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What’s New in Moldex3D 2026 r2
Driven by Automation, Optimization and Intelligence, Moldex3D 2026 delivers faster, more accurate, and smarter molding simulations. Effectively tackling manufacturing challenges, reducing costs, and accelerating time to market. Ensuring every simulation closely reflects real-world production conditions. Break through every barrier from design to production.
Moldex3D 2026 R2
Moldex3D 2026 R2 latest version Molding Intelligence
As Artificial Intelligence and automation technologies move toward deep application, using intelligent means to precisely process data and predict potential risks has become the core driving force for industrial digital transformation. Moldex3D 2026 focuses on three major development pillars: Automation, Optimization, and Intelligence (A.O.I.), bringing users more powerful intelligent predictive suggestions, intuitive automated workflows, and significant upgrades in simulation performance. The launch of the new version will help enterprises easily implement key intelligent tools, maximizing product development efficiency and core competitiveness.
Evolved Analysis Performance for Precision and Efficiency
Moldex3D 2026 continues to refine its solver architecture and optimize simulation performance to meet the high-precision demands of various industries. The new version offers more stable hot runner injection pressure prediction and enables efficient analysis of multi-cavity systems using partial runner models, achieving over 4x speed improvement while maintaining high accuracy. The fully upgraded crystallization simulation integrates unique high-speed cooling measurement data from the Moldex3D Material Lab, bringing simulations closer to real processing conditions and significantly improving the consistency of weld line length, position, and particle tracking. We also provide non-linear material models for fiber-reinforced plastics; fiber orientation and material properties can be directly exported to LS-DYNA and Atlas, supporting a complete workflow from design to structural verification and making it easier to evaluate the optimal balance between lightweighting and strength.
