisted by an automatic surface generator during the process. In the optimization cycle, new sets of upper and lower die surfaces are required. An automatic surface generation method based on normal vector has been developed to create new finite elements of the new surfaces. The normal vector calculation of the deformed elements after springback generates new upper and lower surfaces with uniform gaps. The new generated elements can be used directly during the optimization cycle. For testing and verification purposes, the method is applied in various complicated surfaces. The test results show that this method is able to generate a uniform gap in a corner with 90 degrees angle, without discontinuity in any elements. The application in optimization to minimize the springback is conducted in hatshape problem. The result shows that the automatic mesh generator works effectively during the optimization cycle. The distortion error after springback can be significantly minimized.
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