Browse Topic: Cutting

Items (1,467)
This study investigates the characterization and dry machining performance of advanced physical vapor deposition (PVD) aluminum titanium nitride (AlTiN) and aluminum chromium titanium nitride (AlCrTiN) coatings deposited using three techniques: cathodic arc evaporation (CAE), high-power impulse magnetron sputtering (HiPIMS), and scalable pulse power plasma (S3p). The coatings were evaluated for thickness, microstructure, surface roughness, coefficient of friction (CoF), adhesion strength, and microhardness. Among the tested coatings, the S3p-deposited AlCrTiN showed the best performance, exhibiting the highest microhardness (40 GPa), the strongest adhesion (108 N), and the lowest CoF (0.25), along with a defect-free microstructure. Under the selected dry turning condition of 150 m/min cutting speed, 0.15 mm/rev feed rate, and 0.7 mm depth of cut, the S3p-deposited AlCrTiN coating achieved a maximum tool life of 10,800 mm, nearly three times higher than the CAE-deposited AlTiN coating. In contrast, CAE coatings showed comparatively lower hardness and weaker adhesion, with minimum values of 25 GPa and 68 N for C1, along with higher CoF values of 0.58–0.60. Furthermore, AlCrTiN coatings produced by HiPIMS and S3p provided 20–30% longer tool life than AlTiN coatings under identical cutting conditions, highlighting the importance of deposition technique.
Dinkar Sonawane, Gaurav
This study carefully designed and successfully developed a mechanical voltage stabilizing control device. The device uses silicone oil as the key component material of the liquid spring and 1Cr13 as the main material of the pressure control unit, enhancing its high-pressure resistance (up to 35 MPa), oxidation resistance, and acid-alkali corrosion resistance. By optimizing the transmission mechanism and simplifying the pressure regulation module, the device achieves a pressure regulation range of 0.1–21 MPa with an accuracy of ±0.01 MPa, significantly broader and more precise than traditional devices. To address manufacturing challenges, advanced CNC machine tools, ceramic cutting tools, and optimized heat treatment processes (e.g., quenching and tempering) were adopted, ensuring component machining accuracy within ±0.02 mm. Field applications in 13 oil wells demonstrated a 15.6% increase in daily oil production (from 25.5 t/d to 29.5 t/d) and a 17.9% increase in daily gas production (from 2800 m^3/d to 3300 m^3/d), with stable casing pressure control at 5.3 MPa. The device has created 1.225 million yuan in economic benefits while eliminating safety hazards, providing critical technical support for efficient and environmentally friendly oil and gas production.
Wang, GangLiu, CuicuiTong, DeshuiCao, JianMu, TaijiHan, Baidong
The cutting machine is a critical component in the cigarette processing line, and its cutting quality depends on the operational condition of the copper bar chain. The grooves on the surface of the copper bar chain accumulate dust during the operation of the machine, which often causes unstable conveyance of raw materials, significant width variations, and a high defect rate. To address this issue, this study developed a linear reciprocating automatic cleaning system for copper bar chains to remove dust from the groove surface and hinge joints. Experiments have verified that the system improved the cutting qualification rate, increased the operational stability of the cutting machine, reduced manual cleaning workloads, and reached higher cleaning efficiency. This innovative system is also expected to provide a valuable reference for similar equipment manufacturers and advance technological innovation in the cigarette processing industry.
Li, HaitaoZhang, ChunyuanFang, JunqingSu, LinChen, PengGuo, ZhiweiXing, Dongdong
This paper examines the temperature distribution during pipe cutting and the impact of the heat-affected zone on the mechanical microstructure and properties of steel pipes. Utilizing testing equipment such as K-type thermocouples, a MESTL-WELD thermocouple spot welding machine, and a DC5516H 16-channel temperature data logger, temperature tests were conducted on Φ 1016 × 17.5 mm X70M spiral seam submerged arc welded steel pipes and Φ 1016 × 21 mm X70M straight-seam submerged arc welded steel pipes. The results indicate that the maximum test temperatures during cutting were 953.8 °C and 1216.6 °C, respectively, with the duration of temperatures exceeding 400 °C at each test point not exceeding 30 seconds. By fitting the relationship curve between the peak temperatures of each test point and the cutting distance using the ExpDec3 model, it was found that the cutting distance corresponding to a temperature of 580 °C was 12 mm. Furthermore, mechanical microstructure and property tests were performed on the pipe body at different positions of the HAZ. Except for an anomaly in the yield strength of the rod-shaped tensile specimens of the Φ 1016 × 21 mm X70M welded pipe body, no other abnormalities were detected. Macroscopic metallographic examination revealed that the axial length of the HAZ at the end of the cut pipe did not exceed 7 mm. Microhardness testing showed significant fluctuations in the microhardness of the pipe body at the end of the cut pipe, while the microhardness of the pipe body beyond 10 mm from the end gradually returned to normal.
Xu, YanBai, QiangFeng, ZhenjunChang, YonggangLi, LiangPeng, Shibi
To enhance the service life of cemented carbide brazed circular saw blades used in sand willow stump cutting machines and to mitigate the problem of uneven stress distribution on saw teeth during cutting, this study investigates the circular saw blade as the research object. Sand willow, widely distributed in arid and desertification-prone regions of northern China, plays a vital role in ecological restoration and biomass utilization. However, due to the high density and toughness of its stems, conventional saw blades often experience severe tooth wear and premature failure, limiting the efficiency and stability of stump cutting operations. In this work, the dynamic simulation module of ABAQUS was employed to establish a finite element model of the cutting process. A Box–Behnken Design (BBD) combined with response surface methodology was then applied to systematically evaluate the influence of key tooth parameters on stress distribution. Using the maximum equivalent stress at critical nodes as the optimization criterion, a cooperative optimization strategy was developed to balance tooth strength and cutting efficiency. The optimized design markedly improved the mechanical performance of the saw teeth. Compared with conventional blades, the maximum stress value was reduced by 51%, resulting in enhanced reliability and prolonged service life. These findings demonstrate the feasibility of integrating finite element simulation with statistical optimization for tool design in forestry machinery, and provide both theoretical insights and practical support for advancing specialized sand willow cutting equipment, thereby contributing to ecological restoration and sustainable biomass utilization in desertification-affected regions.
Li, ZhongZhang, BinbinHan, YiliangHe, JinjunRen, YuyanYang, JianjunWang, HaichaoPei, Zhiyong
During the cutting process of low-stiffness structural components, the coupling effect between dynamic deformation and cutting forces presents a significant challenge in accurately predicting machining-induced deformations, thereby complicating quality control in the manufacturing of such parts. To address this issue, a cutting force-structural coupling simulation method that combines experiment and finite element is proposed, which takes into account the low-stiffness characteristics of structural components. Focusing on thin-plate parts as the research object, an orthogonal experimental scheme is designed considering workpiece thickness that serves as an indicator of rigidity. A milling force prediction model correlated with workpiece thickness is established. Based on the predicted cutting forces, a multi-analysis-step simulation method is introduced to analyze the machining deformation of structural parts. Additionally, a theoretical analytical model for the machining deformation of thin-plate workpieces is developed. A comparison between the theoretical and simulation results shows a relative error of less than 1.03%, validating the accuracy of the proposed simulation method. Finally, the exponential regression model for the machining deformation is constructed using training data obtained from the simulations. The prediction error of the regression model is less than 15%. The findings of this study are also applicable to predicting machining deformations in other large and low-stiffness structural components.
Zhao, YongshengGao, PengfeiXu, JingjingLiu, Zhifeng
Thin-walled structures with weak stiffness are widely applied in aerospace, precision machinery, and mold manufacturing; however, their machining processes are commonly challenged by insufficient rigidity, complex dynamic characteristics, and a high susceptibility to chatter. Due to the differentiated dynamic parameters of these structures at various spatial positions, the compliant interaction between the tool and workpiece during milling significantly increases the risk of chatter, thereby degrading machining precision, surface integrity and productivity. To this end, this research establishes a three degree of freedom (3-DOF) milling process dynamics model based on the full discretization method (FDM), which systematically obtains the modal parameters of the thin-walled component at different locations. Building upon this, position-dependent stability lobe diagrams for milling prediction are constructed to theoretically reveal the influence of local structural regions on milling stability. Furthermore, this paper proposes a multivariate nonlinear regression method to establish a nonlinear identification model for milling force coefficients. Key parameters were effectively identified through experiments, predicting the variation trends of force coefficients under different cutting conditions. Subsequently, cutting experiments were conducted across different spatial regions of the thin-walled structure to comparatively analyze stability performance under various combinations of cutting parameters. The results demonstrate that the established dynamic model and force coefficient identification method can effectively predict the milling stability of weak-stiffness structures at different physical locations and can well explain the spatial distribution characteristics of cutting chatter. This research proposes a novel method for position-dependent milling stability prediction, providing a theoretical foundation and experimental data support for resolving the issue of frequent chatter at different locations on weak-stiffness structures in practical machining, which holds significant engineering value for the efficient and stable processing of complex thin-walled components.
Xi, ChenhuiZhao, YongshengXu, JingjingGao, Pengfei
Metal fins with complex structural surfaces play a crucial role in cooling highly heat-intensive electronic products, and a facile method for fabricating such metal fins is urgently needed. Herein, a simple machining method was proposed for fabricating metal fins with novel waveform structures. The new machining method combined plowing extrusion and cutting (PE-C) processes, enabling one-step fabrication of wavy fins, exhibiting excellent flexibility and efficiency. The combined PE-C tool was first designed and manufactured. Subsequently, experiments for fabricating wavy fins were developed and conducted. Based on this, an in-depth analysis of forming procedures was performed using in-situ experimental insights. Moreover, forming characteristics of wavy fins under key parameters (e.g., the tool rake angle γ^c and the cutting velocity V^c) were discussed. Results show that the novel wavy fins were successfully manufactured by the proposed PE-C method. Wavy fins exhibited excellent, well-developed surfaces with a complete corrugation structure, and their geometric dimensions could be adjusted through processing parameters. The new PE-C method utilized two consecutive stages (i.e., the PE and cutting stages) to achieve the fabrication of wavy fins. The PE stage shaped the uncut metal surface into grooved structures, while the cutting stage transformed the groove structure into a waveform structure. Multiple folding principles, rather than conventional shear deformation, were utilized to achieve wavy fins. Reducing the γ^c and V^c would contribute to obtaining fins with the larger waveform structures. PE-C exhibited excellent potential in the field of heat exchange metal fin manufacturing.
Zhang, BaoyuLiu, ShudengYe, Zhitong
Aiming at the problems of seed cane pile-up and unstable seed supply efficiency in the sugarcane seed production line caused by the seed supply device, a stable seed supply control system was designed, which consists of a seed collection box, an elastic seed-clearing plate and an electrical control system, etc. The EDEM-RecurDyn coupling simulation was adopted to analyze the seed supply process, and the optimal elastic seed-clearing plate structure was designed. Using the single factor test and Box–Behnken experimental design analyzed the effects of the seed supply belt speed, the speed of the first conveyor belt, the number of sugarcane seeds in the collection box and the seed cutting efficiency on the supply efficiency. Establish a quadratic regression model for the efficiency of seed supply and determine the optimal parameter combination: the seed supply belt speed of 0.097 m/s, first conveyor belt speed of 1.639 m/s, and the number of sugarcane seeds is 14. Using the number of sugarcane seeds as the input quantity for the controller, the real-time data is fed back by the TOF sensor. The controller automatically adjusts the seed-cutting efficiency to maintain the continuity and stability of the seed supply process of the seed supply device. The test results show that after applying this system, the seed supply efficiency reached 1.77 setts/s, which was 6% higher than that of the fixed-parameter system. This research can provide technical support for the stable seed supply of integrated equipment for sugarcane seed production.
Li, ShangpingXu, HechangOuyang, RunhongLi, Kaihua
High-precision five-axis machining puts forward strict requirements for the stiffness and position stability of the AC double-angle milling head, especially when the gear transmission system is used under heavy cutting load and complex force coupling conditions. In the actual processing environment, the non-uniform deformation caused by structural coupling and load changes will directly affect the machining accuracy and stability. In order to solve these problems, this paper designs and analyzes a gear-type AC double-angle milling head with a pendulum structure and a layered modular structure. A parametric finite element model was established, and ABAQUS software was used to conduct a static analysis of two typical A-axis directions (0° and 90°), taking into account the internal prestressing force generated by gravity, cutting force, and gear meshing to reflect the typical working conditions. Under the same boundary conditions and load conditions, the influence of different structural materials on the overall stiffness was further studied through comparative analysis. The results show that under the conditions of five-axis linkage machining and positioning machining, the overall deformation of the milling head is maintained within the micron range, which meets the requirements of high-precision machining. The deformation behavior shows obvious dependence on the A-axis direction, reflecting the inherent anisotropic stiffness characteristics of the structure. Compared with the traditional structure, the proposed design has better rigidity performance under combined load conditions and provides practical reference values for the subsequent structural optimization, material selection, and precision control of high-performance five-axis CNC milling heads.
Xie, XinguiYuan, YongchaoQi, QuanLi, Xiangshuai
The development of lightweight materials for use in aerospace and automotive applications is extremely significant. Magnesium (Mg)-based alloys and composites are good candidate materials from the perspective of low density, good specific strength, and abundance. The Mg-4Zn alloy is one such alloy, which is a lightweight, biocompatible, and eco-friendly Mg-based alloy. In spite of these advantages, there is a strong need and scope to improve its wear resistance and mechanical properties. Mg-4Zn nanocomposites with Si3N4 reinforcements (a biocompatible bioceramic) are hypothesized to possess superior properties. Microstructural analysis of the vacuum stir-cast nanocomposites confirms grain refinement and a consequent increase in microhardness with an increase in Si3N4 reinforcement wt.%. The addition of Si3N4 reinforcement to improve the properties of the Mg-4Zn alloy could introduce challenges in machining. To make products from the nanocomposites, machining them with minimal subsurface defects with minimal energy consumption under sustainable conditions is necessary. The resultant machining force (Fr) is a good indicator of subsurface quality and energy consumption in machining. To investigate the effect of reinforcement wt.% and machining parameters on the resultant machining force, dry turning experiments on the vacuum stir-cast Mg-4Zn/Si3N4 nanocomposites were carried out based on the response surface methodology-based Box-Behnken design. It is observed that the regression model for Fr is influenced by the reinforcement wt.%, cutting speed, feed rate, and depth of cut and also their squares and their mutual interactions. Increase in microhardness, variation in porosity, thermal softening, and strain hardening contribute to the variation in Fr. Minimal Fr and hence better subsurface quality and lower energy consumption are obtained at mid values of Si3N4 reinforcement wt.% and cutting speed and low values of feed rate and depth of cut. The developed model is an excellent fit, with R2 and adjusted R2 values of 0.9907 and 0.9799, respectively.
N, AnandShaju, Tony MG, Nagamalleswara RaoD, BijulalK, Jayaprakash ReddyK, VijayanChaman, Joji J
In the automotive industry, during the early phase of development, numerical prediction of strength and durability of chassis parts become crucial as these predictions help in design optimization, selecting the appropriate material and identifying potential issues before physical prototypes are built. One of the crucial simulation requirements is the prediction of accurate load carrying capacity or bucking load of axle links. When it comes to the sheet metal axle links there is a deviation in the hardware test and CAE results for load carrying capacity due to the non-integration of forming effects in the numerical simulation, resulting in overdesign of parts, increased costs and development time. This study aims to address these challenges by integrating forming effects experienced by the part during forming process into static strength simulations. These effects include plastic straining, which contributes to material strain hardening and local thickness changes that lead to thinning. Both parameters are critical for accurately predicting the load carrying capacity of sheet metal axle parts. A multi-step forming simulation is carried out on a rear-axle sheet metal link, which involves simulating all the stages of the forming process to accurately predict the plastic strains and thickness changes. The forming simulations are performed using the anisotropic material model Banabic-Barlat-Comsa (BBC) to capture the anisotropy effects. This model uses several coefficients to precisely characterize the yield surfaces, considering both uniaxial and biaxial yield stresses, as well as anisotropy coefficients. The output of the forming simulation, Equivalent Plastic Strain (EPS) and thickness data, are then mapped on to the FEA model as initial conditions for static strength calculation.
R B, GovindSelvaraj, Nirmal Velgin
The number of female drivers in India is increasing alongside the rapid growth of the Indian automotive industry. A driving comfort survey conducted among female drivers revealed that many of them experienced discomfort when wearing safety belts—while driving and as front-seat passengers. This discomfort is primarily due to a phenomenon referred to as “neck cutting.” The root cause of neck cutting is likely related to vehicle design, which is traditionally based on Anthropometric Test Devices (ATD’s) representing the 5th, 50th & 95th percentile (%tile) of the global population. However, a literature review indicated that the anthropometric dimensions of the Indian populations are generally smaller than those of the global for the respective candidate. To validate the neck-cutting issue, various female candidates were asked to sit in the Driver’s seat for physical measurements trials. Accordingly, methodology was developed to quantify neck cutting parameters objectively. A correlation study was performed to align virtual simulation results with physical trials outcomes, to fine-tune the virtual methodology. Based on the findings, few recommendations were suggested which were evaluated against its effect on existing relevant standards.
Kulkarni, Nachiket AChitodkar, Vivek VEknath Chopade, SantoshMahajan, RahulYamgar, Babasaheb S
Although Ti-6Al-4V alloy offers high strength-to-weight ratio, corrosion resistance, and biocompatibility properties, its machining is challenging due to low thermal conductivity, high hardness, and chemical reactivity. This study examines turning of Ti-6Al-4V under minimum quantity lubrication (soybean oil). Cutting speed (CS), feed rate (FR), and depth of cut (DOC) are considered as the input parameters. On the other hand, material removal rate (MRR), tool wear rate (TWR), surface roughness (SR), and cutting force (Fc) are treated as the responses. Optimization of the said process is carried out using the mixed aggregation by comprehensive normalization technique (MACONT), a recently developed multi-criteria decision-making (MCDM) method. The optimal parameters are identified as CS = 72.26 m/min, FR = 0.022 mm/rev, and DOC = 0.2 mm, achieving high MRR with low TWR, SR, and Fc. The effects of different turning parameters on the responses are also investigated. Sensitivity analysis confirms robustness, and comparative evaluation with other MCDM tools validates accuracy of the adopted approach. The results demonstrate MACONT’s effectiveness in optimizing turning of hard-to-machine alloys, supporting greener and sustainable machining practices.
Das, Partha ProtimSharma, SaurabhChakraborty, Shankar
With the rapid development of the aviation industry, there is an increasing demand for safe apron operations and support capabilities. As a key facility in the apron fuel supply pipeline network, the performance and stability of the fuel hydrant well are crucial. However, the traditional repair and replacement process for fuel hydrant wells faces challenges, including lengthy construction times and significant impacts on airport operations. To address these issues, this article proposes a prefabricated refueling hydrant well technology, aimed at achieving rapid replacement of hydrants under non-stop construction conditions. Through on-site experiments, we have verified the feasibility of this prefabricated fuel hydrant well technology, determined the minimum dismantling boundary, and studied the rapid dismantling process, prefabricated pavement structure and installation process, as well as the application of self-compacting and fast-setting high-strength wellbore filling materials. The experimental results demonstrate that this technology can complete all processes within 12 hours and 34 minutes, including cutting the pavement, breaking the pavement, dismantling the old fuel hydrant well, installing a new type of hydrant well, installing prefabricated pavement, grouting, and filling joints, etc., without affecting oil pressure. The grouting material and the strength of the prefabricated pavement meet the design requirements, and the grouting effect is satisfactory. The connection between the fuel hydrant well and the pavement meets the operational requirements. This study provides a new technical solution for the repair and replacement of fuel supply hydrant wells in civil airports, which is expected to significantly enhance the safety guarantee capability of fuel supply in civil airports.
Ren, YuchengZhao, KunyangChang, LingsuWang, XiangjunHan, TianhuiLi, Zonghe
Hard carbon steel is used for drilling deep holes, such as C19, which has dimensions of 630 mm in length, 50 mm in breadth, and 125 mm in depth. Long twist drills with a diameter of 8 mm are used. Such drills are manufactured with larger helix than the traditional drills for increasing penetration efficiency. But, Prediction of long drill & tool replacement strategies during metal cutting are mostly depend on conservative estimation given by manufacturer’s catalog. Hence, long drill while drilling cam shaft in automobile applications may be underutilized or over utilized. Now a day, Diagnostics software in advanced CNC machines are indicating hours of utilization of tools in bar chart. On the other hand, Utilization of long drill wear beyond the recommended range affects the quality of workpiece. As a result, several researchers have proposed the reliable approach of vibration-based online monitoring of drill flank wear over the past 20 years. In these works, the vibration sensor is mounted on the workpiece, allowing for good signal strength acquisition with little variation in distance from the drill holes and drill wear monitoring. The sensor cannot be placed in a fixed location that is equally spaced from all of the holes that need to be drilled for practically all workpiece profiles. In this project endeavour, the peck drilling technique utilising vibration monitoring is proposed. The monitoring metrics of amplitude (N/m2) and frequency (Hz) are introduced through the examination of vibration in both the time and frequency domains. Experimental results show that percentage variation in long drill wear during severe wear and corresponding vibration signals of amplitude variation of long drill frequency is increasing five times than compared the vibration signals with other stages in the peak search method. This provides greater flexibility in replacement strategy of long drill through vibration analysis and higher percentage variation indicates that substantial to use for drilling.
R. S., NakandhrakumarRaja, SelvakumarElumalai, SangeethkumarVelmurugan, RamanathanM, Ramakrishnan
Earthmoving machines are equipped with a variety of ground-engaging tools that are joined by bolted connections to improve serviceability. These tools are made from heat-treated materials to enhance their wear resistance. Attachments on earthmoving machines, including buckets, blades, rippers, augers, and grapples, are specifically designed for tasks such as digging, grading, lifting, and breaking. These attachments feature ground-engaging tools (GET), such as cutting bits or teeth, to protect the shovel and other earthmoving implements from wear. Torquing hardened plates of bolted joint components is essential to ensure uniform load distribution and prevent premature failure. Therefore, selecting the proper torque is an important parameter. This study focuses on analyzing various parameters that impact the final torque on the hardened surface, which will help to understand the torque required for specific joints. Several other parameters considered in this study include hardware material, coefficient of friction, end bit and cutting-edge material, and their hardness. Understanding the influence of surface hardness on bolted joint torque is crucial for optimizing performance, reliability, and longevity of bolted connections in various engineering applications
Parameswaran, Sankaran PottiBhosale, DhanajiKumar, Rajeev
Handheld outdoor power equipment is utilized globally to shape and maintain the environment, serving as daily assistants in forestry under demanding conditions. In the power tool sector, the transition from petrol to battery-powered products is already well underway, particularly for consumer applications. However, internal combustion engines will continue to be indispensable for professional users of power tools, who place the highest demands on their equipment in terms of performance and energy density. These power tools are often used in remote locations and thus far away from a possible charging infrastructure. To contribute to climate protection, biofuels and RFNBOs are crucial. The continuous optimization of engine technology and its overall system, including cutting tools (such as saw chains and cutting wheels), is a key development goal for STIHL. The optimized interaction between the saw chain, guide bar, and power train is necessary for efficient work progress and ergonomic handling of the products during operation. Consequently, STIHL focuses on the overall system in design and development, supported by the in-house manufacturing of all critical components. The newly developed STIHL Hexa saw chain is an innovative system featuring a new tooth shape, representing a significant milestone. The Hexa sharpening pattern and narrow kerf enhance the cutting performance of the previous standard saw chain by up to ten percent. This improvement is clearly noticeable to professional users during felling, limbing, and cutting to length. The saw chain also remains sharp for a longer period and has an extended service life with optimal cutting performance. This means that the energy used is converted into work progress with higher efficiency. When combined with a highly efficient two-stroke engine and sustainable fuels, not only the energy consumption per cutting surface is reduced, but CO2e emissions are also significantly lowered. This comprehensive package contributes positively to climate protection during sequential timber harvesting.
Beck, Kai W.Maier, GeorgMüller, MatthiasLux, ThomasKölmel, ArminLochmann, HolgerMelder, Jens
This SAE Aerospace Recommended Practice (ARP) covers procedures or methods to be used for fabricating, handling, testing, and installation of oxygen lines in an aircraft oxygen system.
A-10 Aircraft Oxygen Equipment Committee
SAE TOMORROW TODAY - How Simulation is Shaping the Future of Motorsports135277/24/2025
From driver training to vehicle engineering and strategy development, simulation is no longer just a tool -- it's a competitive advantage. Top racing teams are using simulators to optimize car setups, dramatically cutting down on testing time and maximizing on-track performance. But the impact of simulation goes far beyond the racetrack. With cutting-edge realism and high-bandwidth systems, Dynisma is helping elite drivers stay sharp while accelerating product development for automotive manufacturers. Dynisma Motion Generators (DMGs) create detailed 3-D environments that include driver behavior and environmental factors, and accurately model the physical characteristics of vehicles, such as tire performance and surface interactions. To learn more, we sat down with Simon Holloway, Commercial Director, to discuss how Dynisma's data-driven engineering is revolutionizing simulation in both the motorsport and automotive sectors to enhance performance, safety, and efficiency. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, Twitter, and YouTube. Follow host Grayson Brulte on LinkedIn, Twitter, and Instagram.
Patterson, Lori
The utilization of Inconel 718 is increasing daily in stringent operating conditions such as aircraft engine parts, space vehicles, chemical tanks, and the like due to its physical properties such as maintaining strength and corrosion resistance at higher temperature conditions. Besides, Inconel 718 is one of the difficult materials for machining because of maintaining its strength at elevated temperature, which generates higher cutting force leading to observed multiple tool wear mechanisms that affect the surface quality; lower thermal conductivity of materials produces high temperature generation that impacts the tool performance by reducing tool life. In addition, the presence of carbides and high hardness of IN 718 affects the machining performance. Therefore, in this view, this article describes the effect of cutting environments and machining parameters on the machining of Inconel 718 and optimizes the cutting conditions for sustainable machining. Three input parameters namely cutting speed, feed rate, and depth of cut as well as three cutting environments such as flood cooling, MQL (minimum quantity lubrication), and NMQL (nano minimum quantity lubrication) were considered for the experimentation. Experimental runs were designed based on the Taguchi method, which had a total of 27 runs performed on the CNC turning. TiAlN-coated triangular-shaped cutting inserts were used for all experimental runs. This research study addresses three output parameters namely surface roughness, tool wear, and cutting temperature. Finally, the cutting condition was optimized by using the Taguchi method and predicting the relationship between the input parameters and the output parameter using the RSM method. Experimental results observed that the NMQL cutting environment shows better machining performance than the MQL and flood cooling due to the presence of nanoparticles in the base fluid, which act as heat carriers. Whereas minimal surface roughness 0.4 μm and lower cutting temperature (85°C) were observed at low cutting speed, feed rate, and depth of cut (78.54 mm/min, 0.1 mm/rev, 0.1 mm) combination and minimum tool wear was found in moderate cutting speed conditions (117.81 mm/min, 0.1 mm/rev, 0.1 mm). Whereas highest cutting temperature and tool wear such as 130°C and 0.3 mm, respectively, observed in flood cooling environment at the cutting speed (157.08 mm/min, 0.3 mm/rev, 0.3 mm). Using the Taguchi method optimum condition was found in the NMQL cutting environment, at the combination of cutting speed 78.54 m/min, feed 0.1 mm/rev, and depth of cut 0.1 mm. From the ANOVA results, develop the predictive model whose results match with the experimental result. Finally, regression model was developed between the response variable and input parameters.
Mane, Pravin AshokDhawale, Pravin A.Nipanikar, SureshKhadtare, Avinash N.
Hybrid additive manufacturing (AM) and subtractive manufacturing (SM) processes utilize the combination of AM (e.g., LPBF and DED) and SM (e.g., milling and turning operations) to produce the final part. Due to the poor surface roughness resulting from the uneven melting of powders in AM, the subtractive process is a necessary finishing operation to improve the surface roughness of the AM part. The hybrid AM/SM technology combines the benefits of AM and SM processes to create complex geometry while introducing good surface finish and compressive stress to prevent crack initiation. However, the relationship between large process parameter space and the residual stress/distortion in the part is not well understood, which impedes the adoption of hybrid AM/SM to minimize the residual stress in the final product. To expedite the process optimization, we establish a pipeline for the sequential modeling of additive manufacturing (AM) and subtractive manufacturing (SM) processes. Key accomplishments achieved under this study include (1) development of thermal abstraction technique for the AM process to speed up the macroscale level heat transfer analysis based on the manufacturing factors including scanning vector, laser power, dwelling time, etc.; (2) development of the sequentially coupled thermal-mechanical model to predict the residual stress and distortion after AM process by passing the temperature history obtained from heat transfer analysis to the mechanical analysis at each time point; (3) validation of the thermal-mechanical model for AM using thin-wall structure from literature and cantilever beam structure from UNT’s experiments data; (4) conduction of the parametric study on the chamber temperature and part design in the AM process to demonstrate how the temperature gradient and supporting structure affect the residual stress and distortion; (5) exploration of macro and micro scale models to predict the bulk and surface residual stress after cutting; (6) applying the developed modeling framework to tailoring the hybrid AM/SM process. To support model verification and demonstration, we print cantilever beam structure with different supporting structure designs and cutting strategies to study how these factors affect the final part residual stress and distortion. The data collected in the printing and cutting process is used to examine the applicability of the developed simulation tool.
Lua, JimLi, RuiRajanna, ManojHaridas, Ravi SankarMishra, Rajiv
SAE TOMORROW TODAY - How Autonomy is Breathing New Life into Farming135155/19/2025
Labor shortages are pushing many family farms to the brink. The solution? Autonomous technology which is emerging as a game-changer--boosting productivity, cutting risk, and giving family farms a fighting chance to thrive for generations to come. At the forefront of this transformation is Blue River Technology, a John Deere subsidiary leading the charge in precision agriculture. From AI-driven tools to autonomous machinery, the company is helping to build the future of farming the John Deere way, meeting farmers in the field and designing solutions grounded in real-world challenges. With safety and scalability built in, farmers can start small with retrofit kits that upgrade existing tractors, making automation more accessible than ever. To learn more, we caught up with Aaron Wells, Director of Engineering at Blue River, to explore how automation is transforming agriculture and giving farmers the tools they need to stay ahead--despite labor challenges. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, Twitter, and YouTube. Follow host Grayson Brulte on LinkedIn, Twitter, and Instagram.
Hineman, Marcie
This specification covers procedures for sampling and testing aircraft-quality, special aircraft-quality, and premium aircraft-quality steels requiring transverse tensile property testing.
AMS E Carbon and Low Alloy Steels Committee
The current ASTM A653 standard for determining the bake hardening index (BHI) of sheet metals can lead to premature fracture at the transition radius of the tensile specimen in high strength steel grades. In this study, a new test procedure to characterize the BHI was developed and applied to 980 and 1180 MPa third generation advanced high strength steels (3G-AHSS). The so-called KS-1B methodology involves pre-straining over-sized tensile specimens followed by the extraction of an ASTM E8 sample, paint baking and re-testing to determine the BHI. Various pre-strain levels in the range of 2 to 10% were considered to evaluate the KS-1B procedure with select comparisons with the ASTM A653 methodology for pre-strain levels of 2 and 8%. Finally, to characterize the influence of paint baking at large strain levels, sheared edge conical hole expansion tests were conducted. The tensile mechanical properties of the 3G steels after paint baking were observed to be sensitive to the pre-strain with bake hardening indices exceeding 100 MPa. However, the sheared edge formability was not significantly affected by paint baking.
Northcote, RhysBerry, AvalonNarayanan, AdvaithTolton, CameronLee, HaeaSmith, JonathanMcCarty, EricButcher, Cliff
Mechanical analysis was performed of a non-pneumatic tire, specifically a Michelin Tweel size 18x8.5N10, that can be used up to a speed of 40 km/h. A Parylene-C coating was added to the rubber spoke specimens before performing both microscopic imaging and cyclic tensile testing. Initially, standard ASTM D412 specimens type C and A were cut from the wheel spokes, and then the specimens were subjected to deposition of a nanomaterial. The surfaces of the specimens were prepared in different ways to examine the influence on the material behavior including the stiffness and hysteresis. Microscopic imaging was performed to qualitatively compare the surfaces of the coated and uncoated specimens. Both coated and uncoated spoke specimens of each standard type were then subjected to low-rate cyclic tensile tests up to 500% strain. The results showed that the Parylene-C coating did not affect the maximum stress in the specimens, but did increase the residual strain. Type C specimens also had a higher maximum stress on average than the Type A specimens. These mechanical tests provide useful data to determine material properties, such as Ogden material parameters, for future simulation of both the hyperelastic and hysteresis behavior of the rubber spokes.
Collings, WilliamLi, ChengzhiSchwarz, JacksonLakhtakia, AkhleshBakis, CharlesEl-Sayegh, ZeinabEl-Gindy, Moustafa
Abrasive water jet (AWJ) machining is the most effective technology for processing various engineering materials particularly difficult-to-cut materials such as aluminum alloys, steels, brass, ceramics, composites, and the like. The present study focuses on the experimental study on surface roughness and kerf taper is carried out during AWJ machining of Al 6061-T6 alloy with 40 mm thickness, and the influence of process parameters includes water jet pressure, standoff distance, and abrasive flow rate on the kerf taper and surface roughness is analyzed. The number of experiments is designed using Taguchi’s L9 orthogonal array. Experimental results are statistically analyzed using ANOVA. Also gray relational analysis (GRA) coupled with principal component analysis (PCA) hybrid approach was implemented to optimize the performance parameters. From the results it is found that standoff distance and hydraulic jet pressure are the most influencing parameters on surface roughness and kerf taper.
Kolluri, Siva PrasadSrikanth, V.Ismail, Sk.Bhanu, C.H.
The experimental investigation analyzed the performance of three machining conditions: dry machining, cryogenic machining, and cryogenic machining with minimum quantity lubrication (MQL) on tool wear, cutting forces, material removal rate, and microhardness. The outcome of this study presents valuable knowledge regarding optimizing conditions of turning operations for Ti6Al4V and understanding the machinability under cryogenic-based cooling strategies. Based on the experimentation, cryogenic machining with MQL is the most beneficial approach, as it reduces cutting force and flank wear with a required material removal rate. This strategy significantly enhances the machining efficiency and quality of Ti6Al4V under variable feed rates (0.05 mm/rev, 0.1 mm/rev, 0.15 mm/rev, 0.2 mm/rev, 0.25 mm/rev) where cutting velocity (120 m/min) and depth of cut (1 mm) are constant. The effects of the main cutting force, feed force, thrust force, material removal mechanism, flank wear, and microhardness on machining performance have been analyzed in this research work. It has been observed that higher cutting forces result in greater energy transferred to the workpiece material, leading to more effective material removal, and chip thickness is reduced in cryogenic plus MQL conditions compared to dry and cryogenic machining due to the excellent cushioning effect and reduced adhesion.
Misra, SutanuKumar, YogeshPaul, GoutamForouhandeh, Fariborz
Surface roughness is a key factor in different machining processes and plays an important role in ergonomics, assembly process, wear and fatigue life of components. Other factors like functionality, performance and durability of parts are also affected by surface roughness. Although maintaining an optimum surface roughness is a major challenge in many manufacturing industries. Surface roughness during machining depends upon machining parameters such as tool geometry, feed rate, depth of cut, rotational speed, lubrication, tool wear, etc. Tool vibrations during machining also have significant influence in surface roughness. In this work an attempt is made to predict the surface roughness of machined components made by the turning process by using machine learning of tool vibration signals. By varying different machining parameters and keeping other tooling and material properties same, a range of surface roughness values can be obtained. For each condition, corresponding tool vibration signals were recorded. Our experimental setup involves a vibration data collector which is used for recording vibration signals generated during the turning operation. The collected data preprocessed and categorized into training and test sets. Various machine learning regression techniques including Linear Regression, Ridge Regression, Support Vector Regression (SVR), Decision Tree Regression, Random Forest Regression, Gradient Boosting Regression, K-Nearest Neighbors Regression (KNN), and Neural Network Regression were used to predict the surface roughness. The study highlights the importance of feature extraction and model selection in achieving accurate and reliable surface roughness predictions, ultimately contributing to enhanced machining process control and product quality.
S S, SafeerSadique, AnwarD, Navaneeth
In automotive applications, most of the engineering components come across the material removal process in manufacturing. Face milling is one of the prominent material removal processes wherein a multi-point cutter is used to machine the flat workpiece to bring it to its required dimension. In the material removal process, the cost of the cutting tool occupies the major part of the total manufacturing cost of a product. Also, the continuous usage of the cutting tool results in tool wear. The usage of the cutting tool after the threshold value of the tool wear deteriorates the surface finish of the workpiece which leads to product rejection. Hence, optimal tool usage is inevitable. The continuous monitoring of the cutting tool condition will ensure optimal tool usage. In the present work, four real-time tool conditions are considered, namely, fresh tool (G), tool flank wear (FW), tool flaking on rake surface (FL) and tool with broken tip (B). Vibration signals are acquired while milling mild steel workpiece with cutting tools of considered conditions. From the vibration signal, Discrete Wavelet Transform (DWT) features are extracted and the top-ranked wavelet member in terms of classification accuracy of the tool condition is selected using the Decision Tree (DT) algorithm. The Mean Squared Energy (MSE) of the detailed coefficients of the selected wavelet member is computed and that forms the features set. Then the classifying ability of Machine Learning (ML) algorithms such as Support Vector Machine (SVM), and Naïve Bayes (NB) are analysed using the feature set. The results show that the NB outperformed the SVM with the MSE of selected wavelet members derived from DWT.
D, Pradeep KumarSyed, ShaulV, MuralidharanS, Ravikumar
Inconel 800H superalloy is a difficult-to-turn material. This study aims to achieve optimal machining results, including reduced cutting force, improved surface roughness, and minimized residual stress, by optimizing input machining parameters like cutting speed, feed rate, spraying angle, and nozzle distance on Inconel 800H. The Taguchi L27 method is utilized for experimentation, while the Harris hawks optimizer (HHO) is applied in a multi-objective optimization model. Additionally, the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) is used to identify the optimal input parameters. Five distinct weight schemes were employed, including the Analytic Hierarchy Process (AHP), the Entropy weight method, Criteria Importance through Inter-Criteria Correlation (CRITIC), Grey relational analysis (GRA), and Principal Component Analysis (PCA) to determine response weights. The analysis revealed that the primary factor affecting all measured weights is the feed rate, with the nozzle angle closely followed, as determined by ANOVA, based on a comprehensive evaluation of all output responses. Notable enhancement in MQL turning when contrasted with dry turning, reflected in the output responses of roughness, force, and residual stress at 72.62%, 8.08%, and 19.32%, respectively, using AHP-TOPSIS compared to AHP-HHO.
Kannan, VenkatesanMokshajna, Kotha
This specification covers requirements for the superfinishing of High Velocity Oxygen/Fuel (HVOF) applied tungsten carbide thermal spray coatings.
AMS B Finishes Processes and Fluids Committee
This study focuses on machining automobile parts such as drive shafts and axles made of low alloy steel AISI 4140. The influence of cutting inserts geometrical parameters, viz., relief angle (RIA), rake angle (RAA), and nose radius (NA) are studied by designing experiments using Taguchi’s methodology. Numerical simulation is conducted using DEFORM-2D; a suitable L9 orthogonal array (OA) is considered for this work for varying combinations of inputs, and the resultant cutting force, maximum principal stress, and tool life are determined. Adopting a signal-to-noise (S/N) ratio minimizes the outputs for better machining conditions and achieves high-quality components with precision, tolerance, and accuracy. The ideal conditions obtained from the S/N ratio are RAA of 6°, RIA of 3°, and NR of 0.6 mm. Analysis of variance presents that the NR influences the resultant cutting force, wear depth, and work piece damage 73.51%, RAA following by 23.99%, and RIA by 2.03% achieved with a R2 value of 99.53%.
Senthilkumar, N.
This study describes the Taguchi optimization process applied to optimize drilling parameters for glass fiber reinforced composite (GFRC) material. The machining process is analyzed in relation to process parameters using analysis of variance (ANOVA). The characteristics assessed for both the drilling and the specimen include speed, feed rate, drill size, and specimen thickness. The commercial software program MINITAB14 was used to collect and analyze the measured results. Cutting force and torque during drilling are examined in relation to these parameters using an orthogonal array and a signal-to-noise ratio. The primary goal is to identify the critical elements and combinations of elements that impact the machining process to achieve minimal cutting thrust and torque, based on the evaluation of the Taguchi technique.
Raja, RosariJannet, SabithaKandavalli, Sumanth Ratna
The goal of this work is to increase the accuracy and efficiency of hose cutting operations in small scale industries is by designing and building an automatic hose-cutting equipment. The device uses a computer-controlled system to autonomously cut pipes of various sizes and lengths. By means of a stepper motor-driven, rapidly spinning blade, the cutting process is accomplished. Additionally, the machine has sensors that measure the hose's length and modify the cutting position as necessary. Premium components and materials are used in the machine's construction; these are chosen for their performance and longevity. The device is able to boost cut precision and raise industry production all around from 100% to 190% efficient system thereby decreasing labor and time needed for hose cutting operations.
Feroz Ali, L.Manikandan, R.Madhankumar, S.Sri Hari, P.Suriya Prakash, T.Vishnu Doss, G.
Since the inception of battery driven electric vehicles in the automotive world, there has been a constant challenge in maximizing the range of an electric vehicles through various means including battery technology, vehicle weight optimization, low drag coefficients etc. The tires being a viscoelastic composite material have now become a vital to the range performance of an EV. The rolling resistance of a tire is now become a hotter topic than ever. The rolling resistance coefficient (RRC) is the measure of energy loss during rolling due to viscoelastic dissipation in the tire. The viscous dissipation in tire arises due to hysteresis in the various components of a tire including tread, sidewall, inner liner, apex etc rubber compounds. The internal friction between layers of body ply, steel belts and tread crown ply also contribute to the internal heat generation. Therefore, the development of ultra-low RRC tires is a serious challenge for tire engineers. Nevertheless, the recent advances in the tire technology, which include introduction of new generation reinforcing fillers in rubber compounds, tread pattern design and construction matrix optimization, allow the tire experts to carefully select the suitable material and design parameters to meet the performance characteristics and durability of an EV tire. This paper demonstrates the scientific way of analysing cut and chip failure in tires which is one of the most frequent and troublesome challenges in the development cycle of low RRC tires. The various material characterization techniques which include viscoelastic behaviour of tread rubber compound, polymer-filler interaction and filler dispersion in tread rubber compound were studied along with the tire footprint characteristics. Eventually a better comprehensive understanding was drawn on the impact of material behaviour and tire characteristics on the cut and chip damage of ultra-low RRC tires for Electric Vehicle (EV) vehicles.
Mishra, NitishSingh, Ram Krishnan
Most rechargeable batteries that power portable devices, such as toys, handheld vacuums, and e-bikes, use lithium-ion technology. But these batteries can have short lifetimes and may catch fire when damaged. To address stability and safety issues, researchers reporting in ACS Energy Letters have designed a lithium-sulfur (Li-S) battery that features an improved iron sulfide cathode. One prototype remains highly stable over 300 charge-discharge cycles, and another provides power even after being folded or cut.
This work aims to define a novel integration of 6 DOF robots with an extrusion-based 3D printing framework that strengthens the possibility of implementing control and simulation of the system in multiple degrees of freedom. Polylactic acid (PLA) is used as an extrusion material for testing, which is a thermoplastic that is biodegradable and is derived from natural lactic acid found in corn, maize, and the like. To execute the proposed framework a virtual working station for the robot was created in RoboDK. RoboDK interprets G-code from the slicing (Slic3r) software. Further analysis and experiments were performed by FANUC 2000ia 165F Industrial Robot. Different tests were performed to check the dimensional accuracy of the parts (rectangle and cylindrical). When the robot operated at 20% of its maximum speed, a bulginess was observed in the cylindrical part, causing the radius to increase from 1 cm to 1.27 cm and resulting in a thickness variation of 0.27 cm at the bulginess location. However, after optimizing the speed at 35% of its maximum speed, 100% dimensional accuracy was achieved. The integration resulted in collision-free robot and extrusion movement, flexibility, capability of making large parts, and enhanced dimensional accuracy.
Srivastava, KritiKumar, Yogesh
Super Duplex Stainless Steels (SDSS) are attracting attentions of the manufacturing industries due to the excellent corrosion resistance to critical corrosion. But SDSS2507 is the hardest to machine with lowest machinability index among DSS family. Moreover, formation of built-up layer (BUL) and work hardening tendency makes it further difficult to machine. Researchers have the conflict in opinions on using wet machining or dry machining using tool coatings. In this investigation SDSS2507 machining is carried out using uncoated and PVD–TiAlSiN-coated tools. The wet and dry machining environment are compared for increase in cutting speed from 170 m/min to 230 m/min. Excellent properties of PVD–TiAlSiN coatings exhibited microhardness of 39 GPa and adhesion strength of 88 N, which outperformed the uncoated tools. Tool life exhibited by coated tools was four times higher than uncoated tools. Wet machining was found to be ineffective when PVD-coated tools are used, exhibiting the same performance as that of dry machining. Dry machining can be preferred for the machining SDSS2507 with PVD–TiAlSiN-coated tools, eliminating the cost of cutting fluids with enhanced productivity.
Sonawane, Gaurav DinkarBachhav, Radhey
The primary objective of this article is to study the improvement of machining efficiency of EN-31 steel by optimizing turning parameters using newly developed cutting fluids with different proportions of aloe vera gel and coconut oil, utilizing the Taguchi technique. Furthermore, performance metrics including material removal rate (MRR), surface roughness, and tool wear rate (TWR) were assessed. Analysis of variance (ANOVA) suggested that as cutting speed and feed increase, the MRR is positively influenced, but likewise tool wear is intensified. The surface roughness exhibited a positive correlation with cutting speed, and a negative correlation with increasing both cutting speed and feed. It was found that the maximum MRR value was attained at a cutting speed of 275 m/min, a feed rate of 1.00 mm/rev, and a cutting fluid composition of 30% aloe vera and 70% coconut oil. For the best surface smoothness, it is advisable to adjust the cutting speed to 350 m/min and the feed rate to 0.075 mm/rev. A cutting speed of 275 m/min and a feed rate of 1.00 mm/rev led to a lower TWR. The results suggest that the combined use of coconut oil and aloe vera as cutting fluids improves the turning quality of EN-31 steel, particularly when employing a combination of 30% aloe vera and 70% coconut oil. As a possible solution for performance problems in achieving desired results during the turning of EN-31 steels, these recommendations may be used in industries to enhance turning performance.
Premkumar, R.Ramesh Babu, R.Saiyathibrahim, A.Murali Krishnan, R.Vivek, R.Jatti, Vijaykumar S.Rane, Vivek S.Balaji, K.
High productivity, low manufacturing costs, and high workpiece quality: these are the key factors that deliver sustainability, profitability, and competitive edge for industrial manufacturers. Reliable machine monitoring yields valuable real-time insights into ongoing processes; it is the basis for dependable, productive, and reproducible manufacturing and it helps machine operators to reach well-founded decisions on both short- and long-term improvements. This technology can even capture anomalies in highly dynamic machining processes, so users can respond instantly to ensure high productivity, decrease scrap rates, and prolong tool lifetimes. Thanks to all these advantages, continuous machine and process monitoring based on suitable sensor technology is a critical success factor in today’s manufacturing industry.
This research explores the experimental analysis of titanium alloy using an innovative approach involving a 2–7% carbon nanotube (CNT)-infused cubic boron nitride (CBN) grinding wheel. Employing a full-factorial design, the study systematically investigates the interactions among varied wheel speed, workpiece feed rate, and depth of cut, revealing compelling insights. The integration of CNTs in the CBN grinding wheel enhances the machining performance of titanium alloy, known for its high strength and challenging machinability. The experiment varies CNT infusion levels to assess their impact on material removal rate (MRR) and surface finish. Significantly, MRR is influenced by CNT content, with 5% and above demonstrating optimal performance. The 7% CNT-CBN wheel exhibits a remarkable 61% improvement in MRR over the conventional CBN wheel. Interaction studies highlight the pivotal role of depth of cut, indicating that slower speeds and feeds, combined with increased depth of cut, enhance abrasive grit penetration and produce superior surface finishes. The damping coefficient, reflective of wheel strength and longevity, follows the MRR trend, with the 7% CNT-CBN wheel displaying the highest value. SEM and AFM images confirm improved surface finishes and reduced grinding burns. This study presents a novel strategy for studying the MRR and Ra while grinding titanium alloy with CNT-infused grinding wheels, offering valuable insights for the field.
Stephen, Deborah SerenadeSethuramalingam, Prabhu
Tank Technologies, a company producing porcelain-lined water heaters, faced significant challenges with their manual cutting processes. Challenges in the cutting process are detrimental in an industrial landscape where speed requirements and cost pressures are high. The introduction of Hirebotics’ Cobot Cutter significantly improved their operations, drastically reducing rework, improving cycle times, and elevating overall efficiency.
This specification, in conjunction with the general requirements for peening media covered in AMS2431, establishes the requirements for the procurement of conditioned carbon steel cut wire shot with a hardness of 55 to 62 HRC.
AMS B Finishes Processes and Fluids Committee
This specification, in conjunction with the general requirements for peening media covered in AMS2431, establishes the requirements for the procurement of conditioned carbon steel cut wire shot with a hardness of 45 to 52 HRC.
AMS B Finishes Processes and Fluids Committee
This specification, in conjunction with the general requirements for peening media covered in AMS2431, establishes the requirements for the procurement of conditioned stainless steel cut wire shot.
AMS B Finishes Processes and Fluids Committee
Selective Laser Melting (SLM) has gained widespread usage in aviation, aerospace, and die manufacturing due to its exceptional capacity for producing intricate metal components of highly complex geometries. Nevertheless, the instability inherent in the SLM process frequently results in irregularities in the quality of the fabricated components. As a result, this hinders the continuous progress and broader acceptance of SLM technology. Addressing these challenges, in-process quality control strategies during SLM operations have emerged as effective remedies for mitigating the quality inconsistencies found in the final components. This study focuses on utilizing optical emission spectroscopy and IR thermography to continuously monitor and analyze the SLM process within the powder bed, intending to strengthen process control and minimize defects. Optical emission spectroscopy is employed to study the real-time interactions between the laser and powder bed, melt pool dynamics, material behavior, and energy deposition. In parallel, IR thermography provides temperature gradient mapping and thermal insights during SLM, facilitating the detection of potential thermal irregularities. By employing these diagnostic methods, deviations from anticipated process behavior are identified and classified, which can be employed in multi-physics models as input for studying defects and deformation. Real-time data acquisition enables swift detection of anomalies like powder segregation, uneven layer melting, and potential thermal concerns. The insights derived from optical emission spectroscopy and IR thermography are processed and analyzed. This study provides comprehensive process insights through optical spectroscopy and IR thermography. These advanced diagnostics not only elevate the overall quality of manufactured components but also cut down on post-processing and material wastage, rendering additive manufacturing more efficient and dependable.
Raju, BenjaminKancherla, Kishore BabuB S, DakshayiniRoy Mahapatra, Debiprosad
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