In the development and production of injection molded products, CAE plays an indispensable role for design engineers. CAE analysis enables engineers to identify potential issues and optimize designs before going to production. Additionally, virtual molding tryouts through CAE analysis assist engineers to determine suitable molding conditions, serving as a foundation of subsequent mold tryout results. However, once mold development is complete and mass production begins, on-site manufacturing teams often cannot directly access CAE-driven molding conditions, relying instead on experience to adjust process parameters. For new products or materials, limited experience may prolong the mold tryout process, thereby delaying production. Since Moldex3D CAE analysis results are generated based on product, material properties and machine characteristics, the optimized molding conditions closely represent actual production scenarios. This scientific molding, compared to traditional methods, significantly accelerates the mold tryout process and reduces cost. As a result, enabling effective data sharing between CAE and production has become essential. Such integration allows manufacturing teams to readily access analysis results as tryout references while equipping design teams to efficiently utilize tryout results for future design and optimization.
The importance of integrating design and manufacturing has surged in recent years, a trend showcased at industry exhibitions. To facilitate seamless manufacturing connectivity, Moldex3D had collaborated with leading injection molding machine manufacturers— FANUC, SUMITOMO, and ENGEL— to integrate CAE with their machines. This enables molding results to be swiftly and effortlessly transmitted to production teams, allowing molding engineers to utilize these conditions for rapid tryout initiation. Consequently, optimal conditions are identified faster, tryout time is reduced and challenges posed by new materials and new products are effectively mitigated. With a smoother two-way data exchange, tryout data is easily preserved and stored in the system, as a reference for future product development. By uniting design and manufacturing, workflow and information across both phases are seamlessly connected, fostering a smart molding production process.
Integration with FANUC ROBOSHOT Injection Machines
Moldex3D and FANUC exchanges data through Moldex3D iSLM. Both operate within client’s private cloud for enhanced information security and confidentiality. Design engineers perform Moldex3D analysis on-premises and upload results to iSLM. At the tryout site, molding engineers access the results directly through ROBOSHOT LINKi2 on the machine controller, using iSLM integration—no additional equipment is required. This allows real-time viewing of CAE analysis and enables a two-way information data exchange, as shown in Figure 1.
Figure 1 Integration Workflow of Moldex3D with FANUC ROBOSHOT Injection Machines
Molding engineers can directly open iSLM on the controller and obtain analysis results for the upcoming mold tryout, such as flow front results, or injection pressure curves, and review them instantly. To begin a mold tryout, a one-click function transfers CAE-derived molding conditions to the manufacturer’s side as initial mold tryout settings (as shown in Figure 2). Engineers then fine-tune based on product quality to achieve optimal part quality. Post-tryout, adjusted parameters can be uploaded back to iSLM by only single click, storing key tryout data and insights for future use by molding or design engineers, thus speeding up R&D and production efficiency.
Figure 2. One-Click Transfer of Molding Conditions from CAE To Manufacturing
Integration of Moldex3D with SUMITOMO Injection Molding Machines
Moldex3D integrates with SUMITOMO machines using machine-readable molding condition files (Figure 3). This integration is supported by SUMITOMO NC-10 controller. Before the mold tryout, molding engineers configure settings like mold opening/closing on the tryout machine’s controller and export the condition file. In Moldex3D, engineers open the target analysis group, access the NC-10 real-machine page in the Molding Wizard, and import the machine file. By selecting the desired molding condition file and specifying a save location, the Wizard will automatically embed CAE conditions into the machine file. Engineers then load this file into the machine, where the controller applies the CAE condition directly.
Figure 3. Integration Workflow of Moldex3D with SUMITOMO NC-10 controller
Integration with ENGEL Injection Machines
Moldex3D collaborates with Engel injection machines through ENGEL’s sim link, a production monitoring and data analysis system, bridging simulation and production. Supporting Moldex3D analysis results, the workflow is illustrated in Figure 4. Users install on-premises software to generate exchange files between Moldex3D and sim link. Via this interface, they select an analysis project, export a compatible file, and upload the file to the cloud service in sim cloud, designating the production machine. Sim link adjusts the molding conditions for the chosen machine and produces a new exchange file. Importing this back to Moldex3D generates a new analysis group with updated conditions. After re-running the analysis, the results can be re-uploaded to sim link. Once validated, users can output a machine-readable file via sim link’s cloud service, which molding engineers then import into an ENGEL injection molding machine to start the tryout efficiently.
Figure 4. Procedure of Moldex3D and ENGEL Injection Machine Integration
Conclusion
With integrated design and manufacturing, molding analysis results are seamlessly delivered to the production side as tryout references, thereby accelerating tryout process. This synergy also ensures critical tryout data is stored in the system, offering a robust foundation for future design and production. Through its integration with injection machines, Moldex3D partners with you to tackle diverse mold tryout challenges, co-creating a smart future for injection molding.