This study focuses on optimizing machining parameters in the micro-milling of AlSi10Mg aluminum alloy produced via the powder bed fusion additive manufacturing process. Although additive manufacturing enables complex geometries and minimizes material waste, challenges remain in reducing surface roughness and cutting forces during post-processing. Micro-milling experiments were conducted using spindle speeds up to 60,000 rpm, with varied feed rates and cutting depths. Cutting forces (Fx, Fy, and Fz) were measured using a Kistler-9119AA1 mini dynamometer, while surface roughness (Ra) was evaluated with a Nanovea-ST400 3D optical profilometer. Five advanced machine learning models, random forest regressor (RFR), gradient boosting regressor (GBR), LightGBM, CatBoost, and k-nearest neighbors (KNN), were employed to predict cutting forces and surface roughness, with CatBoost achieving the highest predictive accuracy (R² > 0.96). Among all models, CatBoost achieved the best predictive performance, with test R² values exceeding 0.96 for both force and Ra estimations. Experimental and ML-based results demonstrated that higher feed rates and depths of cut increased cutting forces, particularly in the Fx direction, while elevated spindle speeds reduced forces due to thermal softening. Surface roughness was minimized at lower feed rates and higher spindle speeds. The optimal machining conditions for achieving Ra < 1 µm were identified as ap = 50 µm, n = 30,000 rpm, and fz = 0.25 µm/tooth. This integrated approach supports precision machining of AM aluminum alloys.

In industrial manufacturing and research laboratories, precise machining of work materials is crucial to meet the demand for fast assembly and sustainable high-quality production. Precise machining procedures play a vital role in manufacturing compatible parts that meet the production requirements. This study investigates the impact of different parameters on burr formations and slot dimensions during the micro-milling of AISI 316 material. A careful examination was conducted using scanning electron microscopy (SEM) images under varying conditions. The variables considered include cutting speed, feed rate, and depth of cut. The main finding revealed that the feed rate and depth of cut significantly influence burr formation, with lower rates and depths resulting in noticeable reductions. A higher feed rate was associated with more pronounced burr formation. Moreover, burr widths on the down-milling sides were typically wider than those on the up-milling sides due to continuous chip formation and compressive forces during down-milling. Utilizing image processing, the study further quantified burr and slot widths with high accuracy, offering a reliable method to characterize burr formation. This research presents potential ways to minimize burr formation during micro-milling processes by effectively managing machining parameters.

The most critical component of Industry 4.0, the new face of the machinery-manufacturing industry sector, is metal additive manufacturing. Laser-based additive manufacturing techniques are dominant for metal additive manufacturing today. In this study, the metal alloy studied is Ti-6Al-4V, one of the essential Ti alloys used in more than 50% of all commercial Ti applications. Ti-6Al-4V parts produced by additive manufacturing are used in the biomedical, aerospace-defence industry, and industrial areas due to their high strength, fatigue behaviour, fracture strength, good corrosion resistance, and biocompatibility. In the study, samples of Ti6Al4V alloy were produced with different manufacturing parameters by the direct metal laser sintering (DMLS) method, which is one of the powder bed fusion methods. Then, the surface qualities of the samples were processed by milling and wire EDM. The effects of machining operations on the surface roughness of the samples were investigated and compared with the surface roughness obtained from the samples produced by the DMLS method. After the optical microscope images of the samples were taken, the physical and surface morphology were examined. Although the mechanical properties of the parts manufactured by DMLS methods were higher, the samples with machining presented higher machinability with lower forces, lower surface roughness. the This is explained that mechanical properties of samples of Ti6Al4V alloy in additive manufacturing are highly dependent on the rapid cooling of the material. Results show that samples of Ti6Al4V manufactured by additive manufacturing has been possible using with machining. The most critical component of Industry 4.0, the new face of the machinery-manufacturing industry sector, is metal additive manufacturing. Laser-based additive manufacturing techniques are dominant for metal additive manufacturing today. In this study, the metal alloy studied is Ti-6Al-4V, one of the essential Ti alloys used in more than 50% of all commercial Ti applications. Ti-6Al-4V parts produced by additive manufacturing are used in the biomedical, aerospace-defence industry, and industrial areas due to their high strength, fatigue behaviour, fracture strength, good corrosion resistance, and biocompatibility. In the study, samples of Ti6Al4V alloy were produced with different manufacturing parameters by the direct metal laser sintering (DMLS) method, which is one of the powder bed fusion methods. Then, the surface qualities of the samples were processed by milling and wire EDM. The effects of machining operations on the surface roughness of the samples were investigated and compared with the surface roughness obtained from the samples produced by the DMLS method. After the optical microscope images of the samples were taken, the physical and surface morphology were examined. Although the mechanical properties of the parts manufactured by DMLS methods were higher, the samples with machining presented higher machinability with lower forces, lower surface roughness. the This is explained that mechanical properties of samples of Ti6Al4V alloy in additive manufacturing are highly dependent on the rapid cooling of the material. Results show that samples of Ti6Al4V manufactured by additive manufacturing has been possible using with machining.

Endüstri devrimi 4.0 temel bileşenlerinden birisi olan eklemeli imalat karmaşık geometriye sahip parçaların imalatını yaparak imal edilebilirlik kısıtını ortadan kaldırmıştır. Ham maddenin katı, sıvı ve gaz esaslı olmak üzere malzeme türüne göre eklemeli imalat sınıflandırılmaktadır. Günümüzde metallere yönelik çok sayıda eklemeli imalat teknolojisi kullanılmaktadır. Çalışmada metal eklemeli imalat çeşitlerinden seçici lazer ergitme yöntemiyle 316L paslanmaz çelik malzemeden standart parametre ile numune üretilmiştir. Daha sonra sabit kesme hızı, ilerleme hızı ve derinlik parametreleri ile numunenin ilk orta ve son olmak üzere farklı kesme mesafelerinden çapak genişlikleri ölçümleri gerçekleştirilmiştir. Elde edilen sonuçlara göre, kesme işleminin başlangıcında çapak genişlikleri (109 µm) genel olarak düşük seviyededir. Sağ kenardaki çapak genişliği (372 µm) sol kenardakinden oldukça fazladır. Artan kesme mesafesiyle birlikte, numunenin sol kenardaki çapaklar (1001 µm) genellikle kanal kenarından uzaklaşarak yatık bir vaziyette iken sağ kenardaki çapaklar (539 µm) genellikle kanal içinden kenara yaslı bir biçimde olduğu görülmüştür.

This study aims to increase the microhardness of Ti-6Al-4 V produced by laser polishing (LP) with selective laser melting (SLM), to make micromachinability with optimum parameters and to minimize surface roughness. LP process has started to attract great industrial interest today due to the significant increase in surface quality. In addition, the processing of small geometry channels, requiring precision and high surface quality, further increases the importance of micromilling. In this experimental study, the surface morphology, microhardness and micromachinability of Ti-6Al-4 V material produced by SLM were investigated before and after LP. The aim is to investigate the increase in microhardness, surface roughness, and burr amount with 3 different spindle speeds (4000-6000-8000), 4 different feed rates (2-4-6-9), and 2 different depths of cut used as micromilling parameters. When the SLM material was compared to the LP material, the hardness value increased by approximately 27%. It was observed that there was a 400% improvement in surface roughness values (Sa). When viewed with three-dimensional surface topography, it is seen that the cutting marks are more prominent in the material made with LP. Surface roughness values are inversely proportional to cutting speed and directly proportional to feed rate. While materials with high hardness should have lower surface quality in machined areas, Sa values are lower in LP areas. In addition, the difference between the surface roughness values is maximum for both SLM and LP material at the same depths of cut. These findings are aimed to determine the machinability parameters during the manufacturing of materials used especially in the aviation, defense, medical, and automotive industries.

In this study, the machinability of PET-G (Polyethylene Terephthalate Glycol) material produced by Fused Deposition Modeling (FDM) was experimentally investigated under various manufacturing and machining parameters. The effects of key parameters influencing delamination—namely infill percentage, layer thickness, spindle speed, and feed rate—were specifically examined. Statistical data were obtained using the Taguchi method, and the results were analyzed in terms of both mean values and Signal-to-Noise (S/N) ratios. The findings revealed that infill percentage has a significant effect on delamination. The lowest delamination values were observed at a 100% infill level, while the highest delamination occurred at a 33% infill ratio. When layer thickness was increased from 1 mm to 2 mm, a reduction in delamination tendency was observed. An increase in spindle speed resulted in a notable rise in delamination, particularly at high rotational speeds (4500 rpm), where elevated cutting forces and temperature led to structural damage and delamination. The influence of feed rate on delamination was relatively minor. This study presents a comprehensive experimental analysis of both production parameters (infill percentage and layer thickness) and machining parameters (spindle speed and feed rate) for PET-G material. It is concluded that, for optimal machinability of PET-G manufactured via the FDM method, an infill percentage of 100% and a layer thickness of 2 mm are recommended. This work provides valuable guidance for quality control and parameter optimization in post-additive manufacturing machining processes.