Comparative assessment of cooling conditions,including MQL technology on machining factors in an environmentally friendly approach

Manufacturers need to continuously improve productivity and reduce the most disadvantages. In the current work, an experimental study has been carried out in order to evaluate the influence of different cutting parameters on the various machining factors such as surface roughness, cutting force, cutting power, metal removal rate, and tool wear during turning of X210Cr12 steel using a multilayer-coated tungsten carbide insert with various nose radii (r). Tests are designed according to Taguchi’s L₁₈ (2¹ × 3⁴) orthogonal array. ANOVA has been performed to determine the effect of the cutting conditions, and mathematical models have been developed through response surface methodology (RSM). The results indicate that the feed rate and the tool nose radius are the main affecting factors on surface roughness while both tangential force and cutting power are affected mainly by the depth of cut followed by the feed rate and the nose radius. Other special tests of long term have been established in order to study the wear evolution and consequently to determine the tool life. The results indicate also that minimum quantity lubrication (MQL) leads to an important improvement in terms of the cutting tool life by a gain of 23~40% compared to wet and dry machining. It has been found that the MQL is an interesting way to minimize lubrication cost and protect operator health and the environment while keeping better machining quality.     

Machining performance of a grooved tool in dry machining Ti-6Al-4 V

In this paper, dry machining experiment of Ti-6Al-4 V was carried out to investigate the machining performance of a grooved tool in terms of its wear mechanisms and the effects of cutting parameters (cutting speed, feed rate, and cutting depth) on tool life and surface roughness of the machined workpiece. The results showed that chip-groove configuration substantially improved the machining performance of cutting tool. The main wear mechanisms of the grooved tool were adhesive wear, stripping wear, crater wear, and dissolution-diffusion wear. The resistance to chipping was enhanced due to the decrease of contact pressure of tool-chip interface. And the resistance to plastic deformation of tool nose was weakened at the cutting speed of more than 60 m/min. The appropriate cutting speed and feed rate were less than 70 m/min and 0.10 mm/r, respectively. With cutting speed increasing, the surface roughness of machined workpiece decreased. A high feed rate helped the formation of higher surface roughness except 0.21 mm/r. When cutting depth increased, tool nose curvature and phase transformation of workpiece material had great impact on surface roughness.     

Effect of machining parameters on surface roughness and tool wear for 7075 Al alloy SiC composite

In the present study, an attempt has been made to investigate the influence of cutting speed, depth of cut, and feed rate on surface roughness during machining of 7075 Al alloy and 10 wt.% SiC particulate metal-matrix composites. The experiments were conducted on a CNC Turning Machine using tungsten carbide and polycrystalline diamond (PCD) inserts. Surface roughness of 7075Al alloy with 10 wt.% SiC composite during machining by tungsten carbide tool was found to be lower in the feed range of 0.1 to 0.3 mm/rev and depth of cut (DOC) range of 0.5 to 1.5 mm as compared to surface roughness at other process parameters considered. Above cutting speed of 220 m/min surface roughness of SiC composite during machining by PCD tool was less as compared to surface roughness at other values of cutting speed considered. Wear of tungsten carbide and PCD inserts was analyzed using a metallurgical microscope and scanning electron microscope. Flanks wear of carbide tool increased by a factor of 2.4 with the increase of cutting speed from 180 to 240 m/min at a feed of 0.1 mm/rev and a DOC of 0.5 mm. On the other hand, flanks wear of PCD insert increased by only a factor of 1.3 with the increase of cutting speed from 180 to 240 m/min at feed of 0.1 mm/rev and DOC 0.5 mm.     

Modelling the effects of cutting parameters on residual stresses in hard turning of AISI H11 tool steel

In the present study, an attempt has been made to model the effect of cutting parameters (cutting speed, feed, depth of cut and nose radius) on residual stresses in hard turning of AISI H11 tool steel using ceramic tools. The machining experiments were conducted based on response surface methodology and using the Box–Behnken design of experiments. Residual stresses were determined using the X-ray diffraction technique, and the experimental results were investigated using analysis of variance. The results indicated that the feed and depth of cut are the main influencing factor on residual stresses whereas cutting speed and nose radius are having mild impact on residual stresses. The results show that it is possible to produce tailor-made residual stress levels by controlling the tool geometry and cutting parameters. The aim of this paper is to introduce an original approach for the prediction of residual stresses.     

Experimental observations on surface roughness, chip morphology, and tool wear behavior in machining Fe-based amorphous alloy overlay for remanufacture

Fe-based amorphous alloy, a new-type material, was developed as a special-purpose welt overlay for remanufacture. It was deposited on the worn-out part for resuming and upgrading part performance. The microstructure characteristics of the overlay was characterized, including microstructure, phase composition, thermostability, and microhardness. In order to get a comprehensive insight to the machining process of amorphous overlay, this paper presents an experimental investigation into the effect of various machining parameters and tool geometry (Edge) on the surface roughness, tool wear, chip morphology, and surface damage. Comparing larger rake angle of 15°and smaller nose radius of 0.4 mm with 5° and 0.8 mm at the same cutting parameters, we found that larger rake angle of 15° and smaller nose radius of 0.4 mm increased the R _a surface roughness parameter. In the tests, crater wear was not observed, and the friction and wear on the minor cutting edge wear were heavy due to the spring back of the machined surface. In brief,abrasion, adhesion, fatigue, and chipping are the main wear mechanism. As the feed rate reduced and the depth of cut increased (from feed rate?=?0.06 mm/rev and depth of cut?=?0.3 mm to feed rate?=?0.09 mm/rev and depth of cut?=?0.2 mm), a number of physical changes occurred in the chip including reduced distance between serrations, increased shear band angle, and changed chip morphology from spiral to ribbon shape. The results show that strain and strain rate rises in the chips’ inside with the increase in cutting temperature. When the thermal softening exceeded strain hardening, the shear resistance decreased rapidly. Thus, the free surface of the chip presents the nodular and lamella structure. It was noted that specimens generated by larger rake angle of 15° and smaller nose radius of 0.4 mm showed poor surface roughness as well as extensive surface damage.     

PCBN刀具切削堆焊钴基合金的试验研究

采用PCBN刀具对堆焊钴基高温合金层进行切削试验,研究不同的切削用量和刀尖圆弧半径对表面粗糙度和切削力的影响规律,并采用离差分析法对其影响程度进行评估。试验结果及分析表明:切削加工堆焊钴基合金时,切削力和表面粗糙度的部分变化规律有别于传统切削理论,这是因为钴基堆焊合金特有的物理机械性能、堆焊层组织状态、PCBN刀具的性能特点及所选取的几何参数使切削区域材料性能变化和刀具磨损特征不同于传统切削理论所致。试验获得的表面粗糙度值较小,符合以车代磨的加工工艺要求。由离差分析结果可知,进给量对表面粗糙度、主切削力和背向力影响最大,背吃刀量对进给力的影响最大。     

Assessment of flank wear and nose radius wear from workpiece roughness profile in turning operation using machine vision

Although literature on the measurement of flank wear and crater wear in single-point turning tools using machine vision is well documented, the study on the effect of nose radius wear on the roughness profile and dimensional changes of workpiece is less explored. The measurement of flank wear using the 2-D profile of the tool nose region or the roughness profile of the workpiece has also not been attempted in the past. In this work, the nose radius wear of cutting tools and roughness profile of turned parts in a lathe operation were measured using the machine vision method. The flank wear width VB_C in the nose area was determined from the nose radius wear using the tool setup and machining geometry. The nose radius wear was also determined from the roughness profile of the workpiece and used in calculating the flank wear width. Comparison between the maximum flank wear width VB_Cmax determined from the roughness profile and that obtained using a toolmaker’s microscope showed a mean deviation of 5.5%. This result indicates that flank wear can be determined fairly accurately from the workpiece roughness profile if the tool and machining geometry are known.     

Prediction of cutting force, tool wear and surface roughness of Al6061/SiC composite for end milling operations using RSM

The results of mathematical modeling and the experimental investigation on the machinability of aluminium (Al6061) silicon carbide particulate (SiCp) metal matrix composite (MMC) during end milling process is analyzed. The machining was difficult to cut the material because of its hardness and wear resistance due to its abrasive nature of reinforcement element. The influence of machining parameters such as spindle speed, feed rate, depth of cut and nose radius on the cutting force has been investigated. The influence of the length of machining on the tool wear and the machining parameters on the surface finish criteria have been determined through the response surface methodology (RSM) prediction model. The prediction model is also used to determine the combined effect of machining parameters on the cutting force, tool wear and surface roughness. The results of the model were compared with the experimental results and found to be good agreement with them. The results of prediction model help in the selection of process parameters to reduce the cutting force, tool wear and surface roughness, which ensures quality of milling processes.     

Experimental investigation of the three-component forces in finish dry hard turning of hardened tool steel at different hardness levels

In this paper, the effects of cutting speed, depth of cut, feed, workpiece hardness (51, 55, 58, 62, and 65?±?1 HRC), tool flank wear, and nose radius on three-component forces in finish dry hard turning (FDHT) of the hardened tool steel AISI D2 were experimentally investigated by utilizing the PCBN inserts. Experimental results showed that the feed force is the lowest in three-component forces and influence of cutting parameters on it is less than two others in the FDHT of AISI D2. Values of the radial force are higher than those of the cutting force when cutting speed, depth of cut, and feed range from 75 to 301 m/min, and 0.10 to 0.40 and 0.05 to 0.20 mm, respectively, but lower in the range between 0.8- and 1.6-mm nose radius. Values of the cutting force are higher than those of the radial force as the workpiece hardness varies from 51 to 58?±?1 HRC while lower in the range between 62 and 65?±?1 HRC. Besides, there are relations between the changing laws of three-component forces and the softening effect of chip, cohesion effect in the tool–chip junction zone, and intenerating effect of metal in the workpiece surface. The high flank wear formation increases the contact with workpiece surface and hence induces tearing–drawing and welding effect duo to instantaneous high temperature.     

Evaluation on Effectiveness of CVD and PVD Coated Tools during Dry Machining of Incoloy 825

With wide applications of nickel-based superalloys in strategic fields, it has become increasingly necessary to evaluate the performance of different advanced cutting tools for machining such alloys. With a view to recommend a suitable cutting tool, the present work investigated various machinability characteristics of Incoloy 825 using an uncoated tool, chemical vapor deposition (CVD) of a bilayer of TiCN/Al₂O₃, and physical vapor deposition (PVD) of alternate layers of TiAlN/TiN-coated tools under varying machining conditions. The influence of cutting speed (51, 84, and 124 m/min) as well as feed (0.08, 0.14, and 0.2 mm/rev) was comparatively evaluated on surface roughness, cutting temperature, cutting force, coefficient of friction, chip thickness, and tool wear using different cutting tools. Although the CVD-coated tool was not useful in decreasing surface roughness and temperature, a significant reduction in cutting force and tool wear could be achieved with the same coated tool under a high cutting speed of 124 m/min. On the other hand, the PVD-coated tool outperformed the other tools in terms of machinability characteristics. This might be attributed to the excellent antifriction and antisticking property of TiN and good toughness due to the multilayer configuration in combination with a thermally resistant TiAlN phase. Adhesion, abrasion, edge chipping, and nose wear were the prominent wear mechanisms of the uncoated tool, followed by the CVD-coated tool. However, remarkable resistance to such wear was evident with the PVD TiAlN/TiN multilayer-coated tool.     

Selection of an optimal parametric combination for achieving a better surface finish in dry milling using genetic algorithms

In machining, coolants improve machinability, increase productivity by reducing tool wear and extend tool life. However, due to ecological and human health problems, manufacturing industries are now being forced to implement strategies to reduce the amount of cutting fluids used in their production lines. A trend that has emerged to solve these problems is machining without fluid – a method called dry machining – which has been made possible due to technological innovations. This paper presents an experimental investigation of the influence of tool geometry (radial rake angle and nose radius) and cutting conditions (cutting speed and feed rate) on machining performance in dry milling with four fluted solid TiAlN-coated carbide end mill cutters based on Taguchi’s experimental design method. The mathematical model, in terms of machining parameters, was developed for surface roughness prediction using response surface methodology. The optimization is then carried out with genetic algorithms using the surface roughness model developed and validated in this work. This methodology helps to determine the best possible tool geometry and cutting conditions for dry milling.     

Fabrication of polycrystalline diamond microtool using a Q-switched Nd:YAG laser

A Q-switched Nd:YAG laser (1,064 nm, 100 ns) was used to machine 2?×?1.5?×?0.5-mm rhombus-shaped tool inserts from a 60?×?0.5-mm circular disk of polycrystalline diamond. A systematic experimental study was undertaken to examine the effects of pulse repetition rate, feed rate, and number of laser passes on kerf, material removal rate, recast layer, surface morphology, and surface roughness. The optimal laser parameters for generating two-dimensional tool profiles were an average power of 3 W, a pulse repetition rate of 2 kHz, a feed rate of 1 mm/s, and a total of 45 laser passes. The beneficial results were a material removal rate of 0.02 mm³/min, kerf width of 27 μm, cutting edge radius of 6 μm, and surface roughness (Ra) of 0.625 μm. Recast layer formation, undulations, and striations were observed in the laser-cut regions. These features were attributed to the presence of a molten layer of cobalt binder, and amorphous carbon and graphite transitioned from diamond. An intriguing feature is the presence of fine particulate matter ranging in size from nanometers to a few micrometers in the laser-cut regions. It is believed that phase transition of diamond and cobalt during laser machining created thermal expansion mismatch stresses sufficient to fracture the solid into fine fragments.     

Hard turning: Parametric optimization using genetic algorithm for rough/finish machining and study of surface morphology

The present study reports the effect of different process parameters on machining forces, surface roughness, dimensional deviation and material removal rate during hard turning of EN31, SAE8620 and EN9 tool steels. Feed rate followed by hardness, cutting speed and nose radius-depth of cut significantly affected machining forces whereas feed rate had the largest effect on surface roughness. The four responses were subsequently optimized for both rough and finish machining using genetic algorithm to determine the optimum combination of input parameters. Machined surfaces were subsequently analyzed using XRD followed by analysis of grain size and crystallite size of the machined samples and SEM analysis. Higher chromium content was observed at the machined surface as manganese dissolves in cementite and may replace iron atoms in the cementite lattice after machining. High heat is generated when machining at higher cutting speeds causing severe strain. The depth of the white layer decreases with increasing tool nose radius and increases at larger feeds because of greater heat generation. The SEM observations showed a smooth pattern with very low undulations with almost no crack damage.     

Kinematics prediction and experimental validation of machined surface roughness

Online monitoring of surface roughness is a desirable capability for machining processes; however, 100 % inspection of all parts is not feasible unless it can be integrated into the machining process itself through real-time monitoring of cutting conditions. One strategy is to feed these conditions into a predictive modeling kernel which would in turn give the properties of the finished part. In the case of roughness, the surface resulting from turning can be largely represented as the trace of the passing tool geometry. The question addressed herein is whether computationally intensive modeling of the surface accounting for tool nose radius is necessary for online monitoring of surface roughness. This paper presents a predictive modeling methodology wherein the tool-workpiece contact position varies under a simple cutting model, and the resulting surface roughness is estimated. It presents the concept of calculating a “pseudo-roughness” value based only on tool tip locations and to compare this value to that determined by full predictive modeling of the tool geometry. Cutting experimental data has been presented and compared to predictions for model validation. It is found that the root mean square roughness calculation is dominated by tool geometry, rather than tool position deviations and surface roughness estimation could be implemented without a computationally intensive modeling component, thereby enabling online monitoring and potentially real-time control of the part finish.     

Effect of the process parameters on the three-dimensional shape of molten pool during full-penetration laser welding process

Slow tool servo (STS) turning is superior in machining precision and in complicated surface. However, STS turning is a complex process in which many variables can affect the desired results. This paper focuses on surface roughness prediction in lenses STS turning. An exponential model, based on the five main cutting parameters including tool nose radius, feed rate, depth of cut, C-axis speed, and discretization angle, for surface roughness prediction of lenses is developed by means of orthogonal experiment regression analysis. Meanwhile, a prediction model of surface roughness based on least squares support vector machines (LS-SVM) with radial basis function is constructed. Orthogonal experiment swatches are studied, and chaotic particle swarm optimization and leave-one-out cross-validation are applied to determine the model parameters. The comparison of LS-SVM model and exponential model is also carried out. Predictive LS-SVM model is found to be capable of better predictions for surface roughness and has absolute fraction of variance R² of 0.99887, the mean absolute percent error e_M of 8.96 %, and the root mean square error e_R of 10.68 %. The experimental results and prediction of LS-SVM model show that effects of tool nose radius and feed rate are more significant than that of depth of cut on surface roughness of lenses turning.     

Measurement of nose radius wear in turning tools from a single 2D image using machine vision

Flank and crater wear in cutting tools have been extensively studied in the past using direct and indirect methods. In finish and hard turning, however, nose radius wear plays a greater role in determining the surface quality of the finished product. This is due to the direct interaction between the tool nose area and the workpiece during machining. Nose radius wear can be measured from the 2D profiles of the tool before and after machining using a vision method. This approach, however, requires two images of cutting tools to be recorded and precisely aligned before subtraction. This work proposes a new method of measuring nose wear area from a single 2D image of the worn tool. The nose profile is extracted in the Cartesian coordinates and converted to a polar-radius plot. From the plot, the nose wear area is determined by simple subtraction.     

Selection of optimum tool geometry and cutting conditions using a surface roughness prediction model for end milling

Influence of tool geometry on the quality of surface produced is well known and hence any attempt to assess the performance of end milling should include the tool geometry. In the present work, experimental studies have been conducted to see the effect of tool geometry (radial rake angle and nose radius) and cutting conditions (cutting speed and feed rate) on the machining performance during end milling of medium carbon steel. The first and second order mathematical models, in terms of machining parameters, were developed for surface roughness prediction using response surface methodology (RSM) on the basis of experimental results. The model selected for optimization has been validated with the Chi square test. The significance of these parameters on surface roughness has been established with analysis of variance. An attempt has also been made to optimize the surface roughness prediction model using genetic algorithms (GA). The GA program gives minimum values of surface roughness and their respective optimal conditions.     

单点金刚石切削加工表面粗糙度的影响因素分析

本文研究了单点金刚石切削加工表面微观形貌形成机理,建立了圆弧刃金刚石刀具超精密加工表面微观形貌的理论模型,重点分析了主轴转速、进给量、刀尖圆弧半径和振动等因素对超精密加工表面粗糙度的影响。     

铝合金7050-T7451直角切削表面的残余应力研究

采用单因素直角切削试验,对硬质合金刀具切削铝合金7050-T7451加工过程中形成的已加工表面残余应力进行了研究。使用X射线衍射应力测试技术对残余应力进行测量,得到了不同切削参数对应的残余应力值。通过考虑刃口半径的存在,阐述了已加工表面残余拉应力和压应力的产生机理,同时分析了切削速度、切削深度等参数对残余应力值的影响规律。