Search Results (34)

Reducing the surface roughness of thermal barrier coatings (TBCs) improves engine aerodynamic efficiency and mitigates CMAS adhesion, but turbine blades’ complex geometries demand low-cost, damage-mzitigated finishing. This work employed drag finishing with spherical ceramic media, establishing a discrete element method (DEM) model to quantify abrasive trajectories, contact forces, and energy distributions, combined with surface characterization to study abrasive effects on columnar YSZ and modified GZO topcoats. Results show roughness reduction is constrained by fracture toughness and columnar unit local fracture, leading to different decay rates and late-stage improvement between YSZ and GZO. Introducing smaller abrasives enhances packing density via void filling, strengthens microscale cutting, and reduces strong normal impacts, promoting surface uniformization and suppressing localized damage. These findings guide mechanistic understanding of drag finishing on multi-material TBCs, as well as abrasive grading design and process parameter optimization. Full article

Background/Objectives: Silicosis caused by dust from engineered stone (ES) exposure is an emerging occupational lung disease that severely impacts respiratory health. This study aimed to analyze the association between cytokine profiles and disease severity and progression in patients with engineered stone silicosis (ESS) to assess their potential as biomarkers of progression and their usefulness to stratify risk. Methods: A longitudinal study was conducted with a seven-year follow-up (2017-2024) on 72 workers with simple silicosis (SS) or progressive massive fibrosis (PMF), all with a history of cutting, polishing, and finishing ES countertops. Data on lung function and levels of 27 cytokines were collected at four control points. Machine learning (ML) models were built to classify the disease stage and predict its progression. Results: 39% of patients with SS progressed to PMF. Significant differences in the expression of some cytokines were observed between ESS stages, suggesting a role in the evolution of the inflammatory process. Specifically, higher levels of IL-1RA, IL-8, IL-9, and IFN-$\gamma$ were found at checkpoint 1 in patients with PMF compared to SS. The longitudinal analysis revealed a significant relationship between IL-1RA and MCP-1$\alpha$ and disease duration with MCP-1$\alpha$ also being associated with time and disease grade. Machine learning (ML) models were built using the cytokines selected through a sequential backward feature selection. The Support Vector Machine model achieved an accuracy of 83% in classifying disease stage (SS, PMF), and of 77% in predicting the disease progression. Conclusions: The findings suggest that cytokines can be used as dynamic biomarkers to reflect underlying inflammatory processes and monitor disease evolution. The performance of ML algorithms to predict diagnostic status based on cytokine profiles highlights their clinical value in supporting early diagnosis, monitoring disease progression, and guiding clinical decisions. Full article

Wire electrical discharge machining (WEDM) is a standard micro-manufacturing technology. In WEDM, surface roughness (SR), deviation dimension (DD), and machining time (MT) are critical requirements that impact machining quality and are affected by various input parameters. The workpiece often performs multiple machining steps (roughing, semi-finishing, and finishing) to achieve high accuracy. Each machining step directly affects the accuracy and machining time, and the preceding machining step influences the subsequent machining step parameters. Many input control parameters regulate WEDM’s performance. Thus, optimizing process control parameters at each step is essential to achieve optimal results. This study investigates the influence of input parameters, including pulse on time (Ton), pulse off time (Toff), and servo voltage (SV), on SR, DD, and MT when machining AISI D2 mold steel through rough, semi-finish, and finish cutting. Taguchi and Analysis of Variance (ANOVA) are applied to analyze and optimize this WEDM process. The results display that the optimal surface roughness values for rough, semi-finish, and finish-cut stages are 2.03 µm, 1.77 µm, and 0.57 µm, corresponding to the parameter set of Ton = 6 μs, Toff = 10 μs, and SV = 30 V; Ton = 3 μs, Toff = 15 μs, and SV = 60 V; and Ton = 21 μs, Toff = 45 μs, and SV = 60 V, respectively. In addition, in the finish-cut stage, the parameters for optimal DD of 0.001 mm (0.04%) are Ton = 3 μs, Toff = 15 μs, and SV = 40 V. In contrast, those values for optimal MT of 218 s are Ton = 3 μs, Toff = 30 μs, and SV = 40 V. All optimal input values are confirmed by the manufacturing mold and die parts. Full article

Due to constantly shifting environmental and personal circumstances, humans have a wide range of thermal comfort needs. Cold intolerance (CI) is a personalized thermoregulation disorder characterized by a persistently cold-feeling problem, regardless of weather conditions. Improvements in clothing thermal comfort can help maintain proper insulation levels, hence reducing excess heat loss brought on by thermoregulation disorders since the wearer’s thermal comfort is impacted by controllable environmental and personal factors. Despite extensive research on cold-proof clothing, no studies have examined the current status of cold protective clothing systems when taking individual considerations into account, particularly those who use them and have cold sensitivity. There is a significant study gap in research on cold intolerance discomfort and advancements in appropriate cold protection apparel applied to individuals with thermoregulation disorders. Accordingly, this paper reviews the occurrence and severity of cold intolerance and its comfort challenges. It also addresses recent developments in cold protective clothing design, aimed at opening pathways for further investigation into adopting this cutting-edge technology for cold intolerance wear design. This review also aims to clarify the existing opportunities for enhancing the thermal insulation capabilities and other comfort factors of cold protection apparel, which are conducted during the stages of garment design and clothing material/textile manufacture. A thorough assessment of the research on introducing novel surface finishing methods in the pretreatment section and modifying the structural properties of garment materials at the fiber/yarn or weaving stage is conducted. Furthermore, we systematically discuss the potential design solutions regarding fit and size as well as stitching technologies during garment development for thermal insulation enhancement of cold protective clothing design. Full article

The Cutting Stock Problem (CSP) is an optimization challenge that involves dividing large objects into smaller components while considering various managerial objectives. The problem’s complexity can differ based on factors such as object dimensionality, the number of cutting stages required, and any technological constraints. The demand for coils of varying sizes and quantities necessitates intermediate splitting and slitting stages to produce the finished rolls. Additionally, relationships between orders are affected by dimensional variations at each stage of processing. This specific variant of the problem is known as the One-and-a-Half Dimensional Two-Stage Cutting Stock Problem (1.5-D TSCSP). To address the 1.5-D TSCSP, two algorithmic approaches were developed: the Generate-and-Solve (G&S) method and a hybrid Row-and-Column Generation (R&CG) approach. Both aim to minimize total trim loss while navigating the complexities of the problem. Inspired by existing problems in the literature for simpler versions of the problem, a set of randomly generated test cases was prepared, as detailed in this paper. An implementation of the two approaches was used to obtain solutions for the generated test campaign. The simpler G&S approach demonstrated superior performance in solving smaller instances of the problem, while the R&CG approach exhibited greater efficiency and provided superior solutions for larger instances. Full article

Difficult-to-cut titanium matrix composites (TMCs) are widely used in the aerospace, automotive, and defense sectors due to their excellent physical properties. Electrochemical mill grinding (ECMG) can achieve the processing effects of electrochemical milling and electrochemical grinding using the same tool, which has the potential to complete the rough and finish machining of TMCs in succession. However, in the rough machining stage, the bottom of the slot becomes concave due to the inevitable stray corrosion, leading to poor flatness, which increases the machining allowance for subsequent finish machining. In this paper, a bottom outlet hole layout of an abrasive tool with a diameter of 6 mm is proposed. Dynamic simulations demonstrate that the electrolyte flow rate in both side regions of the slot is significantly increased by the bottom outlet holes. The experimental results confirm that, compared with the tool without bottom outlet holes, a 61.2% reduction in the bottom flatness can be achieved when using the newly proposed tool during rough machining. After the finish machining, a slot with a width of 8 mm and a depth of 4.8 mm was obtained on the TMCs, which had a flat bottom and sidewall surface with good surface quality. Full article

The Alattu–Päkylä gold occurrence is located in the Northern Lake Ladoga area, in the Raaha-Ladoga suprasubduction zone, at the Karelian Craton (AR)—Svecofennian foldbelt (PR₁) boundary. Its gold ore mineral associations are of two types of mineralization: (1) copper–molybdenum–porphyry with arsenopyrite and gold (intrusion-related) and (2) gold–arsenopyrite–sulfide in shear zones. Optical and scanning electron microscopy, X-ray fluorescence spectrometry, inductively coupled plasma mass spectrometry (ICP-MS), instrumental neutron activation analysis (INAA) and fire analysis with AAS finishing were used to study them. Type 1 was provoked by shallow-depth tonalite intrusion (~1.89 Ga) and type 2 by two stages of Svecofennian metamorphism (1.89–1.86 and 1.83–1.79 Ga) with the possible influence of the impactogenesis of the Janisjärvi astrobleme (age ~1 Ga). Intrusive and host rocks were subjected to shearing accompanied by the formation of ore-bearing metasomatic rocks of the propylite-beresite series (depending on substrate) and quartz–sericite, quartz and sericite–tourmaline veins and streaks. Ore mineralization is present as several consecutive mineral associations: pyritic–molybdenite with arsenopyrite and gold; gold–arsenopyrite; quartz–arsenopyrite with antimony sulfosalts of lead; gold–polysulfide with tetrahedrite –argentotetrahedrite series minerals and gold–antimony with Pb–Sb–S system minerals and native antimony. Arsenopyrite contains invisible (up to 234 ppm) and visible gold. Metamorphosed domains in arsenopyrite and rims with visible gold around it are usually enriched in As, indicating higher (up to >500 °C) temperatures of formations than original arsenopyrite with invisible gold (<500 °C). A paragenetic sequence associated with the deposition of invisible and visible gold established at the Alattu–Päkylä ore occurrence: pyrrhotite + unaltered arsenopyrite (with invisible gold) → altered arsenopyrite (As-enriched) + pyrite ± pyrrhotite + visible gold. Gold, associated with gudmundite, sphalerite and native antimony, seems to be due to cainotypic rhyodacitic porphyry cutting tonalite intrusion or with a retrograde stage in post-Svecofennian metamorphism. The isotopic composition of Pb and ²³⁸U/²⁰⁴Pb (9.4–9.75) for the feldspar of the tonalite intrusion and the pyrite of gold mineralization, εNd (−4 up to −5) for tonalites and ẟ³⁴S values of −2.10–+4.99 for arsenopyrite, indicate the formation of gold occurrence provoked by Svecofennian magmatic and tectono-thermal processes with the involvement of matter from a mantle-lower crustal reservoir into magma formation and mineralization. Full article

Petunia stands as the top-selling bedding plant in the U.S., and improved lighting control in greenhouses holds the potential to reduce crop production time and optimize crop quality. This study investigated the impact of four distinct daily light integral (DLI) conditions with and without supplemental far-red (FR) radiation on the growth of petunia liners and subsequent development of finish plants. Two experiments were conducted in spring (9 April to 18 June 2021) and winter (28 October 2021 to 6 January 2022). Petunia cuttings were rooted in a common environment and then transferred to four greenhouse sections with different DLI treatments: 6, 9, 12, and 15 mol·m⁻²·d⁻¹ for four weeks. Within each DLI condition, half of the plants were exposed to 28 μmol·m⁻²·s⁻¹ supplemental FR radiation for 16 h daily (equivalent to 1.61 mol·m⁻²·d⁻¹ light integral). The number of flower buds and open flowers were tracked daily. Representative liners were destructively harvested and evaluated after four weeks of lighting treatments. The remaining plants were transplanted and moved to a common DLI condition of 15 mol·m⁻²·d⁻¹ for an additional three weeks before being destructively harvested and evaluated as finish plants. The primary finding reveals the promoting effect of DLI on flowering, branching, morphology, and biomass accumulation of petunia liners, with many effects persisting into the finish stage. A threshold DLI of 9 mol·m⁻²·d⁻¹ was identified, as lower DLI (6 mol·m⁻²·d⁻¹) resulted in extensive stem elongation, rendering the plants unmarketable. Higher DLI levels were found to be optimal in terms of flowering and morphology. Supplemental FR accelerated flowering by up to three days in the summer experiment and up to 12 days in the winter experiment. However, FR had limited impact on the number of flower buds and open flowers, branching, and shoot and root weight of the finish plants. Interactions between DLI and FR were observed on some parameters, whereby FR effects were more pronounced under lower DLI. Overall, both higher DLI and supplemental FR exhibited beneficial effects, but DLI had a more pronounced effect. Thus, DLI during petunia liner production appears more important than adding FR. This study well simulated the commercial propagation and production of petunia plants, providing practical insights for decision-making regarding lighting strategies. Full article

Two-dimensional ultrasonic-assisted grinding (2D-UAG) has exhibited advantages in improving the machining quality of hard and brittle materials. However, the grinding mechanism in this process has not been thoroughly revealed due to the complicated material removal behaviors. In this study, multi-step 2D-UAG experiments of silicon carbide are conducted to investigate the effects of machining parameters on surface quality. The experimental results demonstrate that the tool amplitude and the workpiece amplitude have similar effects on surface roughness. In the rough grinding stage, the surface roughness decreases continuously with increasing ultrasonic amplitudes and the material is mainly removed by brittle fracture with different surface defects. Under semi-finishing and finishing grinding steps, the surface roughness first declines and then increases as the tool amplitude or workpiece amplitude grows from 0 μm to 8 μm and the inflection point appears around 4 μm. The surface damage contains small-sized pits with band-like distribution and localized grooves. Furthermore, the influences of cutting parameters on surface quality are similar to those in conventional grinding. Discussions of the underlying mechanisms for the experimental phenomena are also provided based on kinematic analysis. The conclusions gained in this study can provide references for the optimization of machining parameters in 2D-UAG of hard and brittle materials. Full article

The machining of austenitic stainless steel alloys is usually characterized by high levels of adhesion and built-up edge; therefore, improving tribological conditions is fundamental to obtaining higher tool life and better surface finish. In this work, three different Al_0.6Ti_0.4N coatings are compared, two deposited by Cathodic Arc Evaporation (CAE) and one with High-Power Impulse Magnetron Sputtering (HiPIMS). The effects of the micromechanical properties and the microstructure of the coatings were then studied and related to the machining performance. Both arc-deposited coatings (CAE 1 and 2) exhibited similar average tool life, 127 min and 128 min, respectively. Whereas the HiPIMS lasted for only 21.2 min, the HiPIMS-coated tool had a much shorter tool life (more than six times lower than both CAE coatings) due to the intense adhesion that occurred in the early stages of the tool life. This higher adhesion ultimately caused built-up edge and chipping of the tool. This was confirmed by the cutting forces and more deformation on the shear band and undersurface of the chips, which are related to higher levels of friction. The higher adhesion could be attributed to the columnar structure of the HiPIMS and the (111) main texture, which presents a higher surface energy when compared to the dominant (200) from both arc depositions. Studies focused on tribology are necessary to further understand this relationship. In terms of micromechanical properties, tools with the highest plasticity index performed better (CAE 2 = 0.544, CAE 1 = 0.532, and HiPIMS = 0.459). For interrupted cutting machining where adhesion is the main wear mechanism, a reserve of plasticity is beneficial to dissipate the energy generated during friction, even if this was related to lower hardness levels (CAE 2 = 26.6 GPa, CAE 1 = 29.9 GPa, and HiPIMS = 33.6 GPa), as the main wear mechanism was adhesive and not abrasive. Full article

The prerequisite of the weld bead finishing is intricately linked to the quality of the welded joint. It constitutes the final, yet pivotal, stage in its formation, significantly influencing the reliability of structural components and machines. This article delineates an innovative post-weld surface finishing method, distinguished by the movement of a specialized cutting tool along a butt weld. This method stands out due to its singular approach to machining allowance, wherein the weld bead height is considered and eradicated in a single pass of the cutting tool. Test samples were made of AISI 304L, AISI 316L stainless steels and EN AW-5058 H321, EN AW-7075 T651 aluminum alloys butt-welded with TIG methods. Following the welding process, the weld bead was finished in accordance with the innovative method to flush the bead and the base metal’s surface. For the quality control of welded joints before and after the weld finishing, two non-destructive testing methods were chosen: Penetrant Testing (PT) and Radiographic Testing (RT). This article provides results from the examination of 2D profile parameters and 3D stereometric characteristics of surface roughness using the optical method. Additionally, metallographic results are presented to assess changes in the microstructure, the microhardness, and the degree of hardening within the surface layer induced by the application of the innovative post-weld finishing method. Full article

Zero-Defect Manufacturing (ZDM) is a promising strategy for reducing errors in industrial processes, aligned with Industry 4.0 and digitalization, aiming to carry out processes correctly the first time. ZDM relies on digital tools, notably Artificial Intelligence (AI), to predict and prevent issues at both product and process levels. This study’s goal is to significantly reduce errors in machining large parts. It utilizes data from process models and in situ monitoring for AI-driven predictions. AI algorithms anticipate part deformation based on manufacturing data. Mechanistic models simulate milling processes, calculating tool deflection from cutting forces and assessing geometric and dimensional errors. Process monitoring provides real-time data to the models during execution. The research focuses on a high-value component from the oil and gas industry, serving as a test piece to predict geometric errors in machining based on the deviation of cutting forces using AI techniques. Specifically, an AISI 1095 steel forged flange, intentionally misaligned to introduce error, undergoes multiple milling operations, including 3-axis roughing and 5-axis finishing, with 3D scans after each stage to monitor progress and deviations. The work concludes that Support Vector Machine algorithms provide accurate results for the estimation of geometric errors from the machining forces. Full article

Understanding surface roughness generation in machining is critical to estimate the final quality of the part, optimize cutting conditions, reduce costs and improve manufacturing sustainability in industry. This work presents a review of the factors that affect surface roughness generation in machining (turning/milling) processes. Up to twenty-five different factors were identified, which were classified as setup factors (cutting tool, machine tool/fixturing and workpiece factors), operational factors (cutting and process parameters) and processing factors, which are related to the resulting cutting processes, such as built-up edge, chatter or tool wear. The importance of understanding these factors to improve machining sustainability is highlighted through three case studies, ranging from a simple change in the cutting insert to a more complex case where a controlled surface roughness leads to the elimination of a grinding stage. A case study illustrating the potential benefit of MQL in the sustainability of the machining process is also reported from the mold manufacturing industry. In all of the cases, the improvement in sustainability in terms of the reduction in kg of CO₂ equivalent is notable, especially when grinding operations are reduced or eliminated from the manufacturing process. This paper can be of interest to practitioners in finishing operations at milling and turning operations that want to increase machining sustainability through a deep understanding of surface roughness generation. Full article

Precision edge preparation techniques for cemented carbides enable optimization of the geometry of tools’ cutting edges. These techniques are frequently used in high-stress environments, resulting in substantial improvements in tools’ cutting performance. This investigation examined the impact and evolution of cutting edge parameters and resulting surface finishes as a function of dry-electropolishing time on an end-mill. Findings demonstrate enlargement of the cutting edge radius, a decrease in surface roughness, and the mitigation of defects induced during previous manufacturing stages (i.e., smashed ceramic particles, burrs, chipping, etc.). Additionally, a direct correlation between dry-electropolishing time and primary cutting edges’ micro-geometry parameters has been established. Full article

This paper discusses a method of finish turning Inconel 718 alloy to compare machining performance of a naturally aged and used metalworking fluid (MWF), which had been conventionally managed through its life cycle, with the same new unaged product. The MWF concentrate was a new-to-market bio-ester oil, diluted with water to produce an emulsion. In the experiments, 50 mm diameter bars were turned down with multiple passes at a 250 μm depth of cut to reach a tool flank wear of 200 μm. The machining was interrupted at several stages to measure the flank wear and compare the chip forms for the aged and unaged MWF. The method of finish turning used a small tool nose radius and a small depth of cut that was found to be sensitive in detecting a difference in the flank wear and chip forms for the aged and unaged MWF. On the chemistry, the findings suggest that higher total hardness of the aged MWF was the cause of reduced lubricity and accelerated flank wear. This paper discusses the state of the art with the insights that underpin the finish turning method for the machinability assessment of MWFs. The findings point to stabilization of the MWF chemistry to maintain machining process capability over an extended sump life. Full article