Press Releases and News

The first session of the seminar introduced the latest technological trends and implementation cases of the 'AI-Based Smart Casting Manufacturing Platform', tailored to adapt to the rapidly changing global manufacturing landscape.

To help foundry enterprises with legacy equipment or traditional casting processes adopt smart manufacturing without heavy upfront capital expenditures, MAGMA presented customized 'Retrofit Consulting' solutions. Detailed methodologies were shared on step-by-step implementations—such as modular sensor deployment, data collection techniques, and AI simulation algorithms—to enhance process control precision on existing equipment.

Following the platform overview, a specialized technical presentation was dedicated to 'Advanced High Pressure Die Casting (HPDC) Simulation Technologies and Implementation Strategies'.

This session focused on cutting-edge simulation capabilities designed to address complex challenges unique to the HPDC process. Key highlights included autonomous optimization algorithms for shot sleeve thermal management, runner and gating system design, and quantitative prediction of air entrapment and die erosion.

Furthermore, actionable implementation strategies were presented to help regional foundries seamlessly integrate advanced HPDC simulation into their existing production workflows. By leveraging these predictive insights prior to tooling manufacture, participating engineers gained valuable guidance on drastically reducing trial-and-error cycles and accelerating time-to-market for high-precision cast components.

Following the HPDC presentation, a technical session focused on ‘Cost Reduction and Quality Optimization Utilizing MAGMASOFT®’—a topic that drew significant interest from participants.

The presentation covered simulation technologies to predict and prevent common casting defects such as misruns, porosity, and shrinkage, alongside practical guidelines for improving yield and saving energy. Moving beyond defect reduction, quantitative analysis was shared to demonstrate how minimizing raw material and energy consumption can drastically improve overall production economics.

During the Q&A session, active discussions took place regarding key considerations for field implementation, ways to improve simulation accuracy, and seamless integration with existing foundry processes.