Industry 4.0 Foundry Data Management and Supervised Machine Learning in Low-Pressure Die Casting Quality Improvement

Abstract

Low-pressure die cast (LPDC) is widely used in high performance, precision aluminum alloy automobile wheel castings, where defects such as porosity voids are not permitted. The quality of LPDC parts is highly influenced by the casting process conditions. A need exists to optimize the process variables to improve the part quality against difficult defects such as gas and shrinkage porosity. To do this, process variable measurements need to be studied against occurrence rates of defects. In this paper, industry 4.0 cloud-based systems are used to extract data. With these data, supervised machine learning classification models are proposed to identify conditions that predict defectives in a rea..