Search Results (2,004)

This study presents the first investigation into the application of ultrasonic vibration-assisted electrical discharge machining (UV-EDM) using graphite electrodes for external cylindrical surface machining—an essential surface in the production of tablet punches and sheet metal-forming dies. A custom ultrasonic horn was designed and fabricated using 90CrSi material to operate effectively at a resonant frequency of 20 kHz, ensuring stable vibration transmission throughout the machining process. A Box–Behnken experimental design was employed to explore the effects of five process parameters—vibration amplitude (A), pulse-on time (Ton), pulse-off time (Toff), discharge current (Ip), and servo voltage (SV)—on two key performance indicators: material removal rate (MRR) and surface roughness (Ra). The optimization process was conducted in two stages: single-objective analysis to maximize MRR while ensuring Ra < 4 µm, followed by a hybrid multi-objective approach combining NSGA-II and the Analytic Hierarchy Process (AHP). The optimal solution achieved a high MRR of 9.28 g/h while maintaining Ra below the critical surface finish threshold, thus meeting the practical requirements for punch surface quality. The findings confirm the effectiveness of the proposed horn design and hybrid optimization strategy, offering a new direction for enhancing productivity and surface integrity in cylindrical EDM applications using graphite electrodes. Full article

Rammed earth (RE), a traditional material aligned with circular economy (CE) principles, has been gaining renewed interest in contemporary construction due to its low environmental impact and compatibility with sustainable building strategies. Though not a modern invention, it is being reintroduced in response to the increasingly strict European Union (EU) regulations on carbon footprint, life cycle performance, and thermal efficiency. RE walls offer multiple benefits, including humidity regulation, thermal mass, plasticity, and structural strength. This study also draws attention to their often-overlooked ability to mitigate indoor overheating. To preserve these advantages while enhancing thermal performance, this study explores insulation strategies that maintain the vapor-permeable nature of RE walls. A parametric analysis using Delphin 6.1 software was conducted to simulate heat and moisture transfer in two main configurations: (a) a ventilated system insulated with mineral wool (MW), wood wool (WW), hemp shives (HS), and cellulose fiber (CF), protected by a jute mat wind barrier and finished with wooden cladding; (b) a closed system using MW and WW panels finished with lime plaster. In both cases, clay plaster was applied on the interior side. The results reveal distinct hygrothermal behavior among the insulation types and confirm the potential of natural, low-processed materials to support thermal comfort, moisture buffering, and the alignment with CE objectives in energy-efficient construction. Full article

With the application and rapid development of light industrial robots, it is vital to accelerate the prototype design to fulfill the demands of shortening the robot’s production cycle, owing to rapid update iterations. Since the traditional design method cannot intuitively and efficiently check the deficiencies in the design preparation, the secondary design iterations will result in higher equipment costs, longer design cycles, and lower development efficiency. The MBD (model-based design), a full 3D (three-dimensional) design and manufacturing method, is proposed to swiftly finish the prototype design for solving the above problems. Firstly, the robot design preparation is completed with the design requirements to generate a robot 3D model. Secondly, several design methods are used: (i) the rapid prototyping, which includes the joint component verification and selection to further optimize the 3D model; (ii) the robot kinematics algorithm, which provides a theoretical foundation for the 3D model design; (iii) the robot kinematics simulation, which verifies the correctness of the kinematics algorithm. Finally, the feasibility of the MBD is verified by the robot prototype and the motion control system test. Taking the MBD to design a 5-DoF (five-degrees-of-freedom) robot as an example, the joint verification and selection are finished quickly and accurately to build the robot prototype without the need for secondary design processing, and the kinematic algorithm verified by the co-simulation platform can be used directly in the actual motion control of the robot prototype, which accelerates the development of the robot motion control system. Full article

This study explores the efficacy of magnetic abrasive finishing (MAF) with planetary kinematics for post-processing Inconel 939 components fabricated by laser powder bed fusion (LPBF). Given the critical limitations in surface quality of LPBF-produced parts—especially in hard-to-machine superalloys like Inconel 939—there is a pressing need for advanced, adaptable finishing techniques that can operate effectively on complex geometries. This research focuses on optimizing the process parameters—eccentricity, rotational speed, and machining time—to enhance surface integrity following preliminary vibratory machining. Custom-designed samples underwent sequential machining, including heat treatment and 4 h vibratory machining, before MAF was applied under controlled conditions using ferromagnetic Fe-Si abrasives. Surface roughness measurements demonstrated a significant reduction, achieving Ra values from 1.21 µm to below 0.8 µm in optimal conditions, representing more than a fivefold improvement compared to the as-printed state (5.6 µm). Scanning Electron Microscopy (SEM) revealed progressive surface refinement, with MAF effectively removing adhered particles left by prior processing. Statistical analysis confirmed the dominant influence of eccentricity on the surface profile parameters, particularly Rz. The findings validate the viability of MAF as a precise, controllable, and complementary finishing method for LPBF-manufactured Inconel 939 components, especially for geometrically complex or hard-to-reach surfaces. Full article

Ion beam figuring (IBF) is an ultra-high-precision surface finishing technology characterized by a distinct trade-off between the spot size of the removal function and its corresponding figuring capabilities. A larger spot size for the removal function leads to higher processing efficiency but lower figuring ability. Conversely, a smaller spot size results in higher figuring ability but lower efficiency. Adjusting the spot size of the removal function using tools with an aperture is a possible approach. However, existing variable-aperture tools have certain limitations in IBF processing. To leverage the advantages of both large and small spot sizes for the removal function during IBF processing, an in situ dynamic beam variable-aperture device has been designed. This device optimizes the parameters of diaphragm sheets and employs FOC for dynamic aperture adjustment. Simulations show that 12 numbers of 0.1 mm-thick sheets minimize removal function distortion, with the thermal strain-induced area variation being <5%. FOC enables rapid (≤0.45 s full range) and precise aperture control. Experiments confirm adjustable spot sizes (FWHM 0.7–17.2 mm) with Gaussian distribution (correlation >96.7%), operational parameter stability (relative change rate ≤5%), and high repeatable positioning precision (relative change rate ≤3.2% in repeated adjustments). The design enhances IBF efficiency, flexibility, and accuracy by enabling in situ spot size optimization, overcoming conventional limitations. Full article

The current research trends of production engineering are based on optimizing the machining process concerning human and environmental factors. High-performance materials, such as hardened steels, nickel-based alloys, fiber-reinforced polymer (FRP) composites, and titanium alloys, are classified as hard-to-cut due to their ability to maintain strength at high operating temperatures. Due to these characteristics, such materials are employed in applications such as aerospace, marine, energy generation, and structural. The purpose of this article is to investigate the machinability of these alloys under various cutting conditions. The purpose of this article is to compare cryogenic cooling and cryogenic processing from the perspective of machinability and sustainability in the manufacturing process. Compared to conventional machining, hybrid techniques, which mix cryogenic and minimal quantity lubricant, led to significantly reduced cutting forces of 40–50%, cutting temperatures and surface finishes by approximately 20–30% and more than 40%, respectively. A carbon footprint is determined by several factors including power consumption, energy requirements, and carbon dioxide emissions. As a result of the cryogenic technology, the energy consumption, power consumption, and CO₂ emissions were reduced by 40%, 28%, and 35%. Full article

Fabric veneer panels were prepared using ethylene-vinyl acetate copolymer film (EVA) as the intermediate layer and poplar plywood as the substrate. Eight fabrics with different compositions were selected for evaluation to screen out fabric materials suitable for poplar plywood veneer. The fabrics were objectively analyzed by bending and draping, compression, and surface roughness, and subjectively evaluated by establishing seven levels of semantic differences. ESEM, surface adhesive properties, and peel resistance tests were used to characterize the microstructure and physical–mechanical properties of the composites. The results show that cotton and linen fabrics and corduroy fabrics are superior to other fabrics in performance, and they are suitable for decorative materials. Because the fibers of the doupioni silk fabric are too thin, and the fibers of felt fabric are randomly staggered, they are not suitable for the surface decoration materials of man-made panels. The acetate veneer surface gluing performance was 1.31 MPa, and the longitudinal peel resistance was 20.98 N, significantly exceeding that of other fabric veneers. Through the subjective and objective analysis of fabrics and gluing performance tests, it was concluded that, compared with fabrics made of natural fibers, man-made fiber fabrics are more suitable for use as surface finishing materials for wood-based panels. The results of this study provide a theoretical basis and process reference for the development of environmentally friendly decorative panels, which can be expanded and applied to furniture, interior decoration, and other fields. Full article

Fused Filament Fabrication (FFF) enables the manufacturing of complex polymer components. However, surface finish and dimensional accuracy remain key limitations for their integration into functional assemblies. This study explores the potential of conventional turning as a post-processing strategy to improve the geometric and surface quality of PLA reinforced with carbon fiber (CF) parts produced by FFF. Machinability was evaluated through the analysis of cutting forces, thermal behavior, energy consumption, and surface integrity under varying cutting speeds, feed rates, and specimen slenderness. The results indicate that feed is the most influential parameter across all performance metrics, with lower values leading to improved dimensional accuracy and surface finish, achieving the most significant reductions of 63% in surface roughness (Sa) and 62% in cylindricity deviation. Nevertheless, the surface roughness is higher than that of metals, and deviations in geometry along the length of the specimen have been observed. A critical shear stress of 0.237 MPa has been identified as the limit for interlayer failure, defining the boundary conditions for viable cutting operation. The incorporation of CNC turning as a post-processing step reduced the total fabrication time by approximately 83% compared with high-resolution FFF, while maintaining dimensional accuracy and enhancing surface quality. These findings support the use of machining operations as a viable and efficient post-processing method for improving the functionality of polymer-based components produced by additive manufacturing. Full article

The study focuses on optimizing the Fused Deposition Modeling (FDM) process by implementing a cost-efficient support structure strategy. The main objective is to develop a systematic approach for analyzing structural and technological parameters considering print time, material consumption, and surface quality. The study focus is on manually designed support structures as an alternative to automatic generation, allowing for precise control over print settings. The methodology includes comparative analysis of various support strategies using a Prusa MK3S+ printer under standardized conditions. Statistical and visual evaluations confirm that the designed support structures reduce print time by up to 59 min while maintaining comparable material use and superior surface finish. The findings offer a practical framework for optimizing 3D printing processes, reducing waste, and enhancing efficiency in prototyping and small-batch production. Full article

This study analyzed the surface layer condition of X5CRNI18-10 stainless austenitic chromium–nickel steel test pieces after burnishing. Among the finishing operations, burnishing is an economical and low-environmental-impact process. In special cases, grinding can be replaced by burnishing, so the same roughness can be achieved with much lower environmental impact. The aim of this study is to analyze the roughness of a surface machined by diamond burnishing using Kraljic matrices. The technological parameters used during the burnishing tests were burnishing speed, feed rate, and burnishing force. The full factorial experimental design method was used to carry out the experiments. Using Kraljic matrices, the optimum burnishing force was determined to select the best value of the surface roughness, and the change in surface roughness was investigated using full factorial experimental design for different technological parameter combinations. A special improvement ratio formula was developed to evaluate the effectiveness of the burnishing process with respect to 2D and 3D roughness parameters. Full article

Ceramic dental prosthetics with internal metal structures are made from a cobalt–chromium alloy that is coated with ceramic. This study aims to validate surface treatments for the metal that enhance the adhesion of the ceramic coating under masticatory forces. Surface conditioning is performed using mechanical methods, like sandblasting (SB), and thermal methods, such as oxidation (O). The ceramic coating is applied to the metal component following the conditioning process, which can be conducted using either a single method or a combination of methods. Each conditioned sample undergoes characterization through various techniques, including drop shape analysis (DSA), scanning electron microscopy (SEM), X-ray diffraction (EDX), and atomic force microscopy (AFM). After the ceramic coating is applied and subjected to thermal sintering, the metal–ceramic samples are mechanically tested to assess the adhesion of the ceramic layer. The research findings, illustrated by scanning electron microscopy (SEM) images of the metal structures’ surfaces, indicate that alloy powder particles ranging from 10 to 50 µm were either adhered to the surfaces or present as discrete dots. Particles that exceed the initial design specifications of the structure can be smoothed out using sandblasting or mechanical finishing techniques. The energy-dispersive spectroscopy (EDS) results show that, after sandblasting, fragments of aluminum oxide remain trapped on the surface of the metal structures. These remnants are considered impurities, which can negatively impact the adhesion of the ceramic to the metal substrate. The analysis focuses on the exfoliation of the ceramic material from the deformed metal surfaces. The results emphasize the significant role of the sandblasting method and the micro-topography it creates, as well as the importance of the oxidation temperature in the treatment process. Drawing on 25 years of experience in dental prosthetics and the findings from this study, this publication aims to serve as a guide for applying the ceramic bonding layer to metal surfaces and for conditioning methods. These practices are essential for enhancing the adhesion of ceramic materials to metal substrates. Full article

This study examines the capabilities and optimisation of electrochemical jet machining (ECJM), a component of the electrochemical machining (ECM) production chain. A localised electrolyte jet helps remove material from selective areas; it is a suitable process for contoured parts and hard-to-machine material without inflicting thermal or mechanical stresses. In this regard, the study incorporates details of an experimental layout and variation in parameters in terms of voltage, electrolyte concentration, and jet velocity. The most striking findings indicate that the material removal rate and surface quality are susceptible to parameters such as applied voltage and stand-off distance, and electrolyte concentration and jet velocity (via electrolyte supply rate) fixed. Higher voltages and fixed electrolyte concentrations give higher removal rates, though this might impair the surface finish, thereby requiring a trade-off at best. These results provide insights into optimising process parameters for enhanced precision and efficiency in ECJM. Future research could focus on advanced electrolytes and improving scalability for industrial applications. Full article

Thermal modification applies to a technique for the enhancement of biological durability, stability, and appearance of wood. Much is known about its effects on the chemical and physical attributes of wood. However, there is a knowledge gap concerning the effects of heat treatment on surface coating performance of different wood species. The focus of this research is heat treatment regulation of 160 °C, 180 °C, and 200 °C for three commercially important wood species which are Populus (poplar), Quercus (oak), and Pinus (pine). These treatments were evaluated in relation to coating performance indicators adhesion, integrity, and visual stability during and after natural and artificial weathering. It was revealed that specific responses among species differences exist. Populus behaved differently and exhibited a steady loss in mass and volume. Quercus demonstrated gradual degradation alongside enhanced lignin stability. Pinus exhibited maintenance of volume and mass until 180 °C after which accelerated degradation was observed. Coating durability and adhesion exhibited dependence on thermal condition, wood species, porosity, surface chemistry and microstructural variations that occurred. The research results can be used to streamline finishing processes for thermally modified wood while underscoring the critical nature of precise treatment parameter adjustments guided by species-specific responses to ensure long-term stability. Full article

The aim of the study was to determine the relationship between selected features of wood and the surface properties after sanding operations. Woods presenting different anatomical structures, i.e., ring-porous hardwood (European oak) and diffuse-porous hardwood (Norway maple), were used in the study. The wood surfaces were finished by sanding with aluminum oxide sandpapers of different grits: P60, P120, P180, and P240. It was shown that among the analyzed factors (wood species, anatomical section, measurement direction, and sandpaper grit size) and the interactions between them, the direction of measurement had the greatest influence (47%) on the Ra parameter values for oak wood. The sandpaper grit determined 22% of the Ra parameter variability. The measurement direction and the grit size of the sandpaper were identified as the most influential factors affecting the Rsm parameter values. Comparable patterns were observed in the case of Norway maple wood. Due to its diffuse-porous structure, the roughness of maple wood was less affected by the sandpaper grit compared to that of oak wood. Wood species had the greatest influence, increased from 41% to 71% when examining the contact angle at phase boundary wood-water after 3 s and 30 s. Sandpaper grit showed the greatest impact on the contact angles at the wood–diiodomethane phase boundary. This impact was practically at the same level after testing the contact angles after 3 s (27%) and after 30 s (28%). Wood species determined the color parameters, being responsible for 93% of the L* parameter, 50% of parameter a*, and 78% of parameter b*. The influence of sandpaper grit on the a* and b* parameter values was at a low level, i.e., 4%. SEM micrographs revealed the diverse structural characteristics of the wood following the sanding process. Full article

This study presents a reinforcement learning–based approach to optimize replenishment policies in the presence of uncertainty, with the objective of minimizing total costs, including inventory holding, shortage, and ordering costs. The focus is on single-level assembly systems, where both component delivery lead times and finished product demand are subject to randomness. The problem is formulated as a Markov decision process (MDP), in which an agent determines optimal order quantities for each component by accounting for stochastic lead times and demand variability. The Deep Q-Network (DQN) algorithm is adapted and employed to learn optimal replenishment policies over a fixed planning horizon. To enhance learning performance, we develop a tailored simulation environment that captures multi-component interactions, random lead times, and variable demand, along with a modular and realistic cost structure. The environment enables dynamic state transitions, lead time sampling, and flexible order reception modeling, providing a high-fidelity training ground for the agent. To further improve convergence and policy quality, we incorporate local search mechanisms and multiple action space discretizations per component. Simulation results show that the proposed method converges to stable ordering policies after approximately 100 episodes. The agent achieves an average service level of 96.93%, and stockout events are reduced by over 100% relative to early training phases. The system maintains component inventories within operationally feasible ranges, and cost components—holding, shortage, and ordering—are consistently minimized across 500 training episodes. These findings highlight the potential of deep reinforcement learning as a data-driven and adaptive approach to inventory management in complex and uncertain supply chains. Full article