Feed Rate Research Articles

Optimizing dynamic measurement accuracy for machine tools and industrial robots with unscented Kalman filter and particle swarm optimization methods

The telescoping ballbar is widely utilized for diagnosing accuracy and identifying faults in machine tools and industrial robots. Currently, there are no established standards for determining the optimal feed rate for ballbar tests. This lack of clear guidelines results in time inefficiency in measurements and inconsistencies in dynamic measurements, which complicates the comparison of ballbar test results under various conditions or across different machine platforms. To mitigate dynamic variations in ballbar results, an updated ballbar data processing method that integrates the unscented Kalman filter (UKF) and particle swarm optimization (PSO) was developed and validated using real ballbar data measured at multiple feed rates and simulated data with varying vibration magnitudes generated through the Renishaw ballbar simulator. Experimental results revealed that the dynamic components extracted from the ballbar results were observed to increase in correlation with the vibration measured at different feed rates and from the simulations. Moreover, the variations in the results measured at different feed rates after PSO-UKF processing were significantly reduced. The findings confirm the effectiveness of the proposed method in minimizing the dynamics of the ballbar results. Ultimately, this approach enhances the efficiency and accuracy of ballbar testing and offers a general method for improved diagnostics.

Experimental study on the effect of filament-extrusion rate on the structural, mechanical and thermal properties of material extrusion 3D-printed polylactic acid (PLA) products

AbstractMaterial extrusion (MEX), also commonly referred to as fused deposition modeling (FDM) or fused filament fabrication (FFF) is currently one of the most commonly used additive manufacturing techniques. The quality of the 3D-printed objects fabricated by MEX methods highly relies on various printing parameters, one of which is the so-called filament extrusion multiplier (k). In this study, 3D-printed parts were prepared by MEX technique during which the material feeding rate was adjusted by varying the extrusion multiplier in the range of 97–105% (k = 0.97–1.05). The fabricated parts were tested for their geometrical, structural, mechanical, and thermal conductivity properties. Based on computed tomographic analysis and scanning electron microscopic images, increasing the k parameter resulted in smaller voids, along with gradually decreasing porosity (from 5.82 to 0.05%). Parallel to the decreasing defects, the thermal conductivity of the parts improved from 0.157 to 0.188 W/mK as determined by light-flash analysis technique. On the other hand, when k was set to ≥ 1.03 the geometrical accuracy declined, the size of the specimens considerably increased relative to the nominal values, especially in the X–Y directions due to excess material getting “squeezed” on the sides of the specimens. This latter phenomenon also resulted in the formation of a number of stress concentration sites, which manifested in the decrease of mechanical properties. Accordingly, the tensile, flexural, and impact strength of the samples improved up to k = 1.03; however, above that it dropped considerably.

Intelligent in-process enhancement technique for machining efficiency in CNC machine tools based on spindle power

In the realm of mechanical machining, adaptive machining techniques offer an efficient method. However, existing adaptive machining technologies cannot automatically identify the type of workpiece to be machined, nor can they set different control targets based on tool load-bearing capacity. This often requires manual and cumbersome operations, making the application of adaptive machining technology difficult to popularize. To address these challenges, this paper proposes an intelligent and efficient adaptive machining method. Specifically, a workpiece automatic classification algorithm based on machine tool spindle power is introduced. This algorithm classifies the machined workpieces according to the collected spindle power data, enhancing the convenience of adaptive machining technology. Also based on spindle power data, a time-series segmentation method is proposed, dividing spindle power into different subsequences according to the tools used in machining, which enhances the accuracy of adaptive machining technology. Furthermore, an adaptive feed rate control algorithm is designed based on fuzzy control theory, realizing intelligent and efficient adaptive machining of workpieces to improve machining efficiency. Finally, experiments are conducted to validate the effectiveness of the intelligent and efficient adaptive machining method. The proposed method effectively addresses the drawbacks of existing adaptive machining method, which require complex parameter settings. It simplifies the operational process, enhances the intelligence, and improves the practical applicability of adaptive machining techniques. This represents an innovative contribution to the field of adaptive machining techniques.

An Experimental Investigation of the Effects MQL Using Nanofluids on Surface Roughness of Hard Milling Process

High cutting force and cutting heat are challenging problems that need to be overcome for the hard milling process. Minimum quantity lubrication (MQL) has been shown to be effective and suitable for use in hard milling due to the improving lubrication in the cutting zone. The content presented in this article is to investigate MQL using emulsion cutting oil with/without Al2O3 nanoparticles for hard milling of 60Si2Mn steel (50-52 HRC) using carbide tools. Factorial experimental design is used to evaluate the cooling condition, cutting speed and feed rate on surface roughness. Experimental results show that feed rate has the greatest influence on surface roughness among the parameters investigated, followed by cooling mode and cutting speed. MQL technique using nano cutting oil gives better machined surface quality than MQL using pure cutting oil, which has proven that the additives of Al2O3 nanoparticles to the base cutting oil has improved cooling and lubrication capability. Furthermore, the applicability of MQL method is expanded to apply for hard milling.

Investigation of Machining Parameters for Turning Process

Manufacturing industries mainly concentrates on how to minimize the cost of the products. The process planers have to prepare the process plan of the product based on the availability of the recourses. All the information is available in the plan including inspection and delivery date of the product. Based on the recommendation of the manufacturing and inspection methods, components are produced at affordable cost. Most of the research work concentrated on selection of machining parameters using optimization techniques and also prove that the machining time / cost were minimized for the particular components / operations. In this work, tool nomenclature is to be considered for the investigation for selection of machining parameters. Work presents an experimental investigation of the influence of the three most important machining parameters of depth of cut, feed rate and spindle speed on surface roughness during turning of aluminium alloy. In this study, the design of experiment which is a powerful tool for experimental design is used to optimize the machining parameters for effective machining of the work piece. L9 orthogonal array experimental design method as well as analysis of variance (ANOVA) is used to analyse the influence of machining parameters on MRR & Machining Time. Two different grade of aluminium alloy i.e. AL 6063 & AL 6068 were machined with input parameters of depth of cut and speed. The output parameters are MRR and machining time. Based on the results empirical equations are formed and optimized results are validation .The optimal results are recommended to manufacturing industries.

Development of spray‐dried oat milk powder with improved stability

AbstractBackground and ObjectivesOat milk is a plant‐based milk alternative and rich in various nutrients, however, the liquid product with a shorter shelf life limits its sales and consumption. This study is designed to develop an oat milk powder (OMP) using spray drying and improve the stability of reconstituted OMP by adding stabilizers.FindingsResults revealed that the optimal spray drying temperature was 160°C and the feed rate was 14 mL/min. The developed OMP showed higher bulk density compared to commercial soymilk powder. Furthermore, OMP maintained high contents of nutrients, including total phenol, β‐glucan, and various essential amino acids. The addition of stabilizers in OMP significantly decreased the turbidity and increased the pH stability, thermal stability, and freeze‐thaw stability of reconstituted OMP.ConclusionThe developed OMP product has abundant nutrients as well as stable physiochemical properties. Xanthan gum is the most effective stabilizer in improving the stability of reconstituted OMP across a wide range of pH and temperature.Significance and NoveltyThis study was the first to process oat milk into powder products and compare the effectiveness of different stabilizers in improving its stability. Our results suggest that OMP is a promising plant‐based beverage with stable physiochemical properties.

Uptake from water and depuration of 137Cs and 90Sr by silver Prussian carp (Carassius gibelio)

To follow up field observations in the Chornobyl Exclusion Zone (ChEZ), a series of controlled model aquarium experiments were conducted to determine the uptake and depuration rates of 137Cs and 90Sr in silver Prussian carp (Carassius gibelio) in fresh water, varying in temperature from 5 to 27 °C, with daily feeding rates of 0–1.5 % fish weight day−1.In the present study, the 137Cs uptake rates in muscle tissues directly from water, 0.05–0.09 day−1 at temperatures of 5–27 °C, were significantly lower than previously reported for fish fed under natural conditions in contaminated lakes within the ChEZ. The rate of 90Sr uptake in bone tissues of silver Prussian carp varied from 0.055 day−1 at a water temperature of 5 °C and feeding rates ≤0.15 % fish weight day−1 to 1.5 ± 0.2 day−1 at a temperature of 27 ± 1 °С and at the highest tested feeding rate of 1.5 % day−1.The rate of decrease of 137Cs concentration in muscle tissues was kb = 0.0028 ± 0.0004 day−1 (T1/2 = 248 ± 35 days) at the lowest water temperature tested (5 °С). At water temperatures between 13 and 26 °С and a feeding rate of 0.15 % day−1, the rate increased to kb = 0.0071–0.0092 day−1 (T1/2 = 75–99 days).The rates of decrease of 90Sr activity concentration in bone tissues at water temperatures between 22 and 25 °С and a feeding rate of 0.5 % day−1 were kb=0.004–0.0014 day−1, and the associated biological half-life T1/2 ranged 50–160 days, respectively. The present work supported conclusions related to the main pathways of 137Cs and 90Sr uptake by silver Prussian carp, and demonstrated the usefulness of combining field and laboratory uptake and depuration experiments.

On Performance Enhancement of the STED Process Using Modified Tool Electrode

Abstract Shaped tube electrolytic drilling (STED) is an electrochemical machining variant that employs a tubular tool electrode to produce holes with a high aspect ratio on hard-to-machine materials. The tubular electrodes with a diameter below 1 mm produce undesired residue (center-peak) at the machining surface that hampers the machining rate. Therefore, this study attempts to improve the electrolyte flow and enhance the electrochemical dissolution through tool modification. The performance enhancement of the STED process in terms of material removal rate and average diametral overcut has been explored. The issues related to the limitations in material removal in the STED process are brought forth with the technique to resolve those difficulties. The experiments were conducted with the modified tubular tool, and the length of slits on the tool was selected based on the simulation insights and pilot study. The effects of input process parameters (applied voltage, tool feed rate, electrolyte concentration, and tool slit length) on the output responses obtained from the STED process are elaborated. Holes with diameters in the range 0.89-0.97 mm and 12 mm depth were fabricated. Further optimization of the process parameters in the design space is also presented to obtain sustainable process performance.

Protein complexes from edible mushrooms as a sustainable potato protection against coleopteran pests.

Protein complexes from edible oyster mushrooms (Pleurotus sp.) composed of pleurotolysin A2 (PlyA2) and pleurotolysin B (PlyB) exert toxicity in feeding tests against Colorado potato beetle (CPB) larvae, acting through the interaction with insect-specific membrane sphingolipid. Here we present a new strategy for crop protection, based on in planta production of PlyA2/PlyB protein complexes, and we exemplify this strategy in construction of transgenic potato plants of cv Désirée. The transgenics in which PlyA2 was directed to the vacuole and PlyB to the endoplasmic reticulum are effectively protected from infestation by CPB larvae without impacting plant performance. These transgenic plants showed a pronounced effect on larval feeding rate, the larvae feeding on transgenic plants being on average five to six folds lighter than larvae feeding on controls. Further, only a fraction (11%-37%) of the larvae that fed on transgenic potato plants completed their life cycle and developed into adult beetles. Moreover, gene expression analysis of CPB larvae exposed to PlyA2/PlyB complexes revealed the response indicative of a general stress status of larvae and no evidence of possibility of developing resistance due to the functional inactivation of PlyA2/PlyB sphingolipid receptors.

The Experimental Investigation of the Machinability of Armor Steels

In recent years, the use of materials with ultra-high hardness such as Millux Protection 600T has become widespread in industry. However, the effect of different parameters used in the machining process of such steels, especially factors such as feed rate, cutting speed, depth of cut, and radial depth of cut, on the surface roughness of the final product is still not fully understood. In this context, a study was conducted to evaluate the effects of the mentioned armor steel on surface roughness. Using the Taguchi optimization method, the interaction between processing parameters at specified levels was examined, and attempts were made to determine the optimum values. Within the scope of the study, nine different experiments were conducted using Taguchi's L9 orthogonal array, and the surface roughness data obtained from each experiment were recorded. According to the analysis results, it was determined that the feed rate is the most significant parameter in the milling process, followed by radial depth of cut, depth of cut, and cutting speed, respectively. To achieve optimal results, it is recommended that the feed rate be set to level 1, cutting speed to level 2, depth of cut to level 1, and radial depth of cut to level 3. These findings could provide important guidance in the machining of such steels.

The effect of secondary cutting on the chip breaking in turning with (Ti,W)C cermet cutting tools

This study proposes a secondary cutting technique to address the chip breaking issue of cermet cutting tools. A cemented carbide blade is superimposed to cut off the chips while cutting with (Ti,W)C cermet tools, this approach allows for achieving chip breaking while maintaining excellent machining surface integrity. In this paper, the influence of the distance between the secondary cutting tool and the major cutting edge and the thickness of the tool on the chip breaking is studied, by using the combination of finite element simulation and experimental verification. The results indicate that the secondary cutting technique transforms the chips from long helical chips into dual-C-type chips. The distance between the secondary cutting tool and the major cutting edge is the primary factor affecting chip breaking. The reason is that the free end of the chip is subjected to the reaction force of the secondary cutting tool, which hinders the increase of the chip curl radius, increases the internal strain, and achieves the chip breaking condition. The thickness of the secondary cutting tool is also a significant factor influencing chip breaking, when the thickness reaches the critical value of 1.8 mm, the tool transitions from obstructive action to cutting action. When the cutting material is 45 steel, the cutting speed is 300 m/min, the feed rate is 0.142 mm/r, and the cutting depth is 0.2 mm, the distance between the secondary cutting tool and the major cutting edge is 1.5 mm, and the tool thickness is 1.3 mm, the chip breaking effect is the best, the main types of chips is dual-C type chips, with a chip length of 7.1 mm ± 0.3 mm and a chip fracture curl radius of 1.8 mm ± 0.1 mm. At this point, the surface roughness can be reduced to as low as 0.98 μm, good surface integrity is ensured while chip breaking.

Multi-Pass Laser Polishing of As-Built Directed Energy Deposition Surfaces

Abstract Laser polishing (LP) provides a fast and efficient way of remelting part surfaces manufactured by additive manufacturing to alter both their geometric as well as physical properties. Depending on the laser parameters, remelted surfaces with different properties are achieved, with a majority exhibiting lower surface roughness compared to the original surface. In this study, a high-power continuous fiber laser is used to polish Inconel 718 (IN718) surfaces produced by depositing a single layer of clads on a steel substrate by the powder-blown directed energy deposition (DED) process. Polishing was performed under different sets of parameters, namely, laser power, beam diameter, feed rate or feed, hatch spacing, and the number of polishing passes. Their effects on the surface roughness profiles and the microstructural properties of the sample cross section were analyzed after one and two polishing passes. Optical microscopic images of the sample's cross sections show the presence of supersaturated γ phase particles, γ′+γ″ precipitates, Laves phases, and δ phase needles. The combined effect of high-temperature gradients and lower solidification rates in certain regions within the cross section results in undercooled regions and pseudo-heat treatment of unmelted regions close to the undercooled regions. These results are corroborated by indenting the various regions of the IN718 sample cross section with a pyramidal diamond indenter in the form of a grid, resulting in different micro-hardness values due to different densities of precipitate and phase transformed δ particles.

An insight into the influence of precipitation phase on the surface quality in diamond turning of an Aluminium alloy

Diamond turning is an effective technology for processing metal mirrors used in photoelectric communications, radar, and other fields. In diamond turning, the precipitated phase is an essential factor that influences the surface quality of the metal mirrors. However, in previous studies, the precipitation phase has typically been handled as a random variable in a surface morphology model to evaluate its influence on the surface roughness, instead of determining the formation mechanism and proposing suppression solutions. In this study, a new phenomenon is observed in the diamond turning of metal mirrors, that is, the micro diamond tool can reduce the protrusion of the precipitated phase under a small feed rate and improve the surface quality. Investigating the turning process using diamond tools with varying tool nose radii at small feed rates (<1 μm/r), the underlying transformation mechanism of the precipitation phase is determined with the advanced material characterization technologies. The growth of the precipitated phase with an increase in the tool nose radius is explained using the energy gradient theory. The results showed that the increased material strain on the machined surface decreased the activation energy of solute diffusion in the material, causing solute accumulation and precipitate phase growth. With a further increase of tool nose radius to around 1000 μm, the β'' phase breaks and rotates. The representative volume element method shows that when undergoing severe plastic deformation, dislocations and grain boundaries quickly aggregate and slide on the precipitated phase, which will lead to the fracture and rotation of β'' phase. These findings provide a theoretical basis for the development of highly smooth mirrors.

Impact of Cutting Data on Cutting Forces, Surface Roughness, and Chip Type in Order to Improve the Tool Operation Reliability in Sintered Cobalt Turning

The authors present the results of laboratory tests analysing the impact of selected cutting data and tool geometry on surface quality, chip type and cutting forces in the process of orthogonal turning of sintered cobalt. The selected cutting data are cutting speed and feed rate. During the experiments, the cutting speed was varied in the range of vc = 50–200 m/min and the feed rate in the range of f = 0.077–0.173 mm/rev. In order to measure and acquire cutting force values, a measuring setup was assembled. It consisted of a Kistler 2825A-02 piezoelectric dynamometer with a single-position tool holder, a Kistler 5070 signal amplifier and a PC with DynoWare software (Version 2825A, Kistler Group, Winterthur, Switzerland)). The measured surface quality parameters were Ra and Rz. The components of the cutting forces obtained in the experiment varied depending on the feed rate and cutting speed. The obtained test results will make it possible to determine the optimal parameters for machining and tool geometry in order to reduce the machine operating time and increase the life of the cutting insert during the turning of sintered cobalt, which will contribute to sustainable technology.

Experimental Investigation and Optimization of Coaxiality Error Analysis with CNC Turning Process on Delrin for Assembly Fit

This paper mainly deals with the machining operation like turning operation, Material Removal Rate and Surface Roughness are the important parameter which is to be considered for quality product. The material selected for the experiment is DELRIN 500. Turning is one of the important processes that is widely used to create cylindrical components and it is also used for surface finish the product to make it smooth. Nowadays, plastic materials are widely used for making variety of components. To make a component with high dimensional accuracy, turning operation is used. The main concerns of turning are tooling cost and the effect of process on machinability characteristics. It can be seen that the output responses value has a minimum roughness average and a high degree of geometrical quality precision. High degree surface finish is induced by medium speed, feed rate, and small nose radius. The coaxial error was minimized by using medium speed, feed and larger nose radius. Experimentally found that third specimen (RPM -750) (FEED -0.08 mm/Rev) and (NOSE RADIUS 0.8) obtained minimum geometrical error along with minimum Surface roughness. Delrin is a crystalline plastic that offers an excellent balance of properties that bridge the gap between metals and plastics. Delrin possesses high tensile strength, creep resistance and toughness. It also exhibits low moisture absorption

A bottom-up multi-physics model correlating burnishing factors to fatigue life

Burnishing is type of contact based non-metal removal finishing processes that is used to enhance the service performance of hard material like Ti-6Al-4V through modification of roughness, exerting work hardened surface layer and inducing compressive residual stress. However, the design of process aiming at anti-fatigue machining is a big challenge, since on one hand the experimental trial and errors of fatigue tests are time consuming and costly, on the other hand there is lack of predictive models that directly correlate the process factors to lifetime. Therefore, to study the fatigue behavior of burnished samples, a holistic predictive framework is required. The present study takes lead to solve the problem by developing a model which correlates the surface integrity and fatigue life of the materials processed. Here firstly the roughness, microhardness and residual stress of the burnished samples are modeled and correlated to process factors through multiphysics of burnishing. Then they were correlated to fatigue life by using stress-based approach that includes surface geometrical, mechanical and metallurgical aspects. The accuracy of developed models were compared with the series of experiments which were carried out on as-turned Ti-6Al-4V. The results revealed that the developed analytical model can predict the lifetime of the burnished samples with acceptable accuracy where the average prediction error for 16 data sets is 13.6 % within the range of 6.3 % to 22 %. The verified model was then utilized to identify the mechanism of lifetime variation and to understand how the process factors determines the fatigue life. It was obtained that the static force as a parameter contributed to loading has greatest impact on variation of fatigue life by adjusting all the surface integrity aspects i.e. roughness, microhardness and residual stress. It was also found that the main impact of feed rate on fatigue life is attributed to its influence surface roughness at high static force.

Prediction and optimization kerf width in laser beam machining of titanium alloy using genetic algorithm tuned adaptive neuro-fuzzy inference system

AbstractIn the power diode laser beam machining (DLBM) process, the kerf width (KW) and surface roughness (SR) are important factors in evaluating the cutting quality of the machined specimens. Apart from determining the influence of process parameters on these factors, it is also very important to adopt multi-response optimization approaches for them, in order to achieve better processing of specimens, especially for hard-to-cut materials. In this investigation, adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm tuned ANFIS (GA-ANFIS) were used to predict the KW on a titanium alloy workpiece during DLBM. Five machining process factors, namely power diode, standoff distance, feed rate, duty cycle, and frequency, were used for the development of the model due to their correlation with KW. As in some cases, traditional soft computing methods cannot achieve high accuracy; in this investigation, an endeavor was made to introduce the GA-assisted ANFIS technique to predict kerf width while machining grooves in a titanium alloy workpiece using the DLBM process based on experimental results of a total of 50 combinations of the process parameters. It was observed that FIS was tuned well using the ANN in the ANFIS model with an R2 value of 0.99 for the training data but only 0.94 value for the testing dataset. The predicting performance of the GA-ANFIS model was better with less value for error parameters (MSE, RMSE, MAE) and a higher R2 value of 0.98 across different folds. Comparison with other state-of-the-art models further indicated the superiority of the GA-ANFIS predictive model, as its performance was superior in terms of all metrics. Finally, the optimal process parameters for minimum KW and SR, from gray relational–based (GRB) multi-response optimization (MRO) approach, were found as 20 W (level 2) for laser power, 22 mm (level 5) for standoff distance, 300 mm/min (level 5) for feed rate, 85% (level 5) for duty cycle, and 18 kHz (level 3) for frequency.

Effect of SiC addition on laser-based CoNi binary alloy coatings on Ti-6Al-4V alloy

AbstractThis research explores the impact of variations in laser scanning speed and the incorporation levels of SiC-Ni-Co powders on Ti-6Al-4V alloy using laser surface cladding technique. Key parameters, including a consistent laser power of 700 W, a 4 mm beam spot size, a powder feed rate of 1.0 g/min, and a gas flow rate of 3 L/min, along with fixed powder compositions, were maintained. The laser scanning speeds were adjusted to 0.4 m/min, 0.8 m/min, and 1.2 m/min. Microstructural analyses were carried out using scanning electron microscopy (SEM) while Vickers microhardness was employed to assess coating hardness, and corrosion properties were evaluated using a linear potentiodynamic polarization technique. Following the corrosion attack, the protective oxides formed were identified through SEM and X-ray diffractometer (XRD). The results revealed a strong metallurgical relationship between the clad layer and the substrate, demonstrating the effectiveness of the laser-clad technique. Particularly, the highest laser scan speed exhibited the most significant improvements in hardness and corrosion resistance. The coatings displayed an average hardness value of 1269.20 HV0.1, a notable fourfold increase compared to the substrate's value of 334 HV0.1. Concerning corrosion, a clear correlation emerged between scan speed and polarization resistance, confirming that higher scan speeds could lead to enhanced polarization resistance.

Strain-Based Assessment to Evaluate Damage Caused by Deep Rolling.

The positive effects of deep rolling on fatigue strength-reduced surface roughness, work hardening and compressive residual stress-in the near-surface region are achieved by controlled high plasticisation of the treated material. However, excessive and/or repeated plasticising poses a risk of damage to the machined component. This paper investigates the damage caused by deep rolling of a railway axle. Two sections of the axle are experimentally deep rolled repeatedly at different feed rates until damage is detected. For comparative analysis, these experiments are numerically analysed and the damage is assessed using the strain-based damage calculation. The results are compared and a damage sum of ~120% is evaluated for both tests, thus developing a reliable and conservative assessment method. The single deep rolling treatment at a feed rate of 0.25 mm causes damage of 6.1%, and at a feed rate of 0.5 mm, damage of 4.7%. The developed and experimentally validated evaluation method allows for investigating the limits of applicability of different deep rolling parameters. The influence of the deep rolling force and feed rate and a proposed optimisation with multiple deep rolling with reduced deep rolling forces are investigated.

Machinability performance of different fiber orientations of roll wrapped CFRP pipes

AbstractIntegrating fiber reinforcement plastics (FRP) materials into the industry plays a key role especially for pipes. However, due to the production methods of CFRP pipes, surface finishing processes are inevitable at the end of production. Despite the widespread use of CFRP materials, the predominant focus in the literature has been on their mechanical performance. This study aims to contribute to the limited research on the machinability of CFRP materials. In this context, the turning machining process for CFRP pipes was experimentally investigated in the present study. For this purpose, carbon fiber pipes with an inner diameter of 30 mm and an outer diameter of 60 mm were produced and subjected to computer numerical control (CNC) turning. First, a cylindrical aluminum pipe is used as a mold to manufacture CFRP pipes. Unidirectional (UD) carbon fabrics were wrapped on these aluminum molds. Shrink tape was used to enhance the surface smoothness and required pressure to prevent delaminating of the end product during the process. UD carbon fabrics are wrapped on to the mold at the selected angles (0°, 45°, and 90°) and the CFRP pipe specimens were manufactured using epoxy matrix. Pipes were processed on CNC lathe at 120, 160, 200 rev/min speeds and f 0.4 mm/rev feed rate. The surfaces of the machined specimens were measured with a microscope and a surface roughness device. On the other hand, wear on the tools was observed after the process.Highlights CFRP pipes were produced with different fibre orientations, i.e., 0°, 45°, and 90°. All CFRP pipes are made under equal conditions and cured at 80°. Turning of CFRP pipes was examined under dry environments. Performance criteria: surface roughness, temperature, tool wear, and chip formation were explored. 45° fibre angles CFRP pipes showed the best machinability performance.