CONNECT European Moldflow User Meeting – June 2 + 3, 2025

The talk presents insights from the nearly completed publicly funded project “DIGILaugBeh,” focused on sustainability in long glass fiber reinforced PP. Led by PTJ and funded by the BMWK, the project involves partners like Bosch, RWTH-IKV, Fraunhofer-ITWM, University of Stuttgart, M2M, PEG, and others.

The project combines Life Cycle Assessment (LCA) with process simulation using Moldflow—disciplines that are typically done separately. The goal is to assess environmental impacts (e.g., CO₂ footprint, energy use) during part design by integrating data from both areas.

A demonstrator based on a simplified washing machine part was developed for validation. A first prototype of the standalone tool is expected by June 2025, which will then be commercialized by e.g. PEG.

During the initial design phase of a product or in design optimizations, it is often impractical to execute high-fidelity process simulations due to their computational demands. Consequently, it is advantageous to develop rapid approximative models employing machine learning that facilitate a prompt estimation of the mold filling outcome. The primary challenge lies in training such models with a limited quantity of training data and ensuring their generalizability to unseen geometries. With our approach employing engineered features, we can achieve up to 200 times acceleration while estimating the mold filling process with less than 10% error. 

Lead time and cost-effectiveness are critical factors for the success of projects involving the production of plastic parts for the automotive industry. To address these challenges, forteq is leveraging Moldflow simulation as a central tool for the entire industrialization process, from tool design to process parameter definition. After optimizing the tool design and simulating potential issues like shrinkage and warpage, we aim to directly apply Moldflow’s deflection compensation to cut our tools. Additionally, we plan to use the same process parameters from the simulation for the initial tool sampling. A workflow, along with examples, will be presented, and the first results will be discussed.

Film Insert Molding (FIM) represents a key technology for integrating decorated films into injection molded parts, enabling high-quality decorative and functional surfaces. 

A significant challenge in FIM processes is ink washout, which can result in substantial scrap rates and development costs. 

This study presents a novel simulation approach for predicting ink washout phenomena during the FIM process, specifically focusing on Polycarbonate films with black screen-printed designs. The methodology integrates a custom developed Moldflow® API to simulate the interaction between the injected thermoplastic melt and the printed film surface. 

Initial validation tests were conducted using Covestro Makrofol® films. The simulation method enables proactive mold/gate design optimization, potentially eliminating ink washout issues before physical production begins. This advancement represents a significant step forward in FIM process optimization and quality assurance.