반용융 성헝에서의 다구찌 방법과 신경망을 이용한 자동차 알루미늄 피스톤의 최적 재가열 과정에 대한 연구

A Study on Optimum Reheating Process of Automotive Aluminum Piston using Neural Network and the Taguchi Method in Semi-Solid forming

As the manufacturing processes of automotive engine piston, gravity die-casting, squeeze casting, hot forging and powder forging process are generally used for the various specifications. As the semi-solid forming(SSF) is compared with conventional casting such as gravity die-casting and squeeze casting for the characteristics of its process, the product without inner defects such as gas porosity and segregation can be obtained and its microstructure is globular grain. In SSF process, the materials are heated up to the temperature between the solvus and liquidus line at which the materials exists in the form of liquid-solid mixture. In this time, Discussion is given about reheating process of row material and results are presented regarding accurate temperature and process variables controlling for right solid fractions.