This study aims to analyze the influence of cutting parameters (cutting speed, feed rate, and depth of cut) on cutting temperature, forces, and energy consumption during the dry turning of Ti6Al4V, providing an optimized machining strategy to improve efficiency and sustainability. Due to the challenges of machining this alloy, such as high temperatures and tool wear, response surface methodology (RSM) was used to develop second-degree polynomial models, and analysis of variance (ANOVA) identified the most influential factors. The results indicate that depth of cut has the highest impact on cutting temperature (42.59%), cutting forces (53.08%, 74.73%, and 48.87% in the respective force components), and power consumption (49.78%), while feed rate is the dominant factor in energy consumption (63.36%). Gray relational analysis (GRA) was applied to optimize machining conditions based on the developed models, allowing a wider selection of cutting parameters beyond the experimental values. These findings provide a valuable tool for the industry, offering manufacturers a data-driven approach to optimizing the machining of Ti6Al4V and reducing energy consumption and tool wear while improving process stability. The proposed methodology enhances sustainability and cost-efficiency in titanium alloy machining, particularly in the aeronautical sector.

The paper describes an experimental study developed on the AA7075 T651, which is an aluminum alloy extensively used in the aeronautical industry. This work presents a double approach of investigation where there is no literature about previous research. This includes the analysis of the results obtained by the combination of mechanical and chemical actions on the mechanical properties of this material. On the one hand, the combinations of relevant milling parameters (feed rate, cutting speed) on flat samples (flat specimens have been selected by attempting to reproduce with the most accurate way the geometry and the type of machining process known as face milling is usually used in this manufacturing field). On the other hand, the stimulating effect of the corrosion by salt spray on selected batches of specimens was machined in the previous stage. Results from tensile tests performed on the whole of specimens allowed us to evaluate how the main mechanical properties (yield strength, tensile strength, and elongation at break) have been affected by the processes applied. Elongation at the break presents a reduction in an inverse order to feed a rate increase (up to 24.5%) and this reduction is extended (additional 19.17%) in specimens under corrosion conditions, which results in a greater fragility of the material.

Geometrical tolerances play a very important role in the functionality and assembly of parts made of light alloys for aeronautical applications. These parts are frequently machined in dry conditions. Under these conditions, the tool wear becomes one of the most important variables that influence geometrical tolerances. In this work, the influence of tool wear on roundness, straightness and cylindricity of dry-turned UNS A97075 alloy has been analyzed. The tool wear and form deviations evolution as a function of the cutting parameters and the cutting time has been assessed. In addition, the predominant tool wear mechanisms have been checked. The experimental results revealed that the indirect adhesion wear (BUL and BUE) was the main tool-wear mechanism, with the feed being the most influential cutting parameter. The combination of high feed and low cutting speed values resulted in the highest tool wear. The analyzed form deviations showed a general trend to increase with both cutting parameters. The tool wear and the form deviations tend to increase with the cutting time only within the intermediate range of feed tested. As the main novelty, a relationship between the cutting parameters, the cutting time (and, indirectly, the tool wear) and the analyzed form deviations has been found.

The production of sugar from sugarcane cultivation was one of the most significant industrial activities in eastern Andalusia during the late nineteenth and early twentieth centuries. Along the Málaga coastline, remnants of these sugar mills can still be found, many of them currently in a state of abandonment or poor conservation. This study presents the 3D digital reconstruction of the San Joaquín sugar mill (Maro, Málaga, Spain) using UAV-based photogrammetry. A point cloud was generated from aerial images processed with specialized software. A comparative analysis was conducted using between 12.5% and 100% of the captured images to evaluate model accuracy and computational cost. The full dataset (100%) produced the most complete and accurate model, although at a higher computational cost. Reduced datasets (25–50%) achieved high-resolution representations of the main structures but failed to fully reconstruct certain elements, particularly the chimney. The point cloud was subsequently used to develop a HBIM-based model, enabling the reconstruction of structural components, including a hypothetical interpretation of the workers’ housing, currently in a near-ruined condition. These results demonstrate the effectiveness of UAV photogrammetry and HBIM as complementary tools for the documentation and reconstruction of industrial heritage, providing a solid basis for future restoration and adaptive reuse strategies.