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Robotik frezeleme operasyonlarının eniyilemesi ve kinematik analizi
Robotic milling is proposed to be one of the alternatives to respond the demand for flexible and cost-effective manufacturing systems. Serial arm robots offering 6 degrees of freedom (DOF) motion capability which are utilized for robotic 5-axis milling purposes, exhibits several issues such as low accuracy, low structural rigidity and kinematic singularities etc. In 5-axis milling, the tool axis selection and workpiece positioning are still a challenge, where only geometrical issues are considered at the computer-aided-manufacturing (CAM) packages. The inverse kinematic solution of the robot i.e. positions and motion of the axes, strictly depends on the workpiece location with respect to the robot base. Therefore, workpiece placement is crucial for improved robotic milling applications. In this thesis, an approach is proposed to select the tool axis for robotic milling along an already generated 5-axis milling tool path, where the robot kinematics are considered to eliminate or decrease excessive axis rotations. The proposed approach is demonstrated through simulations and benefits are discussed. Also, the effect of workpiece positioning in robotic milling is investigated considering the robot kinematics. The investigation criterion is selected as the movement of the robot axes. It is aimed to minimize the total movement of either all axes or selected the axis responsible of the most accuracy errors. Kinematic simulations are performed on a representative milling tool path and results are discussed.
Artırılmış tırlama titreşimleri kararlılığı için robotik frezelemede sürekli değişken duruş seçimi
The demand for the usage of industrial robots for milling applications has surged owing to their superiority in terms of the large working envelope, reconfigurability, and low capital investment. Albeit such advantages, utilization of industrial robots for milling applications is yet to be a wonderland, where there are major challenges such as low tool path contouring accuracy, less static and dynamic rigidity. The former may be bearable for milling operations requiring less accuracy, such as roughing cycles. However, lowered dynamic rigidity causes decreased chatter stability, which is a roadblock towards effective robotic milling applications as a result of high vibration marks, bad surface quality, tool breakage and damage to the entire system. The position and orientation of the robots have a significant impact on milling stability. Therefore, identification of improved stable conditions is important to achieve increased productivity and process quality. In this thesis, dynamic modeling of the robots is studied to predict the variation in the robot dynamics with robot posture. Simulation results are compared to experimental modal analysis results and possible error sources are discussed. Milling dynamics and stability analysis are further extended to propose an alternative approach to increase chatter stability limits by benefiting the redundant axis of the 6-axis industrial robot. Different configurations of the robot based on the utilization of the redundant axis result in different stability limits by maintaining the same position of the tool. Preferable configuration sequences are generated for the improved cutting conditions through stability simulations based on measured frequency response functions of the tooltip. A proper robot programming scheme is also proposed in order to enable industrial application of the proposed methodology. Furthermore, the advantages of the proposed approach are discussed in accordance with the simulation results.
Büyük kemik kusurları için özelleştirilebilir, modüler doku iskele bloklarının tasarımı ve eklemeli imalatı
Bone has an excellent capacity to regenerate itself after damage, especially for minor defects. However, for large bone defects, external intervention is needed. One of the most suitable external treatments for large bone defects is bone scaffolds. However, the transplanted scaffold must conform to the unique morphological features of the patient's bone while providing adequate biomechanical support with the 3D porous inner structure. With additive manufacturing (AM), producing a structure that meets these requirements is possible. But the current customized scaffold design method (reverse engineering technique) is time-consuming, labor-intense and expensive due to the software and machinery used in the process (2D medical image acquisition machine, medical image processing software), and the joint work of technical and surgical staff to finalize the design of the scaffold. Depending on the complexity of the case, the design phase can take months. But in some cases, like high energy injuries, the proper treatment should be held in the fastest way possible. Otherwise, the patient may face severe and irreversible problems like unbearable pain, long hospitalized time, and even limb loss. In this thesis, a method of constructing a best fitting scaffold for the treatment of large bone defects from pre-printed modular blocks is introduced. A femur surface modeling algorithm using morphological features of the femur as input was created. With this algorithm, femur model of a patient is obtained with measuring the necessary measurements from the fewer number of 2D medical images obtained by more common methods such as x-ray images. To create modular blocks, another parametric algorithm was generated. Modules with different topological features can be created by changing the parameters in this algorithm as desired. Another algorithm has been developed where the created modular blocks are used as input and the tool path for the continuous extrusion AM is produced. As an output from this algorithm, a novel, zig-zag and spiral pattern to manufacture the modules was obtained as a G code file. As the last step, a system was developed that includes information on what the printed modules are. This system informs the clinician in the field about how many of which on-demand modules they could use to create a best fitting patient specific scaffold to represent the defect area of the patient. By following the instruction, the clinician puts the proper scaffold blocks on top of each other and implants the assembled scaffold structure on the body with the help of an intramedullary nail. This study represents a promising approach in the creation of a new customized best fitting scaffold with less time, money and effort for large bone defects.
Vakum torbalama prepreg sistemleri için entegre ve sistematik karakterizasyon metodolojisi
Composite materials have attracted widespread acceptance aerospace industry in the last decades as it offers high rigidity and outstanding strength/weight ratio while enabling the considerable reductions in the manufacturing and operational costs. The autoclave processes have been widely preferred for the primary and secondary aerospace applications as such requirements as high safety, high quality, and reproducibility of the industry. However, producing larger composite parts through low-cost processes has led the industry to out of autoclave processes. Hence, VBO prepregs were developed for out-of-autoclave processes to deliver high-performance composites, which can compete with the autoclave-quality composites in many aspects, such as low-void content and successful impregnation. This is possible through an appropriate combination of fiber bed architecture and resin system, and process parameters. However, composites produced through VBO prepregs are much more susceptible to voids since the maximum consolidation pressure is limited to atmospheric pressure. To address these issues, VBO prepregs were designed to incorporate relatively permeable air channels and exhibit higher initial fiber volume fractions in comparison with the autoclave prepreg systems. Nevertheless, the physical properties of the prepreg system are still the leading parameters in the evolution of VBO prepreg microstructures during the curing process as the incomplete impregnation before gelation directly controls the amount of voids, which degrades the mechanical performance of the final part. Therefore, there is a vital need for a systematic and overarching characterization methodology. This thesis aims to establish a methodology that systematically characterizes such factors as material properties and constitutive behavior to strengthen the VBO prepreg process model's accuracy and reliability. To achieve this goal, a systematic was developed to characterize the main properties of the resin and prepreg system. This approach was also implemented to characterize a commercial VBO prepreg system's properties and processing parameters. Hence, the cure-dependent properties of the resin system were characterized by several sets of semi-empirical phenomenological models. Then, the first fiber architecture, void-content change, the fiber volume fraction of the prepreg system were investigated through sets of x-ray microtomography scans of the prepreg laminates. The initial permeability behavior of the porous media was modeled through a CFD analysis. Finally, the specific heat capacity and thermal conductivity of the constituents were investigated by a series of experiments and numerical studies. This approach can be accepted as a fundamental cornerstone of establishing a process design that integrates characterization, modeling, optimization, and verification approaches to deliver high-performance composites through OoA techniques.
Sıvı kompozit kalıplama yöntemi için iki aşamalı optimizasyon metotolojisi ile güçlendirilmiş bir süreç modeli
Liquid Composite Molding (LCM) is the family of the advanced composite manufacturing method in which dry preform is placed into the mold cavity followed by filling of the preform with the resin system. The final composite part is obtained after the curing cycle. The success of the final part for LCM highly relies on the success of the impregnation of the resin system through the dry preform. In order to have fully impregnated domain, the inlet and vent locations, namely gates, should be engineered in such a way that as the resin is introduced through the inlet gate, vent should be placed where the resin arrives last. Otherwise, the process fails with the formation voids/dry spots beyond tolerance values. Additionally, the fill time of the preform domain for complete impregnation should be reduced considering both finalization of the impregnation before gelation time of the resin and the achievement of high production rates. Thus, the LCM process can be improved through the minimization of the two afore-mentioned parameters: void content and fill time. To achieve that one has to predict the flow patterns within the preform. Mathematical modeling of the resin flow in LCM process is described reasonably well as flow through porous media using Darcy's Law coupled with the continuity equation. Darcy's Law, which relates the resin pressure gradient with the resin velocity, requires two material properties: permeability tensor of the preform and the resin viscosity. Permeability tensor is a preform property and indicates the ease of flow through the preform. Generally, for the LCM models the permeability value is assigned as a bulk property, with the assumption of uniformity of the fibrous domain. This generates simple, deterministic model but as any material property variations, geometrical variations and lay-up of the assembly generate variations in permeability values, there will be some differences between real and predicted flow patterns. Another source of these differences stems from open channels (gaps) created between the edges and corners of the mold and/or inserts and preform. These 'race-tracking' channels have significant effect on the flow patterns which might cause formation of voids. The other property affecting the flow patterns, viscosity, reflects the resistance of the flow of the resin system through the preform and shows variations with temperature and time. The differences between predicted and actual values caused by over-idealized modeling negatively influence any actual utility of model predictions, particularly optimization. Therefore, the accuracy of the model entails accurate permeability data with race-tracking possibilities and viscosity as a function of time and temperature. Note that at this point this is no longer deterministic model. In this study, a new LCM modeling and optimization approach is introduced which aims to optimize void content and fill time using more realistic permeability and viscosity parameters. This is achieved by a two-stage optimization approach. In the first stage, the inlet and vent location optimization are implemented with Genetic Algorithm (GA) adaptation. The GA adaptation including the permeability variations in terms of race-tracking possibilities identifies the optimal inlet/s and vent/s locations working for all possible race-tracking possibilities with equal occurrence probabilities. Also, the GA adaptation enables further decrease in fill time with multiple inlet and multiple vent optimization practices. Then, in the second stage, using the gate locations from first stage the fill time and void percentage is further improved by placing a tailored highly permeable layer (distribution media, DM). This stage includes the lay-out design of the DM layer using a Discrete Optimization algorithm which dictates successful impregnation with minimum void percent and minimum fill time for all possible flow disturbances due to race-tracking issue. Then, this methodology is validated numerically by using Liquid Injection Molding Simulation (LIMS) for various complex geometries under different constraints. For the resin system the viscosity function is adapted from a commercially available epoxy system and permeability variation is defined as race-tracking channels with very high permeability values at the edges. Additionally, with the use of two-stage optimization methodology, computational time is decreased due to simplifications in objective function definitions.
Akustik emisyon esaslı hasar karakterizasyonu ve elektromanyetik iletim performansı kapsamında C-tipi kompozit sandviç radom panellerinin çok disiplinli araştırılması
This study aims to investigate the electromagnetic transmission performance of composite radome sandwich panel structures used in aviation and to cluster the damage mechanisms caused by barely visible impact damages within the panels with the Acoustic Emission (AE) method. Two different sandwich radome panel samples consisting of skin materials made of E-glass and aramid prepregs and Nomex® honeycomb as the core material are examined in the research. Flat sandwich panels with equal skin and core thicknesses are produced by the hot-press curing method. Measurements of the electromagnetic transmission and reflection coefficients are performed by the free space test method in the frequency range of 5-25 GHz. As a result, transmission coefficients including dielectric coefficient and loss tangent values of the panel and its constituents are obtained experimentally. Sandwich panels are numerically modeled as a multilayer substrate by using Hyperworks® FEKO software, where the material parameters that are obtained from the experimental study are used as the input for the model. Planar Green's function approach is used as the solver for the electromagnetic simulations and it is found that the results correspond well with the experiments. As a result, the aramid sandwich panel sample is showed better electromagnetic properties compared to the E-glass sandwich panel sample within the specified frequency range. Barely Visible Impact Damage (BVID) characteristics are investigated in the samples with the quasi-static indentation test approach and the data obtained by the acoustic emission sensors are subsequently clustered with the k-means algorithm to examine and categorize the damage mechanisms that occur in the structure. GAP function is used to specify the optimum initial clustering value of the k-means algorithm. Aramid sandwich panel sample is deformed under the indentation loading and several different damage mechanisms are observed throughout the sample like matrix cracking, fiber breakage, and core crushing. Unlike the aramid samples, debonding and delamination are observed at the interface of the prepreg and core structure within the E-glass sandwich panel sample. Different failure and damage mechanisms within the microstructure are also verified by SEM images. Finally, it has been found that the acoustic emission method can be a useful approach in the damage classification of radome sandwich panels under quasi-static indentation loading. Besides, aramid sandwich panel can be a more suitable material for radome applications in high frequency operating conditions due to its low transmission losses and high structural strength against indentation loads.