فهرست مطالب سعید خدایگان

This competitive commercial space forces designers and manufactures to produce and supply products with high quality and low prices at a desirable level of reliability. On the other hand, during the design and production process, engineers are always faced with uncertainty. In recent years, to encounter these uncertainties and guarantee the quality and reliability of a system subsequently, reliability-based robust design optimization (RBRDO) algorithms have been developed based on robust design optimization (RDO) and reliability-based optimization (RBDO). In practical engineering, uncertainties of some design parameters or variables are epistemic and only a few samples are available for designer. Generally, some of the RBRDO methods ignore the information in the design process. This approach can lead to an enormous error. Other RBRDO methods ignore this valuable information in the design process. This study, a comprehensive RBRDO framework is developed by combining Bayesian reliability analysis and dimensionality reduction method (DRM) using NSGA2-II multi-objective optimization algorithm. For verification of the proposed algorithm, an engineering example is selected and the effects of epistemic uncertainty on objectives are studied. Moreover, the results of the proposed approach are compared with other existing approaches at a specific case of available data about epistemic uncertainty.

The laser-assisted additive manufacturing based on the powder is an efficient layer manufacturing process that uses a high-energy laser for the fabrication of polymeric components. The thermal stresses of the laser arise from the thermal gradients generated by the laser and other parameters of the device. Reducing thermal gradients decreases the deformations in the part and increases the fabrication accuracy. The main aim of this paper is to determine the temperature parameters including the preheating temperature or the powder bed temperature, the ambient temperature, scanning power and spot diameter in such a way that the temperature gradient is minimized. The finite element modeling is performed for the selective laser sintering process for polyamide-12 powder. In this paper, thermal gradient by changing temperature parameters based on the temperature model of the finite element and Taguchi experimental design is optimized. In order to reach this aim, the finite element simulation of the selective laser sintering process is first carried out for polyamide-12 powder. In order to verify the simulations, the experimental test is performed by a selective laser sintering device and the obtained results are compared with the finite element model. Then, using the Taguchi method, experiments are designed at the different levels and optimal temperature parameters are obtained. According to obtained results, optimal parameters were obtained to minimize thermal gradients at 451K preheat temperatures, 359K ambient temperature, 10W laser power, and 0.5mm spot diameter.

Along with improvement of technology and need for access to energy resources, existence of pipelines such as gas, oil and water pipes is vital for our lives. These pipes will be eroded and damaged over time. With the prediction of the defects and tracking of pipeline paths, the probability of sudden damages is greatly reduced. In this paper, at first various non-destructive methods of monitoring the pipelines are investigated and it is shown that the laser method is the most comprehensive and non-destructive inspection method and then the background of the chosen method is examined. Also, the hardware aspect of the system and the proper layout of the laser sensors are determined on the system. After that a complete mathematical model and an algorithm is proposed for it which can be used to analyze the data obtained from the simulation of laser sampling creates image of the pipe internal surface and using this method identifies the defects found at the pipe surface. In the fourth section, a pipe with specific geometric deflection is examined based on the proposed method and algorithm and its results show the correctness of the proposed method.

Rapid prototyping (Additive manufacturing or 3D printing) is defined as the process that can build 3D physical part from the designed model in CAD software by joining materials directly. In the RP process, the orientation pattern of the part is one of the most important factors that significantly affect the product properties such as the build time, the surface roughness, the mechanical strength, and the amount of support material. The build time and the surface roughness are the more imperative criteria than others that can be considered to find the optimum orientation of parts. In this paper, two algorithms based on analytical and empirical optimization methods are presented to determine optimum part build orientation in order to minimize build time and surface roughness. To implement this method, the user's part is received in standard triangle language (STL) format. Then, using the geometric characteristics and type of part orientation, the build time and the average of surface roughness is calculated. In order to determine the optimum part build orientation, two analytical (NSGA-II method) and experimental (new and developed Taguchi method) optimization methods have been used. After introducing the steps of these two methods, in order to determine optimum part build orientation, the steps of these two proposed algorithms are implemented on a part as a case study and obtained results are compared and discussed.

Additive Manufacturing (AM) or 3D printing is a method to build parts by adding layer-upon-layer of material. The selective laser sintering (SLS) method is one of the most important methods of additive manufacturing processes. The low time and the variety of materials used to build the parts are major advantages of SLS method. The high quality of the product is one of the main goals in the additive manufacturing processes. The part warping is one of the factors that reduce the quality of the products which are built by the SLS process. The hatching patterns and scan algorithms in the SLS process are important factors that affect the product quality. In this paper, the effective parameters of the SLS processes such as the scan vector length and the number of offsets or contours, the laser power, the laser speed, and the hitching spacing are optimally determined to minimize the part warping of the product based on the finite element simulations and Taguchi method. For this reason, SLS process has been modeled on the SLS process. Then, to illustrate and validate the accuracy and efficiency of the proposed method, and the computational results are compared to the obtained results from the experimental tests Using SLS containing CO2 laser. Finally, using the Taguchi design of Experiments, the process parameters have been changed at different levels and optimal parameters have been obtained.

Because of increasing demands for using of rotating systems in high accuracy and high speed applications, in addition of specific condition of rotating systems, it is necessary to analyze these rotating systems characteristics. Tolerance analysis is a useful tool for estimating effects of dimensional and geometrical errors of effective parameters on functional characteristics in a mechanical system. Unlike other mechanical systems, in addition to the dimensional and geometrical errors, the accuracy of the rotary systems performance directly depend on the flexibility of parts and Non Repetitive Run-Out (NRRO) errors. In this paper, a new method is proposed for static and dynamic tolerance analysis of the rotary systems with the dimensional and geometrical errors, the flexibility effects, and the NRRO errors based on the tolerance zone model. First, using the small degrees of freedom concept, the dimensional and geometrical errors and the NRRO error are modeled in the tolerance zone. Then, based on a new strategy, the performance -assembly functions of the system for modeling the error propagation of the rotary system in the static and dynamic conditions are extracted. Then, using the proposed equations, sensitivities of the requirements such as the end of shaft position and the main natural frequency to tolerances are computed. To illustrate applicability of the proposed method, a rotary system is considered as a case study. Monte Carlo simulations are used for validation of the computational results from proposed method.

The orientation of part in the additive manufacturing process is one of the most important factors should be considered in the additive manufacturing process. In the additive manufacturing process, the part orientation factor can significantly affect the part properties such as the surface roughness, strength, the manufacturing time and amount of support materials. The manufacturing time is a key factor that can influence the total production cost. Therefore, to minimize the manufacturing time, the optimum orientation of parts should be determined. In this paper, a new method is introduced to estimate the built time of the parts through the additive manufacturing process. According to the proposed method, a practical equation is extracted to estimate the built time of the parts with related to the number of layers and amount of the support materials. The method is capable to estimate the built time of a part associated to the part orientations. The efficiency of the proposed method is demonstrated through a case study in two different type of orientation, and the computational results are compared with the obtained results from the simulations in MankatiUM V5.3 and Repetier-Host software. The average of proposed method relative error in the first type of orientation in comparison with MankatiUM and Repetier-Host software results are, respectively, 5 and 10 percent and for the second type of orientation are 7 and 8 percent. Moreover, calculation cost of proposed method is 140 and 100 times faster than MankatiUM and Repetier-Host software, respectively.

In sheet metal structures, due to high flexibility of the sheets, the dimensional and geometrical errors do considerably influence the assembly tolerances. 4n one hand, various stages of design, manufacturing and assembly of mechanical sets are involved in various factors such as dimensional, geometrical and material uncertainties. As a result, presenting a comprehensive model based on which propagation of the changes resulted from the uncertainties of the manufacturing processes and their relations with assembly tolerances could be approximated with a high accuracy seems necessary. In normal influence coefficients method, neglecting the contact effects between the components not only causes the diffusion of contact surfaces, but also leads to errors in predicting assembly tolerances. In this paper, an applicative method for tolerance analysis of flexible sheet structures and precise prediction of abundant errors in assembly characteristics is presented by modifying the influence coefficients method and by considering the effects of components’ contacts using finite element method (FEM). To do so, a proper strategy based on modeling and the analysis of effective uncertainties in the process of the assembly of the sets with flexible components has been proposed. At the end, the capabilities of the proposed method are investigated by presenting an example and the accuracy of the obtained results has been compared with Monte Carlo and experimental results.