Tool Nose Radius Research Articles

Impact of Toolpath Pitch Distance on Cutting Tool Nose Radius Deviation and Surface Quality of AISI D3 Steel Using Precision Measurement Techniques.

The selection of the right tool path trajectory and the corresponding machining parameters for end milling is a challenge in mold and die industries. Subsequently, the selection of appropriate tool path parameters can reduce overall machining time, improve the surface finish of the workpiece, extend tool life, reduce overall cost, and improve productivity. This work aims to establish the performance of end milling process parameters and the impact of trochoidal toolpath parameters on the surface finish of AISI D3 steel. It especially focuses on the effect of the tool tip nose radius deviation on the surface quality using precision measurement techniques. The experimental design was carried out in a systematic manner using a face-centered central composite design (FCCD) within the framework of response surface methodology (RSM). Twenty different experiment trials were conducted by changing the independent variables, such as cutting speed, feed rate, and trochoidal pitch distance. The main effects and the interactions of these parameters were determined using analysis of variance (ANOVA). The optimal conditions were identified using a multiple objective optimization method based on desirability function analysis (DFA). The developed empirical models showed statistical significance with the best process parameters, which include a feed rate of 0.05 m/tooth, a trochoidal pitch distance of 1.8 mm, and a cutting speed of 78 m/min. Further, as the trochoidal pitch distance increased, variations in the tool tip cutting edge were observed on the machined surface due to peeling off of the coating layer. The flaws on the tool tip, which alter the edge micro-geometry after machining, resulted in up to 33.83% variation in the initial nose radius. Deviations of 4.25% and 5.31% were noted between actual and predicted values of surface roughness and the nose radius, respectively.

Effects of magnetic intensity on the machining quality and tool damage in nickel-based superalloys subjected to magnetic-assisted cutting

Nickel-based superalloys are widely used in engine components due to their excellent high-temperature strength. However, their low plasticity and low thermal conductivity pose significant challenges in machining, leading to poor quality of machined parts and severe tool wear. Magnetic-assisted machining has received considerable attention as a clean and effective machining method, but its application to nickel-based superalloys is rarely reported, necessitating further exploration of its potential. This study focuses on GH4169 alloy and explores the effects of magnetic-assisted cutting (MAC) with varying intensities on the machining quality and tool wear. The experimental results indicate that the introduction of a magnetic field improves the machining quality by reducing tool wear and built-up edge adhesion. Additionally, both the plasticity and thermal conductivity of GH4169 alloy are improved under the effect of magnetic field, resulting in an 11.4 % decrease in cutting temperature. However, when the magnetic intensity ranges from 0.03 T to 0.12 T, secondary serration of the chip edges manifests, resulting in notch wear on the tool nose and a deterioration of surface quality. This secondary serration is attributed to the combined effect of tool nose radius and material plasticity under the magnetic field. As the magnetic field intensity increases further, the secondary serration gradually diminishes, and the surface roughness can be reduced by 26.5 % compared to traditional cutting. This study analyzed the relationship between machined surface, tool wear, chip morphology and magnetic field, and revealed the reasons for the differences in machining quality at different magnetic field intensities. These findings provide more possibilities for future applications of magnetic-assisted cutting to improve the machining quality of nickel-based superalloys and other difficult-to-machine metals.

Optimization of tool wear and surface roughness in ST-37 steel turning process with varying tool angles and machining parameters

The process of cutting low carbon steel (ST-37) typically utilizes High-Speed Steel (HSS) tools owing to their high hardness, affordability, and ease of shaping tool geometry. In machining, tool geometry plays a crucial role in the material cutting process and determines the quality of the final product, particularly surface roughness. The objective of this research is to achieve optimal surface roughness by varying the tool geometry and nose radius. This study employed an experimental approach using ST-37 and HSS tools. The variations in tool geometry include side rake angles of 12°, 15°, and 18°; side cutting edge angles of 85°, 80°, and 75°; and nose radii of 0 mm, 0.4 mm, and 0.8 mm. The machining parameters applied consist of a cutting depth of 1 mm and 2 mm, spindle rotation speeds of 185 rpm, 425 rpm, and 624 rpm, and a feed rate of 0.05 mm/rev, 0.075 mm/rev, and 0.1 mm/rev. Tool wear measurements were captured using a USB camera, whereas the surface roughness was assessed using a surface roughness tester. The impact of the tool geometry on the surface roughness was analyzed using the Taguchi-Grey Relational Analysis (Taguchi-GRA) and ANOVA methods. The optimal combination for ST-37 lathe machining with a sharpening tool is: A1 (cutting depth 1 mm), B1 (cutting speed 17.42 m/min), C3 (feed 0.05 mm/rev), D1 (corner radius 0 mm), E3 (side rake angle γ 18°), and F3 (side cutting edge angle γ 75°). According to the Analysis of Variance (ANOVA), three factors—cutting speed, tool tip angle, and chip angle—should be considered to achieve minimal tool wear and desirable surface roughness during machining

An Experiment Study on Surface Topography of GH4169 Assisted by Ultrasonic Elliptical Vibration Ultra-Precision Turning

Nickel-based superalloys (GH4169) are a typical difficult-to-machine material with poor thermal conductivity and severe work hardening. They are also prone to poor surface quality, severe tool wear, and poor machinability, which affect their performance. In this paper, an experimental study of GH4169 ultrasonic elliptical vibratory ultra-precision cutting was carried out. The experimental results show that ultrasonic elliptical vibratory cutting (UEVC) significantly reduces surface roughness and improves surface quality compared to conventional cutting (CC). The effects of cutting parameters such as cutting speed, feed rate, cutting depth, ultrasonic amplitude, and tool nose radius on the surface roughness of GH4169 workpieces were further investigated in UEVC. Based on the analysis of the experimental data, the optimal combination of parameters for GH4169 ultrasonic elliptical vibration ultra-precision cutting was determined: cutting speed of 3 m/min, feed rate of 16 μm/rev, cutting depth of 2 μm, ultrasonic amplitude of Ay = 3.0 μm, Az = 0.8 μm, and a tool nose radius of 0.8 mm. This parameter combination improves the machining quality of GH4169 and provides a valuable reference for the subsequent development of ultrasonic elliptical vibratory cutting for other difficult-to-machine materials.

Effects of chip breaker groove and tool nose radius on progressive tool wear and behavior when turning GH3536 nickel-based superalloys

Nickel-based superalloys are typically challenging to machine and often exhibit severe tool wear during the turning process, thus attracting substantial research attention. This study not only explores the tool wear mechanisms when turning GH3536 nickel-based superalloys but also introduces a focus on the role of tool geometry configuration. Tools with different chip breaker groove structures and nose radii were investigated, with results indicating the tool wear mechanisms were predominantly abrasive and adhesive. For the 04HA chip breaker, which has a 9° rake angle and a "V"-shaped bottom, there is a single point of impact with the chip during cutting, while the 04VP3 chip breaker, with a 15° rake angle and a flat bottom, has two points of impact with the chip during cutting, increasing chip deformation and favoring chip breaking, thereby suppressing the formation of built-up edge. Additionally, changes in the nose radius influenced the degree of work hardening and consequently influence the severity of notch wear, with the nose radius also impacting the chip flow angle. Based on this finding, a theoretical mathematical model describing the initial chip flow angle was established and validated. Additionally, an examination of the effects of varying operating parameters on tool life was conducted, revealing that cutting speed was the most significant factor affecting tool life, followed by feed rate and depth of cut.

Evaluation of cutting parameters during dry turning of AISI 304 stainless steel and optimization through a modified WPCA approach

The main objective of this study is to analyze how input parameters such as cutting speed ( Vc), depth of cut ( ap), feed per revolution ( f), and tool nose radius ( r) influence the performance of dry turning AISI 304 stainless steel. Performance evaluation includes cutting force components ( Fx, Fy, and Fz), surface roughness (SR), material removal rate (MRR), cutting power ( Cp), and cutting temperature ( T). Experiments are planned using the Taguchi L18 experimental design, and a coated carbide tool (GC 2025) is employed. ANOVA revealed that the most influential factors on SR are f and r, contributing 52.40% and 26.54%, respectively. Axial and tangential cutting force components are influenced by ap and f, with contributions of 72.99% and 5.93% for Fx and 81.57% and 13.38% for Fz, respectively. The radial component is influenced by ap (85.74%). Vc, f, and ap all contribute to cutting power, with contributions of 55.13%, 24.35%, and 10.74%, respectively. Finally, ap and the interaction f*ap contribute 45.18% and 8.81%, respectively, to the temperature in the cutting zone. This article introduces a novel multi-objective optimization method based on weighted principal component analysis. This method distinguishes itself by its ability to address challenges related to data matrix normalization, the ambiguity of eigenvector signs, and the issue of negative signs in Taguchi’s philosophy. The results of the new method, the desirability function, and the classical WPCA method are compared. The results show that the new method suggests a compromise solution that is similar to the desirability function and better than the classical WPCA’s suggestion.

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.

Comparing Bio-Ester and Mineral-Oil Emulsions on Tool Wear and Surface Integrity in Finish Turning a Ni-Based Superalloy

The paper compares the performance of two bio-ester and two mineral-oil emulsion metalworking fluids (MWFs) in finish turning an Inconel 718 alloy bar with a high hardness (HB 397 – 418). In this study, a coolant with a lean concentrate diluted at 6.5% to create an emulsion with stabilised water hardness was used to prepare each MWF. The finish-turning method used a small tool nose radius (0.4 mm) and small depth of cut (0.25 mm) to turn down 52.2 mm diameter bars in multiple passes to reach a maximum tool flank wear of 200 µm. In each MWF turning test, the tool flank wear, cutting forces, and surface roughness were measured against cut time. Chips from each MWF turning test were also collected at the same cut time instances. The surface and subsurface integrity on a workpiece obtained from each MWF turning test were compared by using a new unworn tool. Overall, for the machining parameters studied, the findings suggest the bio-esters were capable of equivalent machining performance as the mineral-oil emulsions, apart from one bio-ester that displayed improved surface roughness. Common to all MWF turning tests was a change in the chip form at low flank wear, which is discussed. Further findings discussed include the sensitivity of the concentration of the MWF diluted in the emulsion and the effect of the workpiece hardness within the batch used, with useful recommendations to improve the finish-turning method for the assessment of MWFs.

Reliability analysis of PVD-coated carbide tools during high-speed machining of Inconel 800

Predicting the cutting tool life is crucial for effectively managing machining costs, ensuring product quality, maintaining equipment availability and minimising waste in machining processes. When machining heat-resistant superalloys such as Inconel, the concern for tool life becomes even more pronounced. Cutting tool failure is a complex phenomenon that depends on several variables, including tool type and material, workpiece material, machine tool type and machining parameters. Traditional run-to-fail tests to predict tool life are costly and time-consuming. To address these challenges, accelerated degradation testing (ADT) offers a promising solution. ADT involves subjecting the component to higher levels of parameters, causing it to fail faster than under normal conditions. This approach saves time and reduces expenses associated with tool life tests for valuable workpieces. In implementing the concept of ADT, the experimental cutting speed [Formula: see text] values are selected much higher than the normal usage levels in the present study. The tool life tests are performed at three levels of [Formula: see text], feed rate [Formula: see text], depth of cut [Formula: see text] and tool nose radius [Formula: see text] using the Taguchi L9 orthogonal array. Parametric statistical approaches, that is, accelerated failure time (AFT) models, are applied with distributions, namely the Weibull, lognormal and log-logistic distributions, to analyse the cutting tool’s reliability based on predictor variables. Various tool wear modes are considered criteria for tool failure. The comparison is made among the mean time to failure (MTTF) of cutting tools as predicted by various fitted models. Additionally, a favourable tool failure pattern is observed when using the middle level of [Formula: see text] and operating at relatively higher [Formula: see text] values while ensuring that [Formula: see text] and [Formula: see text] values fall within the recommended range. The proposed approach has the potential for diverse applications, including assessing the reliability of cutting tools and tool condition monitoring.

Optimization of Multiple Performance Characteristics for CNC Turning of Inconel 718 Using Taguchi–Grey Relational Approach and Analysis of Variance

The optimization of machining processes is a deciding factor when increasing productivity and ensuring product quality. The response characteristics, such as surface roughness, material removal rate, tool wear, and cutting time, of the finish turning process have been simultaneously optimized. We used the Taguchi-based design of experiments L9(34) in this study to test and find the best values for process parameters like cutting speed, feed rate, depth of cut, and nose radius. The Taguchi-based multi-objective grey relational approach (GRA) method was used to address the turning problem of Inconel 718 alloy to increase productivity, i.e., by simultaneously minimizing surface roughness, tool wear, and machining time. GRA and the S/N ratio derived from the Taguchi approach were utilized to combine many response characteristics into a single response. The grey relational grade (GRG) produces results such as estimations of the optimal level of input parameters and their proportional significance to specific quality characteristics. By employing ANOVA, the significance of parameters with respect to individual responsibility and the overall quality characteristics of the cutting process were ascertained. The single-objective optimization yielded the following results: minimal surface roughness of 0.167 µm, tool wear of 44.65 µm, minimum cutting time of 19.72 s, and maximum material speed of 4550 mm3/min. While simultaneously optimizing the Inconel 718 superalloy at a cutting speed of 100 m/min, depth of cut of 0.4 mm, feed rate of 0.051 mm/rev, and tool nose radius of 0.4 mm, the results of the multi-objective optimization showed that all investigated response characteristics reached their optimal values (minimum/maximum). To validate the results, confirmatory experiments with the most favorable outcomes were conducted and yielded a high degree of concurrence.

Investigation Of Machinability Characteristics Of Sae Ams4413b Aluminum Alloy Using Ethylene Glycol As A Coolant

To understand the efficient machining of aerospace materials and achieve high quality machining, the application of coolants is essential and is based on the several factors including the types of machining process, workpiece material, tool nose radius, coolant concentration and cost. With the right type of coolants used, the performance of machining applications and the attributes of responses such as Surface roughness can be remarkably enhanced and HAZ can be improved. An attempt is made here to study the machinability and optimize the process parameters.&#x0D; This paper presents an outline to optimize the Machinability studies on SAE AMS4413B alloy using Ethylene glycol as a coolant. The input parameters selected such as Cutting speed, Feed, depth of cut, coolant concentration, tool nose radius on Surface Roughness (Ra) and Heat Affected Zone (HAZ). A robust DOE based technique stresses for study of response variation using Central Composite design (CCD). The CCD design is a class of Response Surface Methodology used to design the matrix. The experiments are conducted for the confidence levels of 95%. R2 predicted for Ra and HAZ is 95.26% and 95.51% respectively. As per the experimental analysis it is evident the individual effect of Cutting Speed, Feed, Depth of cut, Tool nose radius and Coolant concentration exists for the Ra and HAZ values. Optimum values of Ra and HAZ are 0.21 µm and 20.3 IACS. Selection of the Coolant concentration For Ethylene Glycol shall be in the range of 8-10%.

Influence factors and prediction model of surface roughness in single-point diamond turning of polycrystalline soft metal

Ultrasmooth surface of soft metals is required in the field of advanced technology. However, the strong plasticity of soft metals makes it hard to achieve high surface finishing in ultraprecision machining. In this paper, the ultraprecision machining experiments of polycrystalline tin are carried out, and the factors including tool nose radius, cutting parameters, and material properties affecting the surface roughness in single-point diamond turning are investigated. Side flow, anisotropy, and grain boundary step are identified as the main causes of increasing of surface roughness, with grain boundary step demonstrating the largest impact. A surface roughness prediction model of tin in single-point diamond turning is established, which takes the minimum undeformed chip thickness, side flow, anisotropy and grain boundary step into consideration. The experiments show that the maximum prediction error of this prediction model is 6.51%.

Influence of cutting parameters and tool nose radius on the wear behavior of coated carbide tool when turning austenitic stainless steel

This study investigated the wear behavior of coated carbide tool with different tool nose radius under different cutting parameters when turning AISI 321 austenitic stainless steel. The full factorial turning experiments with three factors and two levels cutting parameters were carried out. The wear progression of the tool with cutting time was recorded. The tool wear mechanism and the influence of cutting parameters and tool nose radius on the tool wear behavior were analyzed. The results showed that the cutting tool mainly exhibited wear manners of abrasive wear, adhesive wear, and oxidation wear. The tool life varies a lot with the cutting parameters, with the feed rate the most sensitive. Decrease the nose radius makes the strength of the tool blade worsened, thereby increasing the tool life sensitivity to cutting parameters. However, decreasing the tool nose radius can effectively increase the tool life. The reason is that when the tool nose radius is reduced, the cutting temperature can be decreased and at the same time the chip breaking performance can be improved, which decrease the mechanical damage of chips to the tool and related wear, and thus resulting in a longer tool life.

Long Sump Life Effects of a Naturally Aged Bio-Ester Oil Emulsion on Tool Wear in Finish Turning a Ni-Based Superalloy

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

Experimental Analysis of Machining Parameters In Turning of Aluminum 7075

High-Speed Machining (HSM) of aluminum alloys represents a critical area in manufacturing industries, including automotive, aerospace and consumer electronics. This research presents an in-depth investigation into the effects of key process parameters on the HSM of Aluminum 7075, a high-strength alloy with superior mechanical properties. Utilizing the central composite design of Response Surface Methodology (RSM), the study scrutinizes the impact of process parameters, including cutting speed, feed, depth of cut and tool nose radius on surface roughness. The findings reveal feed and nose radius as primary factors influencing surface roughness while cutting speed and depth of cut play secondary roles. This comprehensive analysis contributes to the knowledge base for efficient machining practices and lays the groundwork for future optimization strategies. It also underscores the necessity for further research into understanding the intricate dynamics of machining parameters to enhance operational efficiency and product quality in the machining of Aluminum 7075 and similar alloys.

Grey Relational Analysis-based Interactions of Machining Parameters for Optimal Process Response: An Experimental Initiative

This study, investigated the optimal combining of tool nose radius and cutting variables for the overall performance for both AISI 4140 steel and IS-2062 steel. The both materials were machined on a centre lathe and measurements were taken. The data collected was analysed through grey relational analysis. Results showed that grey relational optimal interactions of machining parameters for the overall performance were: N R (0.35mm), U o (0.5mm), V w (65m/min), R f (0.2mm/rev) for both materials. Also, grey relational grade improved by 1.2767 (24.69%) for the expected optimal design for AISI-4140 steel, and improved by 1.7417 (33.68%) for the expected optimal design for IS-2062 steel. The expected responses were: cutting power 11.157 kW, specific metal removal rate 9.710 mm3/min.kW, cutting force 173.110 N, thrust force 77.207 N, shear force 124.838 N, surface roughness 5.00 , and Shear work 7945.9kNm/min for AISI-4140 steel; and cutting power 5.544 kW, specific metal removal rate 19.541 mm3/min.kW, cutting force 86.074 N, thrust force 39.440 N, shear force 65.688 N, surface roughness 6.165 , and shear work 4158.67 KNm/min for IS-2062 steel. Grey relational analysis reduced the factors affecting on the dependent variables to feed rate and depth of cut.

Investigating the machinability behaviour of Al7075/SiC5CS5 hybrid composite with the variation of tool geometry

This research investigates the machinability behavior of an Al7075 hybrid composite fabricated with micro-sized cenosphere (CS) and silicon carbide (SiC) particles. The composite was fabricated using stir-casting with ultrasonic assistance. The experimental study investigated the effect of variation of machining regimes (i.e., feed rate, cutting speed, and depth of cut) and tool geometry (tool nose radii) on main cutting force and tool tip temperature. For the study, the Cermet tool was considered as tool material for the dry turning of aluminum alloy and composite. In addition, a regression model was created using the response surface method (RSM) technique. The results indicate that the developed model can accurately predict output regimes with an accuracy ranging from 80.44 to 99.98%. Further, by using sequential approximation optimization, the optimal combination of input regimes for maximal metal removal rate was identified.

Analytical prediction of chip flow direction in cylindrical turning considering rounded edge effect

The flow direction of a no-free chip has a vital influence on chip control and the machined surface's integrity. In order to establish an accurate prediction model of chip flow direction, a new analytical model considering the effect of workpiece materials and tool nose radius on chip flow direction is proposed for cylindrical turning. The rounded edge engaged in cutting is segmented into many oblique cutting units to consider the effect of the nose radius on the chip flow, whose thermomechanical process of chip formation is characterized by the unequal division shear zone method. The mutual action forces of each discrete chip are calculated to determine the resultant chip flow direction, and the interaction between the constrained chip units is comprehensively considered as non-free chip flow. Simultaneously, the influences of material constitutive and cutting parameters on the flow direction of discrete chip and resultant chip are analyzed by thermomechanical coupling method. The conducted mechanism of the nose radius and the main cutting edge angle on unconstrained and constrained chips is studied. The predicted results of chip flow direction were validated with experimental values and Colewell's model, and the FE simulation was also used to compare with the proposed model, interesting agreement was found.

Statistical analysis, modeling and multi-objective optimization of parameters intermittent turning process of AISI D3

Intermittent machining is characterized by its complex and irregular context. This intermittency causes machining to occur under difficult conditions that greatly influence the technological performance parameters. The aim of the present work is to evaluate the effects of input parameters, cutting speed, Vc, depth of cut, ap, tool nose radius, r and feed rate, f, on surface roughness, Ra, tangential cutting force, Fz, motor power consumption, Pm, cutting power, Pc and material removal rate (MRR), during intermittent turning (IT) of AISI D3 tool steel. Machining was performed with a triple CVD coated carbide tool (AI2O3/TiC/TiCN) by adopting a Taguchi L9 (3^4) experimental design. The ANOVA and RSM methods were used to analyze the effects of cutting factors on the outputs parameters resulting in statistical prediction models. In addition, a multi-objective optimization of the cutting conditions exploiting the desirability function (DF) was done according to four cases of relative importance corresponding to different industrial contexts. Furthermore, the grey relational analysis (GRA) method was applied and compared with the DF method. The results show that the optimal regime found by the DF method, (r =1.6mm, Vc= 240 m/min, f = 0.084 mm/rev and ap = 0.64 mm), favors Ra and MRR. On the other hand, for the GRA method, the combination of (r = 0.4 mm, Vc = 240 m/min f = 0.08 mm/rev and ap = 0.3 mm) favors the minimization of Fz, Pm and Pc. This work presents an originality because the results found are very useful in the field of optimization for a better control of the process IT.

Investigation on surface quality in micro milling of additive manufactured Ti6Al4V titanium alloy

The additive manufactured technology is widely applied to produce titanium alloy parts with complex structures. The subsequent machining operations are necessary for additive manufactured parts to achieve the required machining quality. In this paper, the theoretical surface roughness model in micro milling was established. The model indicated the theoretical milled roughness mainly depends on the feed per tooth, tool nose radius and bottom edge inclination angle. Then, micro milling experiments are conducted on additive manufactured titanium alloy using PCD micro end mill. The surface roughness on milled surface was measured and investigated. At the middle position of micro milled surface, the distribution curves of surface roughness Ra and Sa show the same variation trend under different milling parameters. Moreover, the measured surface roughness results on different transverse positions of milled surface showed that the difference value between the actual and theoretical surface roughness of milled surface is mostly induced by the unstable cutting behaviors, which is also mainly responsible for the surface roughness size effect. The transverse distribution of surface roughness on milled surface exhibited a W shape because of the variation of the instantaneous undeformed chip thickness and material removal mode at different transverse positions.