مجله مهندسی ساخت و تولید ایران
سال پنجم شماره 3 (پاییز 1397)

Nickel-based alloys are largely used in aerospace, power generation and petrochemical industries. Machining of these alloys is usually accompanied with high cutting force and temperature and low surface quality. In order to avoid these limitations, small values of cutting parameters are used in machining of nickel-based alloys that significantly decrease the productivity. In this paper, the effects of cutting speed, feed rate and depth of cut on the surface roughness in dry turning of nickel-based super alloy Inconel 600 by using carbide tool in finishing range have been experimentally investigated. Full factorial design of experiments was used and totally 48 tests were done. Results of the analysis of variance showed that feed rate 69%, depth of cut 6% and cutting speed 2% affects on surface roughness of Inconel 600. In addition to measuring the surface roughness, chip removal rate was calculated for each test and then, for achieving to minimum surface roughness and maximum chip removal rate at the same time, the optimal machining parameters have been achieved by using neural network and imperialist competitive optimization algorithm. By using this algorithm, several levels of optimum cutting parameters are set and a process planner according to the required surface roughness and material removal rate can use these cutting parameters.

In this study, the mechanical, tribological and corrosion properties of Al6061 after different pass number of FSP were investigated. To study the microstructure of samples, optical microscopy (OM) and scanning electron microscopy (SEM) were used. Optical microscopy images showed that the average grain size of samples significantly decreased after FSP. Furthermore, results showed that using of FSP generally leads to the reduction of microhardness values, compared to the base metal. It can be deuced that there are various strengthening and weakening mechanisms governing on the mechanical properties of FSPed aluminum. In consistent with microhardness findings, corrosion results showed that FSP has negative effects on the corrosion resistance of Al6061. In other words, the polarization plots of FSPed samples shifted to the more negative potentials and higher current densities. Wear results are in good agreement with what was mentioned. In this regard, wear weight loss of two pass FSPed aluminum was about 3.5 times higher than that for base metal.

Free-form surfaces are usually described using the relationships of parametric surfaces such as Bezier, B-Spline and NURBS. The computer-aided design systems use NURBS to describe complex (complicated) geometries. Free-form surfaces known as complex (complicated) surfaces are widely used in a variety of industries such as ship-building and molding, inspection of these surfaces is therefore of high importance (very important). Considering that measured free-form surfaces and design models are located in two different coordinate systems, finding the similarity of free-form surfaces and placing them in an identical coordinates system is necessary to compare these surfaces, this process is called localization. This paper introduces a feature and curvature based method for the automatic localization and comparison of free-form surfaces for inspection with coordinate measuring machine (CMM). This method localizes the measurement surface to the design model through two steps. The first step is general localization which is accomplished based on the relation and similarity between curvatures of free-form surfaces and zoning these surfaces to concave, convex and saddle areas. The second step is fine localization based on genetic algorithm which considers correspondence in the form of point to point. The simulation results show that the localization accuracy of the proposed method for the 50 × 50 mm aluminum workpiece of was about 0.02 mm, which is 56 percent less than the value obtained from the iterative closest point method.

Shape memory polymers (SMPs) have the ability to store the deformation and recover the original shape. Shape memory behavior is associated with two features: shape recovery and stress recovery. Full shape recovery and increase the stress recovery value are the challenges ahead of the SMPs. In this paper, the polyurethane and polycaprolactone (PCL) were blended. The thermal stimulated SMPs ware fabricated by melt mixing and solution mixing method and thermo-viscoelastic behavior of SMPs ware analyzed. Two types of polyurethanes with the same chemical structure were used as the hard phase and polycaprolactone was used as the soft phase in SMP blend. The results show that the solution mixing method has advantages such as proper appearance without defect, free from cracks and cavities, higher storage and loss modulus values without fluctuations over temperature. The blend of PCL with low hardness polyurethane one showed better shape memory behavior. In order to investigate the shape memory effect, shape recovery test was carried out with 25% pre-strain at 60°C. Also, the stress recovery was carried out by 25% pre-strain at different temperatures (60°C, 45°C and 37°C) on the samples made by solution method. The stress-recovery function was highly affected by the deformation temperature. The maximum stress and maximum recovery rate were observed in the sample with a deformation temperature of 45°C. A stent was made by the solution method and its shape recovery results showed that recovery was done completely in less than 0.5 seconds at 60°C.

The main purpose of this study is optimization of resistance spot welding of AZ61 Mg alloy to achieve maximum nugget size and minimum tensile residual stresses in welding area. Since the stability and strength of a welded structure is strongly dependent on the nugget size and the residual stresses, an integrated artificial neural networks and genetic algorithm is utilized to optimize the welding parameters. In this study, the resistance spot welding process is simulated by a 2D fully coupled structural-electrical-thermal finite element model. The finite element model is developed to predict of the nugget size and the residual stresses in the welding area. In order to validate the FE model, the results are compared with the obtained results from the experimental tests. The results show that the FE model has a good agreement with the experimental tests. The input parameters for optimization are: electrical current, welding time and electrode force. The results show that the integrated optimization algorithm is successful in determining the optimized welding parameters. Based on the optimization results, the maximum nugget size 6.33 mm and the minimum tensile residual stress 228 MPa are achievable by using 16kA, 16 Cycles and 848 N as current, welding time and electrode force respectively.

Fourier series is a general technique for particle shape analysis. Lower order Fourier descriptors provide measures of roundness, elongation, asymmetry, triangularity and squareness. Higher order descriptors provide textural information like surface roughness. In this paper, firstly the captured image of sands grains is pre-processed to improving the quality of image in terms of edge sharpness, color and other image factors. Then, the sand shape characteristics is extracted using the Fourier series from the output Image of the previous step. In this work, two applications of the Fourier series in particle shape analysis are considered. First, the measurement of sand shape characteristics like elongation and triangularity which is important factors in cement mixture, plaster, other building applications and road construction. Secondly, the sizes of sand grains are also measured and compared to standardized classes used for each above mentioned applications to show the deviation from the standard specifies. The comparison between measured data from machine vision technique and conventional standard method show the efficiency of this new visual inspection system. The shape characteristics are not considered in conventional standard and only the dimensional measurement is developed. Therefore, using the machine vision method along with the Fourier series improves the current standard in terms of fast measuring speed, low cost measurement and adding the shape characteristics as well as the size of sands.