In the case of a die-casting process, defects that are difficult to confirm by visual inspection, such as shrinkage bubbles, may occur due to an error in maintaining a vacuum state. Since these casting defects are discovered during post-processing operations such as heat treatment or finishing work, they cannot be taken in advance at the casting time, which can cause a large number of defects. In this study, we propose an approach that can predict the occurrence of casting defects by defect type using machine learning technology based on casting parameter data collected from equipment in the die casting process in real time. Die-casting parameter data can basically be collected through the casting equipment controller. In order to perform classification analysis for predicting defects by defect type, labeling of casting parameters must be performed. In this study, first, the defective data set is separated by performing the primary clustering based on the total defect rate obtained during the post-processing. Second, the secondary cluster analysis is performed using the defect rate by type for the separated defect data set, and the labeling task is performed by defect type using the cluster analysis result. Finally, a classification learning model is created by collecting the entire labeled data set, and a real-time monitoring system for defect prediction using LabView and Python was implemented. When a defect is predicted, notification is performed so that the operator can cope with it, such as displaying on the monitoring screen and alarm notification.

Aluminum High Vacuum Die-casting process has become more prevalent in automotive manufacturing industry which require high productive rate, weldable process and heat treatment process. However, high pressure die castings usually contain gas porosity due mainly to the entrapment of air or gas in the die during the high speed injection of the molten metal into the die cavity. Vacuum block system with disk spring was developed and vacuum chanel was optimized with numerical flow analysis. The porosity of die castings was analyzed by X-ray CT, and the effect of porosity on the mechanical properties was analyzed by hardness and tensile test. Tensile strength was improved 49.5% for 50mbar high vacuum die-casting process compare then 300mbar. And then, Surface property was analyzed with plunger velocity and fast shot set point.

The investigation on the lightweight of automobiles has been underway in commercial vehicles as well as passenger cars due to global warming and strengthening of European emission standards. In this study, the V-arm were developed for lightweight parts using aluminum alloy instead of steel with high pressure die casting processing. This study has focused on lightweight adaptive concept design. Several models of V-arm were designed and analyzed for the fluidity and solidification. V-arm was produced with ADC12 by high pressure die-casting process. The mechanical properties of developed V-arm were measured; such as tensile strength, elongation, shear strength, and durability. The possibility of mass production with the light weight aluminum V-arm substitute from the steel. The weight was reduced about 38% from 16kg to 9.98kg. The productivity was improved with decreasing the process from 8 to 5 by All-in-0ne process using high pressure die-casting.

In this study, the weldability of ADC12 FSW joints obtained by the load control type of the FSW machine is examined. The higher the tool plunge downforce the wider the range of the optimum FSW conditions is obtained. However, there is a limit of optimum range with increasing the tool plunge downforces. The three different types of defects are formed in ADC12 FSW joints, depending on the welding conditions. One is a large mass of flash due to the excess heat input, another is a cavity or groove-like defects caused by insufficient heat input and the other is a cavity caused by the abnormal stirring. As for the abnormal stirring, it is very clearly seen that the shape of the top part on the advancing side in the stir zone is completely different. For this type of defect, the effect of the tool plunge downforce is not significant, though the size of the defect due to insufficient heat input significantly is decreased with the increasing downforce

When manufacturing die casting mold, generally, the casting layout design should be considered based on the relation between injection system, casting condition, gate system, and cooling system. Also, the extent or the location of product defects were dif

When manufacturing die casting mold, generally, the casting layout design should be considered based on the relation between injection systems, casting condition, gating system, and cooling system. Also, the extent or the location of product defects will be differentiated according to the various relations of the above conditions. High-qualified products can be manufactured as those defects are controled by the proper modifications or the changes of die casting mold with the conditions. In this research, the proper manufacturing method intensively be derived for reducing the defect of the internal porosities issues of power steering which is very complicated to achieve the mold design, and for minimizing and for guaranteeing the product quality through the analysis of the problem of casting parts and the deduction of alternative plans.

The effect of the alloy systems Al-Mg alloy and Al-Si alloy in this study on the characteristics of die-casting were investigated using solidification simulation software (MAGMAsoft). Generally, it is well known that the casting characteristics of Al-Mg based alloys, such as the fluidity, feedability and die soldering behaviors, are inferior to those of Al-Si based alloys. However, the simulation results of this study showed that the filling pattern behaviors of both the Al-Mg and Al-Si alloys were found to be very similar, whereas the Al-Mg alloy had higher residual stress and greater distortion as generated due to solidification with a larger amount of volumetric shrinkage compared to the Al-Si alloy. The Al-Mg alloy exhibited very high relative numbers of stress-concentrated regions, especially near the rib areas. Owing to the residual stress and distortion, defects were evident in the Al-Mg alloy in the areas predicted by the simulation. However, there were no visible defects observed in the Al-Si alloy. This suggests that an adequate die temperature and casting process optimization are necessary to control and minimize defects when die casting the Al-Mg alloy. A Tatur test was conducted to observe the shrinkage characteristics of the aluminum alloys. The result showed that hot tearing or hot cracking occurred during the solidification of the Al-Mg alloy due to the large amount of shrinkage.

A research project was conducted to study work-related musculoskeletal disorders (MSDs) at a die-casting plant in Korea. The project was consisted of 4 main parts; education on the topics of MSDs for all workers, symptom survey, medical check-up, investigation of MSD risk factors. The result of symptom survey showed that 89.5% of the respondents complained pains on at least one part of the body. After cross-sectional analysis of various information and risk factors based upon NIOSH criteria, 83.3% of respondents were considered as active health surveillance level 1, and 16% of the respondents were considered as active health surveillance level 2 those are at high risk of having MSDs based upon a criteria developed by Institute of Labor Science at University of Incheon. Also the result of medical examination by a industrial medicine MD showed that 41workers(44.1%) out of 93 workers examined were considered as MSD patient group at moderate level, and 10 workers(10.8%) were considered as MSD patient group at relatively high level that require certain level of medical treatment and ergonomics interventions for their workplace. The analysis of the work environment using various ergonomic investigation techniques revealed that repeated awakard postures(50%) and highly repatitive task(37.5%) were two most contributing risk factors for the on-set of MSD at this work site followed by handling of heavy object(8.3%), and vibration(4.2%).