This study focuses on an investigation of the M300 maraging steel powder and improving the surface by using tumbling for the printed parts for the purpose of gaining deeper insights into the characteristics of printed maraging steel components, with the aim of enhancing its use in practical applications such as aerospace, energy, automotive, and medical industries. Scanning electron microscopy (SEM) and backscattered electrons (BSE) were used to examine the morphology of the powder. The particle size distribution of the powder (PSD) is next examined for the original powder. Furthermore, an optical technique is used to measure the porosity of the powder. This analysis revealed porosity ranging from 0.04 to 0.12%, with a mean value of 0.07% for both parallel and perpendicular sections. The microstructure was examined. Finally, the post-processing stage was examined after tumbling for 480 min, which yielded a huge improvement in surface area (Ra = 0.26 µm and Rz = 2.08 µm) for 2D surface roughness and (Sa = 0.35 µm, Sp = 5.98 µm, Sv = 15.44 µm, and Sz = 21.42 µm) for 3D roughness measurements. The surface topography and morphology images were evaluated. An assessment was conducted on the chemical composition of the printed parts. In addition, the surface wettability was examined and shown to exhibit wetting behavior (under 90°).

This study delves into selective laser melting (SLM). By using M300 steel in virgin and recycled powder form (after 20 cycles), with the aim of reducing the cost of printing for the practical application of M300 maraging steel, a comprehensive comparison between the two types of powder was evaluated. The powder’s morphology was analyzed using scanning electron microscopy (SEM) and backscattered electrons (BSE). The particles were seen to have a spherical shape, with a notable number of satellites attached to their surfaces. The particle size distribution (PSD) was examined and ranged from 10 to 90 µm for both powders. In addition, the porosity exhibited an average value of 0.07% for the virgin powder and 0.10% for the recycled powder. The microstructure was examined. Additionally, the surface wettability was tested, and it was seen to display wetting behavior for both types of powder, while blackened surfaces showed a higher wetting angle than untreated surfaces (hydrophobic). The 2D roughness measurements showed that the recycled powder had no significant difference from the virgin powder (Ra = 5.33 µm, Rz = 24.17 µm) before blackening and (Ra = 5.48 µm, Rz = 24.07 µm) after blackening. Corrosion tests proved that the recycled powder did not affect the corrosion properties of the material, while blackening caused partial surface corrosion in both types of samples, regardless of the used powder.

A growing number of steel components are being fabricated by 3D metal printing. Using metallic powder as the material fed into the laser is selective laser melting (SLM), one of the most popular and precise techniques. The main focus of this article is the investigation that Renishaw conducted on the powder that was supplied. The powder is made using the gas atomization method, and the powder obtained from the SLM process is then examined. The powder's morphology is analysed using scanning electron microscopy (SEM). The particles were seen to have a spherical shape, with a notable number of satellites attached to their surface. The particle size distribution (PSD) was examined and ranged from 15 to 90 µm. In addition, the porosity exhibited a range of values between 0.03% and 0.12%, with an average value of 0.07%. Additionally, the surface wettability was tested, and it was seen to display a wetting behavior (under 90◦) which provided surface energy up to 46.21 mJ.m−2.

Increasingly, the fabrication of steel components is being done via 3D metal printing. One of the most commonly utilized reliable and precise methods is called selective laser melting (SLM), and it involves the use of metallic powder as the material that is fed into the laser. One of the famous problems that SLM technicians face is the roughness of the printed parts. The goal of this paper is to study the effect of tumbling on the M300 maraging steel, which was produced by using a Renishaw AM500 3D SLM printer. An examination of a procedure that is both cost-effective and efficient for manufacturing and surface treatment is carried out within the scope of this research. The post-processing was investigated in depth, which resulted in 2D surface roughness Ra = 0.39 µm and 3D surface roughness Sa = 0.4 µm. The topography and morphology of the specimens were checked. Additionally, the surface wettability was tested, and it was seen to display wetting behavior, the improvement in surface wettability caused a better surface energy.

To mitigate environmental impact, specifically the CO₂ emissions associated with conventional thermal and nuclear facilities, renewable energy sources are increasingly being adopted as primary alternatives. However, integrating these renewable sources into the utility grid poses a significant challenge, primarily due to the stochastic and nonlinear nature of weather. Consequently, it is imperative that power systems operate under an intelligent control model to ensure energy output meets strict power quality standards. In this context, accurate forecasting is a cornerstone of smart power management, particularly in off-grid architectures, where predicting Power Quality Parameters (PQPs) is fundamental for system optimisation and error correction. This study conducts a comprehensive comparative evaluation of nine different predictive architectures for estimating PQPs. The algorithms analyzed include LSTM, GRU, DNN, CNN1D-LSTM, BiLSTM, attention mechanisms, DT, SVM, and XGBoost. The central objective is to develop a reliable basis for the automated regulation and enhancement of electrical quality in isolated systems. The specific parameters investigated are power voltage (U), Voltage Total Harmonic Distortion THDu, Current Total Harmonic Distortion THDi, and short-term flicker severity (P_st). Data for this investigation were acquired from an experimental off-grid setup at VSB-Technical University of Ostrava (VSB-TUO), Czech Republic. To assess model performance, we utilised Root Mean Square Error (RMSE) as the primary accuracy metric, while simultaneously evaluating computational efficiency in terms of processing speed and memory consumption during testing.

This study investigates the effects of centrifugal and vibratory tumbling on the surface quality of M300 maraging steel components produced using Selective Laser Melting (SLM). Surface roughness is a critical issue in SLM, impacting mechanical properties and overall performance. To address this, two abrasive finishing methods were applied using ceramic, plastic, and porcelain media. Evaluations were performed using 2D and 3D surface roughness measurements, scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), and wettability analysis. Centrifugal tumbling, particularly with ceramic media, demonstrated significant effectiveness in reducing surface roughness, achieving an Sa value as low as 0.39 μm. In contrast, vibratory tumbling showed limited improvement. EDS analysis highlighted a reduction in titanium content and an increase in silicon concentration, likely due to surface layer removal and media interaction. Wettability analysis further confirmed enhanced surface properties, with a reduced contact angle of 60°, promoting better adhesion. These findings emphasize the superiority of centrifugal tumbling for enhancing surface quality in SLM-printed M300 maraging steel components. This cost-effective post-processing technique offers practical applications for industries seeking improved surface integrity and functional performance in critical components.