6,328 research outputs found

    Design for Additive Manufacturing of Conformal Cooling Channels Using Thermal-Fluid Topology Optimization and Application in Injection Molds

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    Additive manufacturing allows the fabrication parts and tools of high complexity. This capability challenges traditional guidelines in the design of conformal cooling systems in heat exchangers, injection molds, and other parts and tools. Innovative design methods, such as network-based approaches, lattice structures, and structural topology optimization have been used to generate complex and highly efficient cooling systems; however, methods that incorporate coupled thermal and fluid analysis remain scarce. This paper introduces a coupled thermal-fluid topology optimization algorithm for the design of conformal cooling channels. With this method, the channel position problem is replaced to a material distribution problem. The material distribution directly depends on the effect of flow resistance, heat conduction, as well as forced and natural convection. The problem is formulated based on a coupling of Navier-Stokes equations and convection-diffusion equation. The problem is solved by gradient-based optimization after analytical sensitivity derived using the adjoint method. The algorithm leads a two -dimensional conceptual design having optimal heat transfer and balanced flow. The conceptual design is converted to three-dimensional channels and mapped to a morphological surface conformal to the injected part. The method is applied to design an optimal conformal cooling for a real three dimensional injection mold. The feasibility of the final designs is verified through simulations. The final designs can be exported as both three-dimensional graphic and surface mesh CAD format, bringing the manufacture department the convenience to run the tool path for final fitting

    Octree-based production of near net shape components

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    Near net shape (NNS) manufacturing refers to the production of products that require a finishing operation of some kind. NNS manufacturing is important because it enables a significant reduction in: machining work, raw material usage, production time, and energy consumption. This paper presents an integrated system for the production of near net shape components based on the Octree decomposition of 3-D models. The Octree representation is used to automatically decompose and approximate the 3-D models, and to generate the robot instructions required to create assemblies of blocks secured by adhesive. Not only is the system capable of producing shapes of variable precision and complexity (including overhanging or reentrant shapes) from a variety of materials, but it also requires no production tooling (e.g., molds, dies, jigs, or fixtures). This paper details how a number of well-known Octree algorithms for subdivision, neighbor findings, and tree traversal have been modified to support this novel application. This paper ends by reporting the construction of two mechanical components in the prototype cell, and discussing the overall feasibility of the system

    Research on Layer Manufacturing Techniques at Fraunhofer

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    Within the German Fraunhofer-Gesellschaft, the Fraunhofer Alliance Rapid Prototyping unites the competences of 12 institutes in the field of solid freeform fabrication. Covered competences are virtual and computer-aided product planning methods and techniques, the development and integration of materials and processes for different industrial sectors. This paper presents actual research results on layer manufacturing within the Fraunhofer- Gesellschaft based on examples from Fraunhofer ILT »Laser Melting - Direct manufacturing of metal parts with unique properties«, Fraunhofer IFAM »ecoMold - A novel concept to produce molds for plastic injection molding and pressure die casting« and Fraunhofer IPT »Quick manufacture, repair and modification of steel molds using Controlled Metal Build Up (CMB)«.Mechanical Engineerin

    Recent advances in 3D printing of biomaterials.

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    3D Printing promises to produce complex biomedical devices according to computer design using patient-specific anatomical data. Since its initial use as pre-surgical visualization models and tooling molds, 3D Printing has slowly evolved to create one-of-a-kind devices, implants, scaffolds for tissue engineering, diagnostic platforms, and drug delivery systems. Fueled by the recent explosion in public interest and access to affordable printers, there is renewed interest to combine stem cells with custom 3D scaffolds for personalized regenerative medicine. Before 3D Printing can be used routinely for the regeneration of complex tissues (e.g. bone, cartilage, muscles, vessels, nerves in the craniomaxillofacial complex), and complex organs with intricate 3D microarchitecture (e.g. liver, lymphoid organs), several technological limitations must be addressed. In this review, the major materials and technology advances within the last five years for each of the common 3D Printing technologies (Three Dimensional Printing, Fused Deposition Modeling, Selective Laser Sintering, Stereolithography, and 3D Plotting/Direct-Write/Bioprinting) are described. Examples are highlighted to illustrate progress of each technology in tissue engineering, and key limitations are identified to motivate future research and advance this fascinating field of advanced manufacturing

    Process planning for an Additive/Subtractive Rapid Pattern Manufacturing system

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    This dissertation presents a rapid manufacturing process for sand casting patterns using a hybrid additive/subtractive approach. This includes three major areas of research that will enable highly automated process planning; a critical need for a rapid methodology. The first research area yields a model for automatically determining the locations of layers, given the slab height, material types and part geometry. Layers are chosen such that it will avoid catastrophic failures and poor machining conditions in general. First, features that are possible thin material machining positions are defined, and methods for detecting these feature positions from an STL model are studied. Next, a layer thickness calculation model is presented according to positions of these features. The second area focuses on tools and parameters for the subtractive side of processing each layer. A tool size and machining parameter selection model is presented that can automatically select tool sizes and machining parameters, given layer thickness, part geometry, and material types. Machining strategies and related machining parameters are studied first. Then the method for Stepdown parameter calculation is presented. Finally, an algorithm based on both accessibility and machining efficiency is proposed for the selection of tool sizes for the rough cutting operation, finish cutting operation and optional semi-rough cutting operation. The final research area focuses on a cutting force analysis for thin material machining with additional layer thickness & tool size interaction. Popular cutting force models are reviewed, and a suitable model for cutting force calculation in this process is evaluated. Then, a cantilever beam model is used to analyze the thin material machining failure problem, and a minimum layer thickness model is presented. Third, a combined layer thickness & tool size model is constructed based on the machining tool deflection under cutting forces. This rapid pattern manufacturing process and related software has been implemented, and experimental data is presented to illustrate the efficacy of this system and its process planning methods

    Automatic online algorithm selection for optimization in cyber-physical production systems

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    Shrinking product lifecycles, progressing market penetration of innovative product technologies, and increasing demand for product individualization lead to frequent adjustments of production processes and thus to an increasing demand for frequent optimization of production processes. Offline solutions are not always available, and even the optimization problem class itself may have changed in terms of the value landscape of the objective function: Parameters may have been added, the locations of optimal values and the values themselves may have changed. This thesis develops an automatic solution to the algorithm selection problem for continuous optimization. Furthermore, based on the evaluation of three different real-world use cases and a review of well-known architectures from the field of automation and cognitive science, a system architecture suitable for use in large data scenarios was developed. The developed architecture has been implemented and evaluated on two real-world problems: A Versatile Production System (VPS) and Injection Molding Optimization (IM). The developed solution for the VPS was able to automatically tune the feasible algorithms and select the most promising candidate, which significantly outperformed the competitors. This was evaluated by applying statistical tests based on the generated test instances using the process data and by performing benchmark experiments. This solution was extended to the area of multi-objective optimization for the IM use case by specifying an appropriate algorithm portfolio and selecting a suitable performance metric to automatically compare the algorithms. This allows the automatic optimization of three largely uncorrelated objectives: cycle time, average volume shrinkage, and maximum warpage of the parts to be produced. The extension to multi-objective handling for IM optimization showed a huge benefit in terms of manual implementation effort, as most of the work could be done by configuration. The implementation effort was reduced to selecting optimizers and hypervolume computation

    Nonterrestrial utilization of materials: Automated space manufacturing facility

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    Four areas related to the nonterrestrial use of materials are included: (1) material resources needed for feedstock in an orbital manufacturing facility, (2) required initial components of a nonterrestrial manufacturing facility, (3) growth and productive capability of such a facility, and (4) automation and robotics requirements of the facility

    Manufacturability Analysis of Thermally-Enhanced Polymer Composite Heat Exchangers

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    Thermally-enhanced polymer composite heat exchangers are an attractive alternative for applications such as the use of seawater as a cooling medium and other corrosive environments that traditionally use expensive exotic metallic alloys, but a number of manufacturing challenges exist. The goal of this thesis is to develop an understanding of the manufacturing feasibility, in particular mold filling and fiber orientation, of utilizing thermally-enhanced polymer composites and injection molding to manufacture polymer heat exchangers. To best predict mold filling feasibility, this thesis proposes developing an explicit construction of the boundary, represented as a surface based on the parameter space, which separates the feasible and infeasible design space. The feasibility boundary for injection molding in terms of the design parameters is quite complex due to the highly nonlinear process physics, which, consequently, makes molding simulation computationally intensive and time consuming. This thesis presents a new approach for the explicit construction of a moldability-based feasibility boundary based on intelligent Design of Experiments and adaptive control techniques to minimize the number or computation experiments needed to build an accurate model of the feasibility boundary. Additionally, to improve the flexibility of the mold filling prediction framework to changes in overall heat exchanger design, a model simplification approach is presented to predict mold filling for general finned-plate designs by determining an equivalent flat plate representation and utilizing a developed flat plate mold filling metamodel to estimate mold filling. Finally, a fiber orientation measurement methodology is presented for experimentally determining fiber orientation behavior for sample heat exchanger geometries that develops both a local and global understanding of the fiber orientation behavior and compares thesis findings to simulation predictions. The work presented in this thesis significantly advances the understanding of manufacturability considerations for utilizing thermally-enhanced polymer composites in heat exchanger applications and is useful in design exploration, optimization, and decision-making approaches
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