The purpose of the present study is to develop techniques for manufacturing anatomically-shaped substrates of implants made from calcium polyphosphate (CPP) ceramic. These substrates have tissue-engineered cartilage growing on their top surfaces and can be used as implants for osteochondral focal defect repair. While many research groups have been fabricating such substrates using standard material shapes, e.g., rectangles and circular discs, it is considered beneficial to develop methods that can be integrated in the substrate fabrication process to produce an implant that is specific to a patient’s own anatomy (as obtained from computer tomography data) to avoid uneven and/or elevated stress distribution that can affect the survival of cartilage. The custom-made, porous CPP substrates were fabricated with three-dimensional printing (3DP) and computer numerically controlled (CNC) machining for the first time to the best of the author’s knowledge. The 3DP technique was employed in two routines: indirect- and direct-3DP. In the former, 3DP was used to fabricate molds for pre-shaping of the CPP substrates from two different powder size ranges (<75 μm and 106-150 μm). In the latter, CPP substrates were produced directly from the retrofitted 3DP apparatus in a layer-by-layer fashion from 45-75 μm CPP powder with a polymeric binder. The prototyped samples were then sintered to obtain the required porosity and mechanical properties. These substrates were characterized in terms of their dimensional shrinkage and density. Also, SEM images were used to assess the particle distribution and neck and bond formations. The substrates produced using the indirect-3DP method yielded densities (<75 μm: 66.28 ± 11.62% and 106-150 μm: 65.87 ± 6.12%), which were comparable to the substrates used currently and with some success in animal studies. Geometric adjustment factors were devised to compensate for the slight expansion inherent in the 3DP mold fabricating process. These equations were used to bring the plaster molds into true dimension. The direct-3DP method has proven to be the ultimate choice due to its ability to produce complex anatomically-shaped substrates without the use of a chemical solvent. In addition, it allows for precise control of both pore size and internal architectures of the substrates. Thus, the direct-3DP was considered to be superior than the indirect-3DP as a fabrication method. In the alternative CNC machining approach to fabrication, the ability to machine the CPP ceramic was feasible and by careful selection of the machining conditions, anatomically-shaped CPP substrates were produced. To develop strategies for optimizing the machining process, a mechanistic model was developed based on curve fitting the average cutting forces to determine the cutting coefficients for CPP. These cutting coefficients were functions of workpiece material, axial depth of cut, chip width, and cutter geometry. To explore the utility of this modelling approach, cutting forces were predicted for a helical ball-end mill and compared with experimental results. The cutting force simulation exhibits good agreement in predicting the fundamental force magnitude and general shape of the actual forces. However, there were some discrepancies between the predicted and measured forces. These differences were attributed to internal microstructure defects, density gradients, and the use of a shear plane model in force prediction that was not entirely appropriate for brittle materials such as CPP. The present study successfully developed 3DP and CNC fabrication methods for manufacturing anatomically-shaped CPP substrates. Future studies were recommended to explore further optimization of these fabrication methods and to demonstrate the utility of accurate substrates shapes to the clinical application of focal defect repair implants.

The proliferation of electric machines has drastically increased in recent years and is likely to increase into the future. This interest in the production of advanced, high power density electrical machines that are small in size has heightened the need for flexible manufacturing processes to produce their laminated components during short batch and prototyping production runs. A means of cost effective, accelerated prototyping of these machines will have a substantial impact on their design and optimization, reducing time requirements to produce and test a given design. A review of the current manufacturing methods for prototyping electric machines was conducted. In particular, laser cutting, electric discharge machining, and abrasive waterjet (AWJ) machining were researched as competitive processes. Each of these methods exhibits marked advantages and disadvantages that present the opportunity for a new process to compete. This work investigates the applicability of high throughput profile milling (HTPM) for the prototyping of advanced electric machines, specifically, the process parameter space for milling of electrical steels. The material response will be determined by characterizing its specific cutting energy and utilizing this to develop a model to predict cutting forces during the milling process. Optimal process parameters will be investigated to obtain maximum productivity and minimal burr formation. Finally, the impact of HTPM processing on the magnetic properties of electrical steels will be compared to that of a leading prototyping technology, AWJ machining.

The purpose of the present study is to develop techniques for manufacturing anatomically-shaped substrates of implants made from calcium polyphosphate (CPP) ceramic. These substrates have tissue-engineered cartilage growing on their top surfaces and can be used as implants for osteochondral focal defect repair. While many research groups have been fabricating such substrates using standard material shapes, e.g., rectangles and circular discs, it is considered beneficial to develop methods that can be integrated in the substrate fabrication process to produce an implant that is specific to a patient’s own anatomy (as obtained from computer tomography data) to avoid uneven and/or elevated stress distribution that can affect the survival of cartilage. The custom-made, porous CPP substrates were fabricated with three-dimensional printing (3DP) and computer numerically controlled (CNC) machining for the first time to the best of the author’s knowledge. The 3DP technique was employed in two routines: indirect- and direct-3DP. In the former, 3DP was used to fabricate molds for pre-shaping of the CPP substrates from two different powder size ranges (<75 μm and 106-150 μm). In the latter, CPP substrates were produced directly from the retrofitted 3DP apparatus in a layer-by-layer fashion from 45-75 μm CPP powder with a polymeric binder. The prototyped samples were then sintered to obtain the required porosity and mechanical properties. These substrates were characterized in terms of their dimensional shrinkage and density. Also, SEM images were used to assess the particle distribution and neck and bond formations. The substrates produced using the indirect-3DP method yielded densities (<75 μm: 66.28 ± 11.62% and 106-150 μm: 65.87 ± 6.12%), which were comparable to the substrates used currently and with some success in animal studies. Geometric adjustment factors were devised to compensate for the slight expansion inherent in the 3DP mold fabricating process. These equations were used to bring the plaster molds into true dimension. The direct-3DP method has proven to be the ultimate choice due to its ability to produce complex anatomically-shaped substrates without the use of a chemical solvent. In addition, it allows for precise control of both pore size and internal architectures of the substrates. Thus, the direct-3DP was considered to be superior than the indirect-3DP as a fabrication method. In the alternative CNC machining approach to fabrication, the ability to machine the CPP ceramic was feasible and by careful selection of the machining conditions, anatomically-shaped CPP substrates were produced. To develop strategies for optimizing the machining process, a mechanistic model was developed based on curve fitting the average cutting forces to determine the cutting coefficients for CPP. These cutting coefficients were functions of workpiece material, axial depth of cut, chip width, and cutter geometry. To explore the utility of this modelling approach, cutting forces were predicted for a helical ball-end mill and compared with experimental results. The cutting force simulation exhibits good agreement in predicting the fundamental force magnitude and general shape of the actual forces. However, there were some discrepancies between the predicted and measured forces. These differences were attributed to internal microstructure defects, density gradients, and the use of a shear plane model in force prediction that was not entirely appropriate for brittle materials such as CPP. The present study successfully developed 3DP and CNC fabrication methods for manufacturing anatomically-shaped CPP substrates. Future studies were recommended to explore further optimization of these fabrication methods and to demonstrate the utility of accurate substrates shapes to the clinical application of focal defect repair implants.

The goal of this thesis work has been to develop and manufacture an ice layer which was to be mounted on the tip of a scaled down wing model. The iced wing should be tested in a wind tunnel and aerodynamic comparisons should be made to the same wing without ice.The development of the ice was carried out as a modified product development process. The main differences are that there is no costumer and that the actual shape and functions of the product are more or less predetermined. The challenge was to find the best way to create the ice layer and how to mount it to the wing without damaging it or covering any pressure sensors. Product development methods such as pros and cons lists and prototypes were used to solve problems before printing the plastic ice layer in a rapid prototyping machine.Wind tunnel experiments were then conducted on the wing with and without the manufactured ice. Raw data from the wind tunnel were processed and lift and drag coefficients were calculated using mathematical equations. Finally, conclusions were drawn by comparing the results from the wind tunnel tests with theory, other works as well as CFD simulations.The ice layer was successfully manufactured and it met the target specifications. The aerodynamic performance of an iced aircraft wing proved to be considerably worse compared to a blank wing. The maximum achievable lift force decreased by 22% and an increased drag force will require more thrust from the airplane.

This work develops optimal assembly sequences for modular building blocks. The underlying concept is that an automated device could take a virtual shape such as a CAD file, and automatically decide how to physically build the shape using simple, identical building blocks. This entails deciding where to place blocks inside the shape and generating an efficient assembly sequence that a robot could use to build the shape. The blocks are defined in a general, parameterized manner such that the model can be easily modified in the future. The primary focus of this work is the development of methods for generating assembly sequences in a time-feasible manner that ensure static stability at each step of the assembly. Most existing research focuses on complete enumeration of every possible assembly sequence and evaluation of many possible sequences. This, however, is not practical for systems with a large number of parts for two reasons: (1) the number of possible assembly sequences is exponential in the number of parts, and (2) each static stability test is very time-consuming. The approach proposed here is to develop a multi-hierarchical rule-based approach to assembly sequences. This is accomplished by formalizing and justifying both high-level and mid-level assembly rules based on static considerations. Application of these rules helps develop assembly sequences rapidly. The assembly sequence is developed in a time-feasible manner according to the geometry of the structure, rather than evaluating statics along the way. This work only evaluates the static stability of each step of the assembly once. The behavior of the various rules is observed both numerically and through theory, and guidelines are developed to suggest which rules to apply. A secondary focus of this work is to introduce methods by which the inside of the structure can be optimized. This structure optimization research is implemented by genetic algorithms that solve the multi-objective optimization problem in two dimensions, and can be extended to three dimensions.

Mask Projection Stereolithography (MPSLA) is a high resolution manufacturing process that builds parts layer by layer in a photopolymer. In this research, a process planning method to fabricate MPSLA parts with constraints on dimensions, surface finish and build time is formulated. As a part of this dissertation, a MPSLA system is designed and assembled. The irradiance incident on the resin surface when a given bitmap is imaged onto it is modeled as the Irradiance model . This model is used to formulate the Bitmap generation method which generates the bitmap to be imaged onto the resin in order to cure the required layer. Print-through errors occur in multi-layered builds because of radiation penetrating beyond the intended thickness of a layer, causing unwanted curing. In this research, the print through errors are modeled in terms of the process parameters used to build a multi layered part. To this effect, the Transient layer cure model is formulated, that models the curing of a layer as a transient phenomenon, in which, the rate of radiation attenuation changes continuously during exposure. In addition, the effect of diffusion of radicals and oxygen on the cure depth when discrete exposure doses, as opposed to a single continuous exposure dose, are used to cure layers is quantified. The print through model is used to formulate a process planning method to cure multi-layered parts with accurate vertical dimensions. This method is demonstrated by building a test part on the MPSLA system realized as a part of this research. A method to improve the surface finish of down facing surfaces by modulating the exposure supplied at the edges of layers cured is formulated and demonstrated on a test part. The models formulated and validated in this dissertation are used to formulate a process planning method to build MPSLA parts with constraints on dimensions, surface finish and build time. The process planning method is demonstrated by means of a case study.

Today the most prosperous interface of architectural design and representation has become the architectural model both in its digital and physical forms. There has been a shift in the design medium from the physical modeling processes to computer-aided design, by way of which the computational design methods have established a much more dynamic, complex, and continual design. In this process, the digital design model now accompanies the whole design as a single entity, contrary to conventional analog modeling techniques where design is compartmentalized into linear phases. By the embracement of computer-aided manufacturing (CAM) in company of computeraided design (CAD), physical modeling has gained another dimension in the interwoven relationship of the digital and physical. The aim of this study is to explore the novel conceptual and computational changes which mark the departure of this new mode of design from the old. There has always been a hierarchy of presence between the virtual space of representations and architecture&rsquo / s materiality. Within this context, the emphasis of the study is on the relationship between the virtuality of conception and modeling processes, and the materiality of construction, production and fabrication.

During last decade, polyurethanes (PUs) which are able to degrade into harmless molecules upon implantation have received a significant level of attention as a biomaterial in tissue engineering applications. Many studies are focused especially on development of PUs based on amino acid derivatives / however, there are only few applications of amino acid based PUs in tissue engineering. In this study, a biocompatible and biodegradable thermoplastic poly(ester-urethane) (PEU) based on L-lysine diisocyanate (LDI) and polycaprolactone diol (PCL) was synthesized and used for the preparation of two dimensional (2D) films and three dimensional (3D) scaffolds. The resulting polymer was casted as 2D films for full characterization purpose and it was found that it is highly elastic with modulus of elasticity ~12 MPa. Surfaces of 2Ds were modified via micropatterning and fibrinogen coating to check the material-cell interaction. The 3D scaffolds were obtained by salt leaching and rapid prototyping (bioplotting) techniques. The 3D scaffolds had various pore size and porosity with different mechanical strength. The bioplotted scaffolds had uniform pore size of ~450 &micro / m and exhibited higher compressive modulus (~4.7 MPa) compared to those obtained by salt leaching (~147 kPa). Salt leached 3D scaffolds had inhomogenous pore size distribution in the range of 5 &micro / m - 350 &micro / m and demonstrated greatest degradation profile compared to 2D films and 3D bioplotted samples under enzymatic condition. Rat bone marrow stem cells (BMSCs) were used to investigate the biocompatibility of the polymer and suitability of fabricated scaffolds for osteogenesis. Presence of micropatterns on 2D matrices did not show any influence on osteoblastic function, but presence of fibrinogen enhanced cell attachment and proliferation. All of the fabricated 3D PEU matrices supported proliferation, osteoblastic differentiation and extracellular matrix (ECM) deposition with highest osteoblastic activity on bioplotted scaffolds which confirmed by von Kossa staining and EDX analysis. The results indicated that the synthesized PEU based scaffolds were able to induce osteoblastic differentiation and mineralization of BMSC and therefore these scaffolds can be good candidates to be used in bone tissue engineering

Customized cellular material is a relatively new area made possible by advancements in rapid manufacturing technologies. Rapid manufacturing is ideal for the production of customized cellular structure, especially on the meso scale, due to the size and complexity of the design. The means to produce this type of structure now exist, but the processes to design the structure are not well developed. The manual design of customized cellular material is not realistic due to the large number of features. Currently there are few tools available that aid in the design of this type of material. In this thesis, an automated tool to design customized cellular structure is presented.

Rapid prototyping (RP) can be used to make complex shapes with very little or even no constraint on the form of the parts. New design methods are needed for parts that can take advantage of the unique capabilities of RP. Although current synthesis methods can successfully solve simple design problems, practical applications with thousands to millions elements are prohibitive to generate solution for. Two factors are considered. One is the number of design variables; the other is the optimization method. To reduce the number of design variables, parametric approach is introduced. Control diameters are used to control all strut size across the entire structure by utilizing a concept similar to control vertices and Bezier surface. This operation allows the number of design variables to change from the number of elements to a small set of coefficients. In lattice structure design, global optimization methods are popular and widely used. These methods use heuristic strategies to search the design space and thus perform, as oppose to traditional mathematical programming (MP) methods, a better global search. This work propose that although traditional MP methods find local optimum near starting point, given a quick convergence rate, it will be more efficient to perform such method multiple times to integrate global search than using a global optimization method. Particle Swarm Optimization and Levenburg-Marquardt are chosen to perform the experiments.