-A melt flow index-based approach for the viscosity curves determination OUBELLAOUCH Keltoum, PELACCIA Riccardo, POZZI Paolo, ZANIBONI Giulia, ORAZI Leonard

Machining of medium-carbon steels, such as AISI 1050, poses a significant challenge in terms of achieving stable cutting conditions, controlled chip evacuation and high surface integrity, in particular when full-face milling is performed under elevated material removal rates. The tool surface engineering approach, particularly laser-induced micro-texturing, comprises a promising route toward modifying the tribological conditions at the tool–chip interface, thus affecting friction, heat generation, chip formation and the resultant surface finish. This study investigates the combined effects of cutting speed, axial depth of cut and tool micro-texture orientation (parallel versus orthogonal to the chip flow direction) on machining performance under wet conditions. In addition to the experimental analysis of cutting forces, chip morphology and surface roughness, this work integrates a full factorial Design of Experiments, regression modeling, and ANOVA to quantify the statistical significance of each factor and to identify dominant interactions. The regression models show strong predictive capability across all measured responses, while the ANOVA confirms the axial depth of cut and tool texture orientation as the most influential parameters. Multi-objective optimization by Pareto analysis further underlines the superiority of orthogonal micro-texturing, which consistently reduces the cutting forces and improves surface quality while promoting controlled chip segmentation. The results provide quantitative and statistically validated evidence of the enhancement of lubrication effectiveness, reduction in interface friction, and stabilization in chip formation provided by the micro-textured tools. Overall, the findings contribute to the development of data-driven machining strategies and surface-engineered cutting tools in view of improved productivity, energy efficiency and surface integrity in advanced manufacturing applications.

In the injection molding process, handling shrinkage is crucial to reduce warpage in molded parts. As demand increases for complex components with high-quality standards, including tight tolerances and defect-free parts, numerical tools have become essential for optimizing the process and improving product performance. This work proposes a novel method to accurately predict part warpage using the Anisotropic Thermo-Viscous Elastic Residual Stress Model implemented in Moldflow, with a focus on calibrating numerical simulations through manual adjustment of the Coefficients of Linear Thermal Expansion (CLTE). Using optical 3D scanning acquisitions to compare experimental results with simulation predictions, the method enables precise calibration that reduces numerical-experimental discrepancies in warpage predictions.

The increasing demand for lightweight and energy-efficient components has strengthened the use of high-pressure die casting (HPDC) for thin-walled aluminium parts, often produced from recycled alloys. However, HPDC components are still affected by microstructural heterogeneity and defect formation, such as shrinkage porosity and gas entrapment, which are closely related to melt flow and solidification conditions. In this study, a dedicated step-casting geometry was developed to reproduce, within a single casting, solidification conditions representative of industrial HPDC components with varying thickness. The design was supported by numerical simulations to control filling and thermal evolution. Experimental HPDC trials were performed under industrial conditions, followed by microstructural characterization in terms of porosity, Secondary Dendrite Arm Spacing (SDAS) and skin layer thickness. Comparison with a complex industrial demonstrator component confirmed that the step casting reliably reproduces both average microstructural features and their variability. The proposed numerical–experimental approach provides a robust framework for process HPDC design and optimization for lightweight cast components.

Efficient thermal management is a key factor in improving the sustainability and productivity of injection moulding processes, particularly at the micro-scale where thermal transients strongly affect part quality and cycle stability. This work investigates the thermal behaviour of hybrid moulds composed of polymeric support plates manufactured in Precision Resin V01 and stainless-steel inserts manufactured by additive manufacturing. An experimental campaign was carried out on a micro-injection moulding machine to characterize the intrinsic thermal response of the mould under uncooled conditions. Temperatures were monitored through embedded thermocouples and used to develop and calibrate a three-dimensional transient numerical model in COMSOL Multiphysics. Particular attention was devoted to the identification and calibration of heat transfer coefficients at the injection and extraction interfaces, which were found to play a dominant role in governing insert temperature evolution. The calibrated model accurately reproduces the experimental thermal transients, with deviations below 10%, demonstrating its reliability as a predictive tool for analysing mould thermal behaviour and supporting early-stage design and process optimization. The results highlight the advantages of hybrid architectures in promoting thermal stability and provide a robust methodology for modelling heat exchange in unconventional mould configurations.

Warpage in injection-molded thin-walled box-shaped parts is primarily caused by non-uniform cooling and differential shrinkage. This study proposes a two-step, multi-objective optimization strategy to reduce part warpage by addressing both thermal and geometric factors. In the first step, the mold cooling system is optimized through a bi-objective formulation that simultaneously minimizes (i) the temperature standard deviation within the part and (ii) the total cooling channel length. The optimization is carried out using a coupled workflow involving parametric CAD modeling, Autodesk Moldflow simulations, and a genetic algorithm. The optimized cooling design reduces temperature non-uniformity by 44% compared to a conventional cooling layout. In the second step, a geometric optimization is performed through the addition of a reinforcing border, where maximum deflection and total part volume are minimized simultaneously. The combined optimization leads to a reduction in maximum warpage from 14.5 mm in the reference configuration to 2.06 mm in the final design. The results demonstrate the effectiveness of a sequential optimization approach in achieving significant warpage reduction while maintaining material and manufacturing efficiency.