Studies on die filling of A356 Al alloy and development of a steering knuckle component using rheo pressure die casting system

In this study, a computational fluid dynamics (CFD) model is developed to investigate die filling of semi solid slurry as part of rheo pressure die casting (RPDC) system. The die filling cavity corresponds to that of an automobile steering knuckle, and the slurry is made of A356 aluminium alloy. The rheological model used in the CFD simulation is determined experimentally. The results obtained from present numerical model includes flow field of the slurry within the die cavity, viscosity evolution, solid fraction distribution, temperature and pressure distribution during solidification within cavity during die filling stage. The main objective of the study is to determine the gating arrangement, pouring temperature, and injection conditions for desirable microstructure and mechanical properties of the developed component. To study the effect of injection conditions on die filling capability of the said alloy slurry, five injection profiles are studied, with a variation in final injection velocity between 2–3.2 m/s. In order to corroborate the findings of the present study, microstructural morphology and structure-property correlation have been studied, primarily in the form of optical microscopy and macro hardness measurements, by obtaining samples from different locations of the solidified component

Investment for process quality improvement and setup cost reduction in an imperfect production process with warranty policy and shortages

Cost reduction for setup and improvement of processes quality are the main target of this research along with free minimal repair warranty for an imperfect production System. This paper deals with the effect of setup cost reduction and process quality improvement on the optimal production cycle time for an imperfect production process with free product minimal repair warranty. Here the production system is subject to a random breakdown from an controlled system to an out-of-control state. Shortages are fully backlogged. The main target to minimize the total cost by simultaneously optimizing the production run time, setup cost, and process quality. A solution algorithm with some numerical experiments are provided such as the proposed model can illustrate briefly. Sensitivity analysis section is decorated for the optimal solution of the model with respect to major cost parameters of the system are carried out, and the implications of the analysis are discussed