جستجوی مقالات مرتبط با کلیدواژه « Surface Roughness » در نشریات گروه « مکانیک »

The milling process is widely used in the manufacturing industry to shape complex geometric parts. Considering the flexibility of the cutting process and the various variables involved, process optimization has become a key issue in achieving higher productivity and quality. To optimize the process planning, it is important to choose a suitable machining strategy. Implementation and selection of tool path strategies and orientations are very important in the machining process, especially in the aerospace and molding industries. The right choice can lead to significant savings in machining time, improvement of work-piece surface quality, and improvement in tool life, thus leading to overall cost reduction and higher productivity. Therefore, this article aims to identify the best strategy in terms of surface roughness and milling time. In this article, Shallow's strategy has been investigated, and the milling of its finishing stage has been studied and compared with three strategies of the milling process, including raster, 3D offset, and raster flat. In this article, the comparison of the strategies in the Powermill software and with the flat-head finger mill, which can grind the floor and the wall simultaneously, has been done. Tool-cutting parameters were considered constant for all tested strategies. Machining quality was evaluated by comparing surface roughness, surface Topography, and dimension control parameters. The results indicate that the Shallow machining strategy has the lowest surface roughness and the best surface quality, and the raster strategy has the highest surface roughness and the worst surface quality in this test.

Surface roughness is one of the most important characteristics in nanomachining products. One of the parameters that always has a great impact on the surface quality is the forces caused by the nanocutting process. In this research, using molecular dynamics simulation in LAMMPS software, the process of dynamic nano ploughing of single-crystal copper workpiece by a diamond tool is investigated. The effect of parameters of dynamic nano- ploughing process such as depth of cut, amplitude and frequency of cutting tool vibration on cutting force and surface roughness has been investigated by calculating average roughness. Also, in order to more closely examine the effect of parameters and their interaction on each other, Taguchi method has been used to design experiments. The simulation results show that the characteristics of cutting depth, amplitude and frequency of cutting tool vibration have the greatest effect on surface smoothness and cutting forces, respectively. Based on the presented results, it has been determined that the surface roughness can be improved in different machining conditions based on the selection of parameters, and it is necessary to check their conditions together well before selecting these parameters. Also, using Taguchi method, the optimal values of dynamic ploughing parameters were obtained to achieve the best surface smoothness and the lowest cutting force in certain dimensions as described by DOC=2.5 , R=0.1 and ω=50 KHz.

Nowadays, due to the increasing need of various military, aerospace, automotive, etc. industries for materials with high strength-to-weight ratio, good resistance to wear and fatigue, etc. the use of composite materials, especially metal-based composites, has increased significantly. Machining to achieve high dimensional accuracy is an integral part of the production process of products made with metal-based composites. Due to the presence of reinforcing materials such as silicon carbide, etc. the machining of this category of materials always faces many challenges, including tool wear, increased machining forces, decreased surface quality, etc. Therefore, it is to study the parameters affecting the machining of metal composites. Many studies have been done in this field by different researchers. In this article, by reviewing the most important articles published in this field, comprehensive and at the same time summary information on the influencing factors in conventional machining processes such as turning, milling, etc. or non- conventional machining processes such as electrical discharge, electrochemical machining, etc. has been tried to be available to the readers. Also, the performance of different types of tools during the machining of metal composites was investigated. In the end, the existing gaps and new and studyable topics for researchers were pointed out.

The development of rapid prototyping methods has been very drastic in recent years. One of these methods, with a nature similar to sheet-forming processes, is the incremental forming method. In the last two decades, this technique has attracted much attention in industrial applications. The incremental forming process has been able to play a major role in advancing industrial projects in the production of low-volume prototypes. This process is a suitable alternative to conventional forming processes in the single production of conical geometries because of the low cost of machinery, equipment, and tools. In this paper, the two-point incremental forming of conical parts by three multi-point matrix designs, including single, double, and three-step cylinders, were investigated. For this purpose, the feed rate (400-1000 mm/min) and the penetration step of the tool (0.5-1.1 mm) were investigated in three levels to form the aluminum sheets with a thickness of 0.5 mm. In the following, the effect of the input parameters on the limiting height of the formed specimens, thickness distribution, surface roughness, and geometric accuracy of longitudinal cut specimens was assessed. According to the results, using the multi-point matrixes, despite increasing the final geometric accuracy, friction was reduced compared to the conical matrix. Using a two-step matrix, deeper pieces were formed by increasing the formability of the sheet, in which the average height was improved by an average of 12%. However, no significant change was observed in the roughness of the samples formed by all three types of matrixes. Therefore, the design of the proposed matrix had almost no tangible effect on the final surface roughness output. From the view of geometric accuracy, the matrix design with three steps created the highest geometric accuracy, as well as the least deviation relative to the planned path.

Waspaloy is a type of nickel-based superalloy that is mainly used in aircraft turbine parts, compressor disks, shafts, and turbine parts. Waspaloy, like many nickel base superalloys, is difficult to machine at room temperature (conventional turning). In this paper, the cutting and feeding forces and cutting temperature have been evaluated by changing rotational speed, feed rate and constant depth of cut, in the dry oblique turning process of Waspaloy. The workpiece's diameter and hardness were 25 mm and 385±10 Vickers, respectively. In order to investigate of the cutting force, temperature and the surface roughness, a full factorial design experiment was used, and a regression model of the influencing factors was presented. Moreover, the surfaces roughness and micro hardness of the machined parts were evaluated. The results showed that the hardness on the surface of the workpiece increases with the increase of the cutting depth and the feed rate.

In this paper, tool and workpiece wear ratio and surface roughness in the removal process of Ti-6Al-4V by spark are modeled using fuzzy algorithm. In the machining process using a spark, a copper electrode is used as a tool and equal channel angular pressing (ECAP) process is applied to the tool. In this combined modelling the number of ECAP passes, current, spark presence time and spark absence time are used as input parameters. The evaluation and validation results of fuzzy modeling, using experimental data, show that the fuzzy algorithm is capable of modeling and establishing relationships between response variables based on input parameters with high accuracy. Therefore, by using this method, one can easily predict the response variables and avoid the need of conducting experiments that require spending a lot of time and cost.

When working with hardened materials, it's important to control and optimize the surface roughness and machining force. To achieve this, we can use intelligent methods that are based on prediction and optimization models. In this study, an artificial neural network was used to evaluate the surface roughness and machining force of hardened steel 4140 by analyzing cutting speed, feed rate, and machining time. A full factorial method was used to carry out 27 experiments, and an uncoated cemented carbide tool TCMW 16T304 H13A was used to measure surface roughness and machining force during turning. An artificial neural network model with two hidden layers was selected as the optimal architecture for separately predicting surface roughness and machining force. The predicted values were then compared with the experimental results, and the average error percentage for validation data was calculated as 4.25% for surface roughness and 5.11% for machining force. Finally, the optimal cutting parameters were selected to minimize surface roughness and machining force.

Endmilling is a type of machining tool for chipping the surfaces of parts, which has received attention due to its wide application in industries such as molding. Therefore, today, the need of the industry to find the optimal parameters of the process is felt so that the quality of the desired surface can be achieved. In general, the selection of effective parameters in any milling process significantly affects the surface quality of a finished part. In this research, using E-fast statistical sensitivity analysis method, the simultaneous influence of input parameters including spindle speed, depth of cut, and feed rate on the output parameter of surface roughness for the samples has been investigated quantitatively. Machining experiments have been carried out under different cutting parameters as defined in steady state conditions for the milling tool. surface roughness and vibration rate of machining with non-linear quadratic forms; It has been modeled based on the cutoff parameters and its interactions through several regression analysis methods. The results of this research showed that the spindle speed time parameter is known as the most influential parameter on the surface roughness with 67% influence. It was also observed that the feed rate parameter with 30% effect of cutting depth with 3% are known as the second and third influencing parameters on surface roughness.

Metal composites have received attention from various industries due to their excellent properties, such as a high strength-to-weight ratio and wear resistance. However, due to the presence of hard and abrasive particles, the challenges have always faced machining. Therefore, studying the effective parameters in the machining of these materials is very important. Drilling is one of the most common and widely used methods in the industry. In this study, the Response Surface Method (RSM) and Central Composite Design (CCD) were used to model, optimize, and analyze the effects of machining parameters. Aluminum composite with AL356 alloy reinforced with 25 micrometers of silicon carbide and 45 micrometers of mica mineral, as well as a 6 mm diameter carbide drill, were used for the experiments. According to the results, with an increase in the drilling speed, the drilling forces increased and the surface roughness decreased. Additionally, increasing the feed rate increased forces and surface roughness. With an increase in the volume fraction of SiC reinforcing particles, the drilling forces and surface roughness increased and decreased, respectively. By analyzing the data obtained from the experiments, the best combination of values was found to minimize the surface roughness and axial force at the same time. The best combination of parameters was found to be: a spindle speed of 1855 rpm, a feed rate of 50 mm/rev, and a weight percentage of 15% SiC

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.

Achieving optimal parameters in production processes is crucial in the military industry, as the products are highly complicated and resistant. Because there is no heat generation in the cutting area, abrasive water jet machining is a particularly popular procedure. This study looked into how input variables affected the abrasive water jet machining of rolled homogenous armour steel. The material removal rate, surface roughness, and Kerf angle regression equations were analyzed using the E-fast method of statistical sensitivity analysis. The findings demonstrated that the standoff distance, with a 74% impact, is the most effective parameter on the kerf angle, and the jet traversal speed, with a 95% and 50% impact on the material removal rate and surface roughness, respectively. In addition, pressure had the least effect on three variables of material removal rate, surface roughness and kerf angle.

The properties of metal-based composites, such as their high strength-to-weight ratio and good resistance to wear and fatigue, have caused a significant growth in their use in the aerospace, automotive, and aircraft industries. Magnesium-based composites have particularly attracted the attention of researchers in various fields, especially aerospace scientists, due to their lower density than other metal-based composite alloys such as titanium and aluminum. However, due to the presence of very abrasive reinforcing material in these materials, machining them is difficult and presents numerous challenges. Therefore, it to study the machining process of these is necessary composites and to examine the effect of the main turning parameters such as cutting speed, feed rate, and depth of cut on machining forces and surface roughness. Sobol's sensitivity analysis method was used for this purpose. Using this method, it was determined that the feed rate, cutting depth, and cutting speed have the greatest effect on the machining forces, respectively. Additionally, the feed rate has a greater effect on the surface roughness than the cutting depth and cutting speed. As the feed rate increases, the surface roughness and cutting forces increase.

The proper operation and quality of the finished product are highly dependent on the surface roughness of parts in a variety of industries. Among the most sophisticated techniques for reducing a part's surface roughness is the magnetorheological polishing procedure. This technique uses a magnetic field and rheological materials to improve the surface roughness of items. The parameters of turning radius, gap, machining time, magnetic pole rotation speed, and workpiece rotation speed have all been studied in the present research. By applying the Sobol method for statistical sensitivity analysis, the parameters have been examined via the surface roughness regression equation. According to the results, the most effective parameters are the workpiece's rotation speed (impact of 51%) and the magnetic pole's rotation speed (impact of approximately 21%). The next parameters to be considered are the machining gap (14% impact) and machining time (11% impact). With a 3% impact, the radius of gyration is thought to be the least important parameter in this process. This means that the time parameter's impact on this procedure can be neglected.