Spindle Speed Research Articles

Investigating the Impact of Robotic Milling Parameters on the Surface Roughness of Al-Alloy Fabricated by Wire Arc Additive Manufacturing

This paper takes the single-wall wall manufactured by wire arc additive manufacturing (WAAM) as the research object and compares it with the as-cast aluminum alloy with the same series. By using feed rate, cutting depth, spindle speed, etc., as single or compound parameters, the machinability of the sample is analyzed. The results indicate that the influence of varying parameters on the as-deposited aluminum alloy follows the order of feed rate > cutting depth > spindle speed. As the feed rate increases, the surface roughness initially decreases and then increases, with the optimal surface quality achieved at 12 mm/s (with a surface roughness of 2.013 μm). Different from the as-deposited alloy, the influence of the parameters on the as-cast alloys follows the order of spindle speed > cutting depth > feed rate. The experiments reveal that, for both as-deposited and as-cast states, the trends of the impact of cutting depth and spindle speed on surface quality are consistent. However, at low feed rates (2–12 mm/s), for as-deposited states, the surface quality of as-deposited samples becomes smoother as the feed rate increases (contrary to common knowledge). This result can be attributed to the elevated milling temperature, which softens the material, making it easier to remove and reducing the surface roughness.

Enhancing Drilling Performance in Natural Fiber-Reinforced Biocomposites Using Taguchi Method for Sustainable Manufacturing

The current research work focuses on optimizing drilling parameters for Sesbania rostrata fiber-reinforced polycaprolactone (PCL) biocomposites using the Taguchi method and ANOVA to improve hole quality, particularly to minimize delamination. The Taguchi L9 orthogonal array was employed with three factors: spindle speed (300, 750, and 1800 rpm), feed rate (0.05, 0.12, and 0.25 mm/rev), and drill size (4, 8, and 10 mm). The experimental results showed that drill size had the most significant effect on thrust force, with a contribution rate of 99.29%, whereas spindle speed primarily influenced delamination, contributing 67.65%. Optimal parameters were determined to be a spindle speed of 300 rpm, a feed rate of 0.25 mm/rev, and a drill size of 10 mm. These findings are significant for industries using biocomposites, offering sustainable solutions with enhanced machining performance.

Study on Self-Learning System for Milling Chatter Feature Based on Hybrid Preprocessing Model and Improved Convolutional Clustering

Milling chatter is a self-excited vibration phenomenon during the cutting process, typically occurring in machining operations with lower stiffness. It significantly impacts the machining precision and surface morphology of the workpiece. To summarize the vibration signal features under operating conditions and enhance the precision of the intelligent recognition model for milling chatter features, this paper proposes an adaptive learning model for chatter feature recognition based on the improved convolutional clustering algorithm. This study uses wavelet analysis to extract chatter features and improved convolutional clustering to identify chatter and stable cutting signals. This method selected appropriate mapping techniques based on differences in chatter signals under various conditions and uses convolution for feature extraction. Improve convolutional clustering evaluates sample similarity through energy transfer, less influenced by signal space structure compared to Euclidean or Mahalanobis distances. This method provides a unified criterion for evaluating different signal feature representation spaces, thereby improving the accuracy and efficiency of chatter sample recognition. The recognition accuracy of chatter phenomena at different spindle speed ranges reaches $95$ % and $96.3$ % respectively. The results show that this method can effectively distinguish between chatter signals and stable cutting signals.

EXPERIMENTAL INVESTIGATION ON FREE VIBRATIONAL DAMPING AND DRILLING BEHAVIOR OF FLAX REINFORCED EPOXY COMPOSITES USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM

Flax reinforced epoxy (F-Ep) composites were prepared by the compression moulding technique, varying the fiber content (0, 25, 35 and 45 wt%). The free vibration test was performed on the neat epoxy and F-Ep composites to understand their dynamic characteristics, and results showed that natural frequency and damping factor of the F-Ep composites increased with an increase in the fiber content. The F-Ep composite (45F-Ep) that exhibited better damping was selected for performing the drilling operation. Factors such as spindle speed (rpm), feed rate (mm/min) and drill point angle (degree) were chosen as input parameters and the tabulated set of experiments were in accordance with Taguchi’s design of experiment. The response measured was thrust force and the obtained values were found in the range of 19.66 to 50.75 N. The minimum value of thrust force was achieved when the F-Ep composite was drilled at high spindle speed (3000 rpm), with a feed rate of 75 mm/min using the drill point angle of 118°. ANOVA analysis showed that the developed regression model was significant and thrust force was mainly influenced by the spindle speed. Mathematical models were developed for drilling F-Ep composite using response surface methodology (RSM) and adaptive neuro fuzzy inference system (ANFIS) and compared for their efficacy.

Design and optimization of volute directing plate and stubble board for enhancing liquidity and anticlogging of tillering straw in spreading operation

In this paper, a novel volute linear directing plate and inverted “Y” structure stubble board are first designed to address the problem of straw agglomeration. Then a flexible and breakable discrete element model of tillering straw is proposed, and a discrete element coupling model of flexible tillering straw-crushing and strip-laying device is also constructed. The results show that the model can predict the operation performance of the crushing and strip-laying more accurately. Finally, the effect of spindle speed, directing plate radius and stubble board angle are investigated in-depth. In addition, the structure optimization of the directing plate and stubble board is conducted by response surface method, and the corresponding field test is also conducted. It is demonstrated that the coefficient of seed zone cleaning increased by 4.6 %, and the coefficient of straw ridge disturbance decreased by 34.6 %, meanwhile, the device performance is greatly improved after optimization.

Experimental Study on Dry Milling of Stir-Casted and Heat-Treated Mg-Gd-Y-Er Alloy Using TOPSIS

This study examines the dry milling process of a rare-earth-based magnesium alloy, emphasizing the optimization of the milling parameters and their impact on the surface quality, cutting forces, and the rate of material removal. The objective is to improve our comprehension of the milling behavior of the Mg-Gd-Y-Er alloy. The Taguchi technique is adopted to formulate the experimental design. This study methodically investigates the influence of heat treatment (T4 and T6) on milling performance, and the effects of speed, feed rate, and depth of cut. The output variables considered for this investigation are the surface roughness (Ra, Rz, Sa, and Sz), material removal rate (MRR), and cutting force. To optimize the milling parameters and achieve superior outcomes, the multi-objective optimization technique TOPSIS is used. At a feed rate of 150 mm/min, a spindle speed of 1500 rpm, and a depth of cut of 1 mm, the T4-treated sample exhibits a minimum surface roughness value of 0.0305 µm. The highest resultant force values of 96.4416 N and 176.1070 N for 200 °C and 225 °C T6-treated alloys are obtained by combining process parameters such as a spindle speed of 1500 rpm, a feed rate of 50 mm/min, and a depth of cut of 1.5 mm. Furthermore, the maximum closeness coefficient value is achieved by combining a spindle speed of 1000 to 1500 rpm, a feed rate of 150 mm/min, and a depth of cut of 0.5 mm to 1 mm. The closeness coefficient value is significantly influenced by the most significant process parameters, as indicated by the ANOVA results.

Investigation on two-dimensional ultrasonic vibration plane turning method based on elliptical plane swinging strategy along short axis

In the ultrasonic elliptical vibration cutting (UEVC) process, the surface morphology suffers from the large fluctuation of ridge height and residual height, which has restricted the development of UEVC technology. Therefore, on the basis of the elliptical plane swinging strategy along a short axis, a surface topography improvement method (i.e., swing ultrasonic elliptical vibration turning (SUEVT)) for two-dimensional ultrasonic vibration plane turning is proposed in this study. The core idea of the method is to swing the ultrasonic elliptical vibration plane along the short axis to form a machining inclination angle, which reduces the ridge height of the machined morphology to a certain extent, thereby optimizing the surface microstructure and reducing the surface roughness. First, this study establishes a mathematical model of the tool tip trajectory of ultrasonic elliptical vibration under different swing angles, theoretically analyzes the influence of swing angles on the tool tip trajectory and surface topography, and provides a theoretical basis for revealing the surface topography formation mechanism of SUEVT. Second, an engineering practice scheme of SUEVT is proposed, and a processing experiment platform is built. Finally, cutting experiments of SUEVT for TC4 titanium alloy were conducted, studying the influence of swing angles on surface topography and roughness and assessing the feasibility of the method. Results showed that compared with ultrasonic elliptical vibration turning (UEVT), SUEVT has certain advantages in improving surface morphology. When the swing angle of SUEVT is 15°, the surface roughness decreases the most, reaching 19.00 %. Under the condition of SUEVT θ = 15°, the surface roughness decreases first and then increases with the increase in spindle speed, while it is proportional to the feed speed and ultrasonic power. The method proposed in this study can provide new methods and new ideas for ultrasonic elliptical vibration high surface quality machining.

Imitating pangolin scale structure for reducing adhesion and resistance of rotary tillage in wet-adhesive soil

The bionic design of soil-engaging components has recently received much attention in conservation tillage and is extremely important for reducing tillage resistance and increasing implement passability in wet-adhesive rice paddy soil. In this paper, to reduce adhesion and resistance of rotary tillage in wet-adhesive soil, a novel imitating pangolin scale structure is first proposed, and the bionic non-smooth surface parameters affecting the soil adhesion effect is clarified. Afterwards, based on the JKR attached Bonding contact model, an accurate discrete element interaction model of the designed rotary tillage blade -wet adhesive soil is established, and the effect of spindle speed, bump size and bump distance on the tillage resistance and soil disturbance is analyzed using the proposed model. Finally, the proposed imitating pangolin scale structure is optimized to improve the anti-adhesive and drag reduction properties using response surface method, furthermore, the corresponding model validation experiments and field tests are also conducted. Results reveal that the relative errors between the simulated and experimental values of the bionic blade rotary torque and soil adhesion mass are only respectively 4.4 % and 8.3 %. In addition, the optimal parameter combinations of anti-adhesion and drag reduction are also determined: the spindle speed is 180 rpm, the bump width is 10.6 mm and the bump distance is 17.9 mm, respectively, at the time, the effect of soil breaking of the designed blade is reduced by 9.95 % compared to that of the traditional blades but the effect of anti-adhesion and drag reduction is improved by 18.81 %.

Multi response optimization of process parameters in titanium alloy minimum quantity lubrication drilling operation

Abstract This work investigates the application of minimal quantity lubrication (MQL) in the drilling process, where a combination of liquid and air creates an aerosol in the form of a fine mist. This protective layer decreases friction and tool wear, hence improving overall efficiency. The study examines the conventional Gulfcut oil blend drilling technique to enhance drilling performance on the titanium alloy Ti-6Al-4V under MQL circumstances. The key drilling parameters, namely spindle speed (N), feed rate (F), and point angle (D), were analyzed using a Taguchi L16 orthogonal array. The experimental inquiry aimed to identify the most favorable conditions that lead to the least amount of torque (TQ), thrust force (TF), and surface roughness (SR). An Analysis of Variance (ANOVA) was used to examine the impact of control factors on drilling performance. The optimized drilling parameters led to a reduction in torque, thrust force, and surface roughness by 12.88%, 21.29%, and 25.76%, respectively. Furthermore, microstructure analysis demonstrated that the Gulfcut lubricant plays a pivotal role in reducing grain size during drilling. This research provides valuable insights into optimizing drilling conditions for titanium alloy using a conventional Gulfcut oil blend with MQL, aiming to reduce torque, thrust force, and surface roughness.

Thermal Evaluation of Bone Drilling: Assessing Drill Bits and Sequential Drilling.

Sequential drilling is a common practice in dental implant surgery aimed at minimizing thermal damage to bone. This study evaluates the thermal effects of sequential drilling and assesses modifications to drilling protocols to manage heat generation. We utilized a custom drill press and artificial bone models to test five drill bits under various protocols, including sequential drilling with different loads, spindle speeds, and peck drilling. Infrared thermography recorded temperature changes during the drilling process, with temperatures monitored at various depths around the osteotomy. The results reveal sequential drilling does not eliminate the thermal damage zone it creates (well over 70 °C). It creates harmful heat to surrounding bone that can spread up to 10 mm from the osteotomy. The first drill used in sequential drilling produces the highest temperatures (over 100 °C), and subsequent drill bits cannot remove the thermal trauma incurred; rather, they add to it. Modifying drill bit design and employing proper drilling techniques, such as reducing drilling RPM and load, can reduce thermal trauma by reducing friction. Inadequate management of heat can lead to prolonged recovery, increased patient discomfort, and potential long-term complications such as impaired bone-to-implant integration and chronic conditions like peri-implantitis. Ensuring healthy bone conditions is critical for successful implant outcomes.

A framework toward fatigue life modeling of machining process verified in burnishing

In the present work a multiscale model was developed to predict fatigue lives of Inconel 718 after a machining process. The model captures the effects of surface integrity like residual stress, microstructure, hardness and roughness. Within this holistic predictive model, firstly burnishing process factors (viz static force, feed rate, spindle speed and pass number) are correlated to surface integrity aspects. Herein, residual stress is modeled using theory of incremental plasticity; also grain size and hardness were correlated to process factors through dislocation density evolution. In order to model the surface roughness, the Z-map approach considering the work hardening of the surface layers was utilized. The foresaid developed models of surface integrity aspects were utilized to predict the fatigue life using Navaro-Rios crack propagation together with Chen’s crack initiation models. Thus, a novel holistic model correlating machining parameters directly to fatigue life has been developed through this hybrid approach. The developed models of fatigue life and surface integrity aspects were then confirmed by series of burnishing experiments on Inconel 718. Later, the confirmed model was utilized to identify the parametric influence of burnishing process on variation of fatigue life where the results were justified using variation of surface integrity factors. Through this developed model, it was found that burnishing setting of 1000 N static force, 0.05 mm/rev feed rate, 300RPM spindle speed and 2 pass number results in improvement of HCF, MCF and LCF of 242 %, 184 % and 212 % where the obtained results from the developed framework were compatible well with experimental values.

Parameter identification of Johnson–Cook constitutive model based on genetic algorithm and simulation analysis for 304 stainless steel

Addressing the significant discrepancy between actual experimental cutting force and its predicted values derived from traditional constitutive model parameter identification methods, a reverse identification research of the Johnson–Cook (J-C) constitutive model for 304 stainless steel was conducted via genetic algorithm. Considering actual cutting zone and the influence of feed motion on the rake (flank) angle, an unequal division shear zone model was established to implement the theoretical calculation for shear zone stress. Through cutting experiments, the spindle speed was negatively correlated with the cutting force at first, and then became positively correlated; The empirical formula (EXP model) for turning force was corrected, revealing that the EXP model was unable to provide optimal predicted values for cutting force. The influence of the J-C constitutive parameter C on the cutting morphology was firstly investigated through simulation analysis, and determined an appropriate value for C, then obtained the precise values for the other four constitutive parameters by genetic algorithm. Moreover, the simulated values of cutting force in JC1 model (obtained from the Split Hopkinson Pressure Bar test) and JCM model (the improved model using genetic algorithm) were obtained by three-dimensional (3-D) simulation via FEM software. The results indicated that, the maximum error between actual experimental cutting force and its simulated values (by JCM model) was 14.8%, with an average error of 6.38%. These results outperformed the JC1 and EXP models, suggesting that the JCM model identified via genetic algorithm was more reliable.

Online vibration monitoring using laser vibrometer and acoustic emission techniques in robotic milling CFRP composites

Carbon fiber reinforced polymer (CFRP) material has superior mechanical properties, often utilized in the aerospace industry. However, its prone to surface defects such as burrs and delamination under the influence of machining vibration, thereby compromising component quality. This study evaluated the relevant vibration signal features via signal processing methods, and investigated the effect of machining parameters on machining stability during robotic milling of CFRP composite. Specifically, the study assessed machining status by analyzing milling signals and compared surface quality between vibration and stable machining stages, the former corresponds to a larger Sa on the machined surface, with more pronounced profile fluctuations. Machining vibration manifests distinct characteristics in laser vibrometer signals, exhibiting in time-frequency plots with short-term signal enhancements at multiple frequencies. This phenomenon occurs more frequently during entry and exit stages. The results indicated that feed speed has a limited effect on milling stability within the selected parameter range, and severe machining vibration occurred at lower spindle speed (12,000 rpm) and higher milling depth (2 mm). Corresponding surface defects formation mechanisms were discussed, revealing that the formation of uncut burrs at the top was related to axial milling force, while interlayer debonding cracks stemmed from variations in fiber orientation between adjacent layers.

Relationship between Cutting Depth and Spindle Speed on Cutting Accuracy of Aluminum 6061 on the TU-3A Retrofit CNC Machine

In the Mechanical Engineering Laboratory of the State Polytechnic of Malang, CNC machines experience decreased performance caused by abrasion and wear on mechanical components such as spindles, bearings, and rails, as well as electronic damage, outdated hardware and software, and inadequate maintenance. This study aims to evaluate the effect of cutting parameters on the roundness of machining results. The results of data analysis show that the depth of cut has a significant effect on roundness, with an F value of 8.05 and a P value of 0.030, which means significant at the 0.05 level. In contrast, spindle speed does not have a significant impact on roundness, with a P value far above 0.05. In addition, the interaction between depth of cut and spindle speed does not show a significant effect on roundness, with an F value of 2.08 and a P value of 0.206.

Characterization of ultrasonic vibration and polishing force in sapphire ultrasonic vibration-assisted flexible polishing: Insights from in-situ monitoring systems

Sapphire ultrasonic vibration-assisted flexible polishing (UVAFP) is a promising technique for comprehensively improving the surface integrity of machined parts. The technique was performed on an ultra-precision machine tool with the in-situ monitoring systems in this paper, which aims to provide a new perspective for understanding the material removal mechanisms in the sapphire UVAFP process. A Taguchi L9 (43) orthogonal experiment was conducted to investigate the effects of feed distance, spindle speed, ultrasonic vibration (UV), and polishing time on the surface finish and material removal in the process. In addition, the effect of a polyurethane ball tool is not trivial. A single-factor experiment was conducted for exploring it. Based on a laser displacement measurement system and an acoustic emission sensor system, the characteristics of time-dependent ultrasonic amplitude and ultrasonic frequency for the sapphire UVAFP system were analyzed, with the effectiveness of UV demonstrated. Based on a three-component force measurement system, the characteristics of normal force and its relationship with process parameters and tool deformation were analyzed, with macro- and micro-level examined. In conclusion, this paper presents the characterization of UV and polishing force in the sapphire UVAFP process, providing novel insights into understanding the material removal mechanisms of sapphire and even more manufacturing problems.

Influence of HSS drill coatings on surface finish and cylindricity of AA6061/C/ZrO2 composite in CNC drilling operations under dry conditions

Abstract This study aims to evaluate the effect of HSS drill tool coatings, namely single-layer TiN, single-layer AlCrN, and double-layer AlTiN + TiSiXN (Durana), on the surface roughness and cylindricity of AA6061 (90 wt%)/C (5 wt%)/ZrO2 (5 wt%) hybrid composite material processed by the stir casting method. The fabricated sample was examined for the uniform particle distribution of reinforcements using Scanning Electron Microscope. The drilling operation was carried out on the fabricated in a CNC machining center by setting the spindle speeds of 800, 1200, and 1600 rpm, depths of cut of 0.5, 1, and 1.5 mm, and feeds of 50, 100, and 150 mm/rev. An orthogonal array (L27) designed by Taguchi’s method was used as the design of the experiment for the optimization of the best cutting parameters and coating. Surface roughness and cylindricity errors were determined for the 27 experimental runs. Field emission scanning electron microscopic (FESEM) examination and Energy Dispersive Spectroscopy (EDS) were used to analyze the surface integrity and elemental composition, respectively. The results revealed that Durana had a significant effect on the surface substrate with minimum surface roughness (Ra) of 1.666 μm and obtained the minimum cylindricity error for the parameters of depth of cut 0.5 mm, spindle speed of 1200 and feed of 100 mm rev−1.

Optimizing the drilling process parameters of AZ91 based hybrid composites using TOPSIS and grey relational analysis

AZ91 is a popular magnesium alloy that contains aluminum (Al), zinc (Zn), and small amounts of other elements that offers a good balance of mechanical properties and corrosion resistance, making it suitable for various applications such as automotive, aerospace, sports, and biomedical. The current research works focused on optimizing drilling process parameters such as cutting speed, feed rate, a set of standard tools, and biofriendly coolants against the surface roughness and axial thrust force for AZ91/ nano hBN/ micron TiB2 hybrid composites. Taguchi L18 orthogonal array was used to design the drilling experiments. The axial thrust force and surface roughness of the drilled hole were observed as response of the experiments. Based on the results from TOPSIS and GRA, the optimal conditions were determined to be a spindle speed of 65 m/min, feed rate of 1 mm/rev, using a High-Speed Steel (HSS) tool, and Liquid Nitrogen (LN) coolant for 1 wt% of nano hBN in the hybrid composite. These parameters resulted in the lowest axial thrust force and surface roughness, highlighting their effectiveness in optimizing the drilling performance of AZ91/TiB2/hBN composites.

Exploratory data analysis & EDS analysis on tool chip adhesion under dry and nano minimum quantity lubrication machining environment

Adhesion, abrasion, plowing and transverse displacement are the major causes of origin of friction. During dry machining of ductile materials, chips are fused with the rake face of the cutting tool and contribute to the formation of the built up edge. Built up edge protects the rake face of the tool from wear, but makes the machined surface rough. To improve the tribological properties and to decrease the tool-chip adhesion, cutting fluids are used. Cutting fluids are added to the machining zone to minimise cutting temperature and friction, but they result in environmental and health degradation. Surface texturing of tools is a potential way to modify the tribological properties of mating surfaces in order to increase the tribological qualities and decrease the tool-chip adhesion. The performance of surface textured tools depends upon orientation, dimple depth, width and pattern. Under lubrication regime, microholes in surface textured tools acts both as lubrication reservoir and traps wear debris to reduce abrasive wear. Nano Minimum Quantity Lubrication (nano-MQL) is an advanced lubrication technique used in machining processes, specifically designed to minimize the use of lubricants while maintaining effective lubrication. This method involves delivering an extremely small amount of high-performance lubricant directly to the cutting zone. The MoS2 lubricant with sunflower oil is typically in the form of nanodroplets, which are much smaller than conventional minimum quantity lubrication (MQL) droplets. The Exploratory Data Analysis (EDA) methodology enables the identification of patterns, trends, and outliers within the collected data, offering insights into the complex interplay of factors affecting the machining of Aluminium Alloy AA2024. At a spindle speed of 3500 rpm the feed force decreases by 37% under dry environment when compared with nano-MQL environment. Under dry environment average surface roughness reduces by 27% when compared with nano-MQL environment.

Effect of machining parameters on average surface roughness during computer numerical controlled dry milling of high strength AISI 420 martensitic stainless steel

This study focuses on developing an empirical model for average surface roughness during computer numerical controlled (CNC) dry milling of AISI 420 martensitic stainless steel, utilizing response surface methodology (RSM). Experiments were designed with three levels of axial depth of cut, feed rate, and spindle speed to quantify their impact on surface roughness. The RSM-Box-Behnken design was employed to construct the empirical model. Model adequacy was validated through residual analysis and analysis of variance (ANOVA). Analysis of the main effects and interaction effects revealed that the primary influences on average surface roughness were the feed rate, spindle speed, and axial depth of cut, while interaction effects were less significant. Optimal cutting conditions were determined to be a spindle speed of 1500 rpm, a feed rate of 30 mm min−1, and an axial depth of cut of 0.3 mm. The model’s validity was further confirmed through additional validation tests.

The Effect of Depth of Cut and Spindle Speed on Cutting Parallelism Results on Aluminum 6061 CNC TU-3A Retrofit Machine

Machining process is an important part of manufacturing to form and finish high-precision components. Milling is a commonly used technique, and the advancement of CNC technology has enabled precise and consistent production. This study evaluated the effect of spindle speed and depth of cut on the surface parallelism (µm) of aluminum 6061 using a TU-3A retrofit CNC milling machine. A quantitative experimental method with factorial design of experiments (DOE) was applied, testing spindle speeds of 600 RPM, 800 RPM, and 1000 RPM and depths of cut of 1.0 mm, 1.5 mm, and 2.0 mm, while maintaining constant feed rates of 48 mm/min, 64 mm/min, and 80 mm/min. The results showed that spindle speed had no significant impact on surface parallelism (µm) (P-value = 0.924), although higher speeds showed a trend of better results. In contrast, depth of cut significantly affects parallelism (µm) (P-value = 0.000), with greater depth improving surface quality (µm). In addition, the interaction between spindle speed and depth of cut is also significant (P-value = 0.002), indicating that the combination of higher spindle speed with lower depth of cut produces better results. These findings suggest optimal machining parameters to improve surface parallelism (µm) in aluminum milling operations.