جستجوی مقالات مرتبط با کلیدواژه « tool wear » در نشریات گروه « مکانیک »

This research investigates tool wear, elemental analysis (EDAX) on the machined surface, surface roughness, microhardness and microstructural changes in the cross-section of milled 304L stainless steel samples under dry and Minimum quantity lubrication (MQL) methods. The MQL process was able to improve the surface roughness for all milling parameters from 17% to 41% compared to the corresponding dry conditions. In dry machining, defects such as built up edge, severe flank wear and tool chipping were created. In MQL mode, these defects were significantly reduced and tool chipping was almost eliminated. By increase of cutting speed and depth, the surface hardness has increased. Compared to the dry method, the MQL reduces the hardness values and hardened depth below the machined surface. According to EDAX analysis on dry and MQL machined surfaces, applying the roughest cutting parameters, it was determined that no change of chemical elements occurred on machined surfaces. Increasing cutting parameters or dry machining causes the plastic deformation to intensify, the microstructure is flattened and the microstructure grains are compressed in the vicinity of the machined surface. The maximum reduction in thickness of deformed layer in MQL compared to dry method is 39%. For each milling sample, there is a direct relationship between the hardened depth and thickness of the corresponding microstructurally deformed layer.

Currently, dissimilar metal joining processes are receiving considerable attention in various industries. The objective is to create composite structures that are both high-strength and lightweight, ultimately reducing the weight of the final product. Researchers have recently proposed friction drilling as a new method for creating joints between dissimilar metal sheets. This innovative technique offers potential advantages in achieving the desired outcomes. In this process, metal sheets are placed on top of each other and simultaneously subjected to friction drilling. As a result, this process not only creates an effective space for tapping but also establishes a frictional joint between the two sheets. Research has shown that preheating up to 350°C can have desirable effects on reducing the gap between the two sheets in the vicinity of the created joint between aluminum and stainless steel using the above-mentioned method. In the upcoming work, the effect of preheating on tool wear in simultaneous friction drilling of aluminum sheet AA6061T6 and stainless steel AISI304L using a tungsten carbide drilling tool has been experimentally analyzed, and the findings indicate that increasing the preheating temperature up to 350°C leads to a 13.77% increase in tool adhesive wear and a 0.46% increase in tool abrasive wear.

Today, the machining and milling of composites is of great importance; Because composites are used in various sectors and have found great efficiency in various industries. Considering this, in this article, in order to save the cost of milling composites, the effectiveness of various parameters that affect the cutting force and tool wear, including spindle speed (rpm), feed rate (mm/rev), cutting depth (mm) and percentage of sic, has been discussed; To minimize tool wear and cutting force by creating optimal conditions. Performing a sensitivity analysis according to the regression equations of cutting force and tool wear has shown that spindle speed with 63% and the percentage of composite silicon carbide with 22% have the greatest effect on tool wear and depth of cut with 47% and advance with 23% have the greatest effect on cutting force.

The ability to predict tool wear during machining is a very important part of diagnosis, which makes it possible to replace the tool at the appropriate time. Therefore, in this research, the artificial neural network approach was used to predict tool wear. First, hardened steel 4140 was turned with uncoated cemented carbide tool TCMW 16T304 H13A and with input parameters including cutting speed, feed rate and machining time in three different levels and with constant cutting depth, and the amount of tool wear was measured. And the experimental test results were used to train and validate the artificial neural network. The optimal neural network architecture was obtained with 3 nodes in the input layer, two hidden layers with 12 and 36 nodes in the first and second hidden layers, and 1 node in the output layer to predict tool wear. The prediction values of the artificial neural network model were compared with the experimental results and the average error percentage of the validation data was calculated as 3.32%.

Due to the significant increase in demand for materials with new capabilities, the use of composite materials is increasing. These materials have unique properties such as high wear resistance and a high strength-to-weight ratio, and are used by engineers in various industries, particularly in the aerospace and automotive sectors. Due to the metallic nature of these materials, the machining process is an integral part in achieving the shape and properties of the final product. Among composite materials, aluminum-based composites are the most widely used in industry. In this study, a methodical was conducted, study including statistical modeling using the response surface method and deriving regression equations of the effect of spindle rotation speed, feed rate, and depth of cut on surface roughness, metal removal rate, and tool wear during machining of A359/B4C/Al2O3 matrix aluminum composite. It was found that an increase in spindle rotation speed, feed rate, and cutting depth increased metal removal. The best combination of parameters that was found to simultaneously minimize the surface roughness and maximize the metal removal rate and minimize flank wear was a spindle speed of 600 rpm, a feed rate of 0.075 mm/rev, and a cutting depth of 0.20 mm

In this research, the effect of parameters of cutting speed, feed rate and machining time at constant cutting depth on tool wear and its effect on the surface roughness of hardened steel 4140 and machining forces were investigated. First, 4140 steel was prepared and its hardness was increased to 45 HRC under heat treatment, and then the TCMW 16T304 H13A tool was prepared from uncoated cemented carbide for machining. The design of the experiments was carried out in a full factorial manner. The analysis of the results was done from the analysis of variance test and the graphs related to the experimental results, based on these results, the advance rate had the greatest effect on the surface roughness and machining shear force, and the machining time had the greatest effect on the machining advance force and Cutting speed also had the greatest effect on tool wear. The highest amount of tool wear was equal to 0.89 mm and the lowest amount of tool wear was equal to 0.41 mm. The best surface quality was measured as 0.372 μm and the highest surface roughness was measured as 1.154 μm. The maximum shear force was 172.7 N and the minimum shear force was 54.2 N. The maximum forward force was equal to 156.59 N and the minimum forward force was equal to 45.86 N.

Advances in many engineering fields depend on materials with appropriate properties. The use of metal-matrix composites is rapidly growing as a suitable alternative to conventional materials due to their strength-to-weight ratio, resistance to wear and creep, etc. Machining of metal-based composites is a difficult task due to the presence of very abrasive reinforcing particles in its based metal. Therefore, it is necessary to investigate the factors affecting these materials. In this research, a methodical study has been conducted to investigate the effect of the parameters of spindle  speed, feed rate, depth of cut and the percentage of reinforcing particles on the behavior of cutting force and tool wear using experimental design methods, modeling and statistical sensitivity analysis methods. . Detailed analysis of behaviors has been done by providing statistical regression equations and optimization by Deringer's method and E-Fast-Sensitivity Analysis. According to the obtained results, the cutting depth had the greatest effect on the machining force. Also, cutting speed with 77%, advance rate with 9% percent and cutting depth and weight percent of reinforcing particles with 7% percent are other parameters affecting tool wear in the milling process of this composite.

In this research, using R410a coolant in cooling the cutting edge of the tool and comparing it with the traditional fluid of soapy water, the life of the tool and the wear rate of the cutting edge of the tool were investigated. The wear rate of high speed steel (HSS) tool in steel cutting (ck45) 1045 at cutting speeds of 15, 25, 40, and 55 meters per minute, cutting depths of 0.5, 1, and 1.5 mm and feed rate of 0.05, 0.12, and 0.2 mm /rev was investigated in two modes of liquid cooling, soapy water and R410a coolant. The obtained results show that cooling with R410a coolant, due to its high cooling power and better control of the temperature of the cutting area compared to the soapy water fluid in the machining process, has reduced the amount of tool wear and can be used as one of the suitable cooling fluids. Based on the minimum amount of tool wear in different conditions, by using R410a coolant, the cutting speed can be increased by 60% from 25 m/min to 40 m/min. Also, in the most optimal mode, the amount of tool wear is improved up to 20 times, and at a cutting speed of 40/min, the cutting depth is 1 mm and the feed rate is reduced from 400 to 20 micrometers.

In ultrasonic vibration-assisted turning, an ultrasonic vibration is added to the tool, which leads to the periodical disengagement of the tool and the work-piece. In this research, an experimental study of ultrasonic vibration-assisted turning and conventional turning on Ti6Al4V Titanium alloy is conducted. First, by analyzing different parameters, four parameters are selected as the main affecting input parameters (cutting speed, feed rate, depth of cut, and ultrasonic vibration), and the effects of these four parameters are studied on two output parameters, namely tool wear and surface roughness. After the experimental tests, a statistical analysis is performed on the results and a neural network model is developed to predict the tool wear and surface roughness. The results show that the developed neural network model has a good agreement with the experimental results. In all experiments using ultrasonic vibrations, the tool wear and surface roughness were lower in comparison with the conventional turning. The cause of the tool wear and surface roughness reduction in ultrasonic mode are reducing the average forces applied to the tool, the alternative disengagement between the tool and the workpiece and increased dynamic stability of the process.

Wear, friction and lubricant are important issues in all disciplines, including in turning. Normally, lubricant is used to reduce the temperature of the tool and also to reduce the friction between the part and the tool. So far, many studies have been done on lubricant optimization by changing its structure, for example by adding nanoparticles to the lubricant. In this article, with a new approach, the effect of creating a surface pattern on the accuracy of the lathe has been studied. More precisely, the effect of holes created by laser engraving on the friction behavior and the formation of the fluid layer in different states were investigated by numerical analysis. In general, the amount of load as well as the speed of chipping is an influencing parameter on the amount of friction. Here, by keeping these two parameters constant, the effect of the number, depth and size of the surface pattern was investigated.

Tool wear has a significant influence on the turning process. Investigations on tool wear monitoring through various methods and sensors have been widely conducted to determine and predict the tool wear. In this study sound generation mechanisms during turning process have been investigated comprehensively and three sound generation sources have been determined and distinguished. Sound generation mechanisms which originated from tool vibration, deformation in the workpiece and vibration at the contact zones (friction), have been investigated and frequency range of the sound generated through each mechanism has been determined. It has been shown that these mechanisms produce sound in 10s hertz, kilohertz and megahertz respectively. Then the mechanism which is appropriate for tool condition monitoring has been studied and suggested. Then the relation between the sound generation mechanisms and chip formation has been studied during machining. Hence, a deep understanding about the machining process has been brought out. Findings could lead to an effective approach to monitoring the machining process, not only using mathematical signal processing methods, but also through a physical comprehension background. Experimental studies have been conducted to evaluate developed theories and models. Experimental results have shown effectiveness of the proposed approach.

AISI630 is a stainless steel that is strengthened by precipitation-hardening mechanism. This steel has high hardness and low thermal conductivity, has made it one of the difficult-to-cut materials. These two factors have its machining is associated with high tool wear and poor workpiece surface quality. In this study, the conventional and hot turning of AISI630 hardened stainless steel have been investigated. To determine the effect of machining parameters on tool wear, a hot turning process up to a preheating temperature of 400°C was performed. Turning was conducted at three feed rates and three levels of cutting speed using PVD-(Ti,Al)N/(Al,Cr)2O3 coated carbide tools. Tool flank wear and wear mechanisms have been studied in different cutting conditions as well as different preheating temperatures using SEM microscope. Experimental results showed that the lowest wear on the free surface of the tool was obtained by hot turning at 300 °C. Hot turning at this temperature reduced the flank wear by 33%. Observation of the worn surface of the tools showed that the tool wear mechanism in hot turning and conventional turning is of the type of abrasive wear and adhesive wear.Moreover, at each cutting speed and feed, with increasing the workpiece initial temperature up to 400°C, the surface roughness decreases. The optimal values of temperature, cutting speed and feed rate were obtained using Minitab software with the aim of reducing tool wear and surface roughness.

The high amount of nitrogen in the composition of AISI 440C stainless steel reduces the machinability of this steel due to the increase in hardness and generates high heat at the cutting edge and the chip-tool contact area. The use of new cooling technologies such as cryogenic machining using liquid nitrogen LN2, leads to increase the life of the tool and improve the cutting speed compared to other common methods. In this research, the effect of cryogenic machining is investigated on roughness and hardness of AISI 440C stainless steel. The results showed that using cryogenic machining, the surface roughness of AISI 440C stainless steel was significantly reduced even at high feed rate. The morphology of the chips showed that with the use of cryogenic machining, the surface burn and the accumulation of materials on the inner surface of the chips has been significantly reduced. In this study, it was found that in cryogenic machining, the tool wear pattern is the erosion pit on the chip surface and has increased the tool life by 400% compared to the dry machining.

Work piece surface roughness as one of the most important output parameters of the machining process has a significant impact on the final cost of production. Parameters such as cutting edge sharpness, vibration and cutting tool wear have a great effect on the surface roughness of the work piece. In this paper, the effect of cutting tool cryogenic treatment on tool wear and work piece surface quality in different machining parameters (cutting speed, feed rate and depth of cut) was investigated and compared with dry and conventional (wet) turning of AISI 304 austenitic stainless steel. The Taguchi method for design of experiments and the signal-to-noise ratio method for analysis of results were used. According to the obtained results, the wear of the cryogenic treated tool was reduced compared to the cutting tool in dry and conventional machining modes. The surface roughness of the work piece in machining with the cryogenic treated tool is less than in the dry and conventional machining modes due to reduced tool wear and preserving the sharpness of the cutting edge of the tool.

Ceramic Matrix Composites (CMCs) are designed to overcome the main drawbacks of monolithic ceramics, especially their brittleness, in high-performance and safety-critical applications. Owing to the inherent properties of CMCs, especially heterogeneous structure, anisotropic thermal and mechanical behavior, and the hard nature of fibers or matrix, the machining process becomes extremely challenging as the generated surface suffers from undesirable quality. Taking the high hardness of ceramic matrix into account, grinding with diamond abrasives is the only efficient way for machining of CMC materials. The aim of this paper was to study the influence of grinding parameters (cutting speed, feed speed, and depth of cut) and different cooling-lubrication conditions (i.e. dry, fluid, and minimum quantity lubrication) on surface roughness, process efficiency, and tool wear. The results indicated that MQL leads to the best results in terms of surface quality and process performance. Furthermore, increasing of cutting speed and feed speed decreased and increased surface roughness, respectively, while depth of cut had an insignificant effect on the roughness value. Regarding the experimental results, four machining strategies considering quality, productivity, and efficiency criteria were developed. Eventually, the material removal mechanism was evaluated using SEM photos, indicating that brittle fracture is the dominant removal behavior of CMC materials.

Increasing workpiece surface quality and reducing tool wear are always the most important ones in machining purposes. There are basic challenges to achieve optimum conditions for workpiece surface and tool life in different machining operations of austenitic stainless steel 304L due to low thermal conductivity and creating high temperatures at the cutting zone. Applying conventional cooling methods such as flood techniques does not usually provide desirable control of machining temperature. Also, their use often creates environmental problems. Recently, the cryogenic cooling process has been considered by researchers to reduce these problems in various machining methods. In this research, turning of 304L stainless steel using cryogenic cooling of CO2 have been studied to investigate the effect of flow rate and fluid spraying method on workpiece surface roughness and tool wear. For this purpose, the tool-workpiece contact zone has been cooled in five different methods of CO2 fluid spraying according to the number and position of the spraying nozzles (Up1, Up2, Down, Up1-Down, Up2-Down) and three different flow rates (12, 18 and 24 l/min). The minimum main flank wear of the tool was achieved in the Up1 cooling method and 18 l/min flow rate and the minimum workpiece surface roughness was achieved in the Up1 cooling method and 12 l/min flow rate. Regarding economic considerations to reduce the consumption of spraying flow of CO2 fluid and achieving the minimum main flank wear of the tool, built-up edge and workpiece surface roughness, the optimum spraying method and flow rate were obtained as Up1 and 12 l/min, respectively.