مجله مهندسی ساخت و تولید ایران
سال نهم شماره 5 (امرداد 1401)

In the process of producing a part with the help of computer aided manufacturing, the required information is created for the workpieces whose design model is specified. To prepare machining instructions, the design information is expressed in a pattern called a feature. In this research an advanced artificial intelligence system has been introduced to identify machining features with the help of deep learning method. The proposed method has been prepared with the help of two-dimensional convolutional networks in deep learning. It can identify machining features from the image of a workpiece. The innovations of this research, in addition to introducing a powerful practical and new method for automatic machining features recognition in the field of computer aided process planning, is identifying features that have geometric interference in a workpiece. The previous methods of automatic machining features recognitions have not been able to solve this problem. Furthermore, the lack of need for different CAD output files and the use of an image of a workpiece to identify machining features are the capabilities of the system introduced in this research. Other capabilities of the proposed method are the ability to identify machining features with different image formats such as image with wire frame format, constructive solid geometry format, image of workpiece with different materials and taken with ordinary cameras such as mobile cellphone camera and other imaging devices. The accuracy of detecting machining features in the image of a workpiece is measured %88 and detection error is measured 0.1 using proposed method.

Based on the review of the previous researches, more than 50% of the cost of ceramic parts is related to machining costs, about silicon nitride (Si3N4), which is one of the most important engineering ceramics, while up to 80% has been reported. This ceramic has a combination of desirable properties such as wear and corrosion resistance and high hardness. Due to the high tool wear in machining process, the use of traditional methods is not appropriate. The electrical discharging machining process is a method that can machined all conductive materials without regard to mechanical and metallurgical properties, but machining of non-conducting ceramics such as silicon nitride is not normally possible by electrical discharging machining process. Therefore, in this research, the assisted electrode method has been used to perform the electrical discharge machining of silicon nitride ceramics. After preparing ceramic samples, copper-carbon bilayer and single copper layer were coating on the Si3N4 and they were successfully machined. In order to further examine the machined surface, imaging was performed by SEM. The results show that an increase in material removal rate in two-layer coating compared to single-layer coating. Also, after finishing machining process, EDX analysis was performed from the surface of ceramic workpiece, which indicates the presence of carbon and copper elements in the machined surface. In addition, the copper tool wear ratio in two-layer coating is less than that of single-layer coating.

High-speed turbine aero engines should be able to perform reliably and work in different flight regimes. Choosing the type of bearing and its design to ensure the performance of the rotating part of these engines in all working conditions is of particular importance Conventional rolling and fluid film bearings are not able to adjust their dynamic behavior in response to changes in the working conditions of the system. Tilting pad journal bearing (TPJB) can eliminate axial vibrations by compensating for misalignment, adapting to speed changes and active damping, and cause stability of operation and reduction of oil film instability. In the design of this type of bearings, the loading method, preload, length-to-diameter ratio, vertical force and starting torque, hardness and equivalent damping, and increase in oil temperature are important. In this research, a bearing sample for a shaft with a specific diameter was designed and manufactured and tested according to the requirements. In order to evaluate, tests are performed at different speeds and the results of the tests are expressed. The results show that while the Shaft moves smoothly and without vibration up to 13000 rpm, the lubrication is in the hydrodynamic range. With the initial parameters including Summerfield 13.6, temperature 23.5oC, 3570 rpm and viscosity 0.034 Pa.s, with the increase in temperature to a ratio of 1.4, while reducing the viscosity ratio to 0.62 and reducing the number bearing characteristics to 0.67, Summerfield number is also reduced. The extracted diagrams show the correct design of the intended bearing.

This paper aims to investigate the effect of the amount of calcium carbonate as foaming agent on the physical and mechanical properties of LM13 aluminum foam. Aluminum alloy LM13 foams have been made using calcium carbonate (CaCO3) as foaming agent and calcium metal (Ca) as stabilizing particles with densities from 0.3 to 0.5 gr/cm3 (relative density from 0.12 to 0.18) and the pores size from 0.25 to 0.92 mm. The effects of the amount of foaming agent on the size of the pores, the minimum thickness of the walls and the density have been evaluated. Furthermore, the mechanical behavior of foams has been investigated using uniaxial compression test. The influences of the amount of foaming agent on compressive strength, elastic characteristics and energy absorption capacity of foams have been investigated. According to the obtained results, the use of more foaming agent leads to the production of foams with larger average pores size and less density. Also, increasing the amount of foaming agent reduces the compressive strength of foams in the uniaxial compression test and their energy absorption capacity.

Additive manufacturing is a new type of manufacturing process which is used for the fabrication of special parts in a minimum possible time. Unlike the machining processes in which the part is prepared by material removal, the parts are fabricated in additive manufacturing by adding a new layer to old printed layers. In this article, the tensile strength of printed specimens from ABS by Fused Filament Fabrication (FFF) will be evaluated. Size, in-fill density, and the print pattern are three process parameters that will be investigated. Three different size samples, five different in-fill density samples, and two samples with different patterns are printed and the stress-strain behavior of prepared samples was compared. The tensile test results show that the tensile strength of samples decreases by increasing the sample size. Also, by decreasing the in-fill density, the tensile load of samples and elongation decreases, and a considerable difference between the 100% in-fill density and other samples are observed. By comparing the ratio of maximum force to the mass of samples it was observed that this ratio is almost constant for non-solid samples but this ratio is 25% higher for the solid (100% in-fill density) sample compared to the non-solid samples. The strength of the samples printed by the normal pattern is 13.9 % higher than the sample produced with concentric profiles. The failure strain of the sample produced with concentric profiles reduces by about 48% compared to samples printed by the normal pattern.

One of the most significant and applicable machining processes in surgeries and medical engineering is the bone drilling process. In this process, it is intended to minimize the axial force on the bone tissue during surgery. To reduce force, different methods have been considered; including the use of a variety of lubricants, ultrasonic oscillations, material replacement, tool geometry, and also the use of coated tools. The purpose of this paper is to investigate the effect of a specific type of nano coating on steel tool, and to investigate the effect of effective input parameters on force behavior in orthopedic drilling with medical requirements in mind. In this study, the polymeric material of poly-methyl-meta-carylate (PMMA), which has similar properties to the bone, was selected; and by creating titanium nitride nano coating on the tool, the effect of tool rotational speed, feed rate, and the tool diameter on the drilling process force have been extracted using the design of experiment by the response surface method, modeling and second-order linear regression equation governing the model. The optimum values of each input parameter are also presented in order to achieve the minimum and the best amount of force created during orthopedic drilling. The results show that the creation of titanium nitride nano coating reduces the force by 40 percent. Also, the axial force with the maximum cutting speed, the minimum feed rate, and in the tools with smaller diameters has been significantly reduced.