Die Casting Process Using Automated Machine Learning

Abstract

Castings that are near to net forms are made using the extremely complex manufacturing technique known as die casting. Despite the method's lengthy history—more than a century—a system engineering method for characterizing it as well as the information that each cycle of die casting can create has not yet been completed. Instead, a tiny subset of knowledge deemed to be essential for die castings has attracted the attention of industry and academia. The majority of the research that has been published on artificial intelligence in die casting has a specific focus, which restricts its usefulness and efficacy in an industrial casting. This study will examine the die casting process through the perspective of systems design and show practical uses of machine learning. In terms of technical definition and how people interact with the system, the die casting process satisfies the criteria for complex systems. The die casting system is an adaptive, self-organizing network structure, according to the technical definition.