End-To-End Simulation Framework for Injection Molding Process Optimization
Explore the source record for details and available documents.
Garg, Nikhil↗
Engineering topics
Pokkalla, Deepak
Publications and source records attributed to Pokkalla, Deepak.
Effect of Internal Structure on Warpage in a Large-Scale Additive Manufacturing Process With Bio-Derived Composites
Extrusion-based large-format additive manufacturing (LFAM) often results in unintended deformation and failures due to thermal residual stress between layers. This LFAM involves a hot molten polymer deposited on a previously deposited and cooled layer, generating a temperature mismatch between the layers. The temperature discrepancy causes a thermal contraction mismatch, generating thermal residual stress. Due to the residual stress, printed structures experience warpage and delamination Therefore, understanding the heat distribution behavior is essential to preventing undesired deformation and failures. The goal of this study is to investigate the effect of infill patterns on heat distribution and deformation in an LFAM system. Wood fiber-reinforced polylactic acid was used as a sustainable and low-cost reinforcement material. A numerical model was developed to predict the temperature and deformation field with thermo-mechanical properties, which were measured by a dynamic mechanical analysis and a thermal expansion test. Simulations were performed on a box geometry with three different infill patterns. The simulation model was verified with temperature data gathered from an infrared camera. The results show good agreement between predicted and measured temperature profiles. The developed simulation model was applied to a roof tray with different infill patterns for a case study. We found that the different thermal mass distributions resulting from the various infill patterns affected the heat distribution and deformation. These findings contribute to a better understanding of the thermal and mechanical behavior of LFAM.
Jo, Eonyeon↗
Reducing warpage in a hybrid large-scale additive manufacturing and compression molding process
In recent years, a hybrid manufacturing process, developed by combining extrusion-based large-scale additive manufacturing (AM) and compression molding (CM) techniques, has shown promising outcomes for producing structurally functional parts. The process can be used with both short fiber-reinforced composites and neat polymers and hence, even multi-material parts can be manufactured easily. This process offers the advantages of structural enhancement by having a desired fiber orientation using a large-scale AM process, as well as rapid manufacturing capability using a CM process. In the large-scale AM process, the alignment of fibers in the deposition direction enables significant improvement in the mechanical properties of the manufactured parts. However, the anisotropy resulting from the directional arrangement of fibers also introduces challenges related to warpage in the produced parts. This study aims to identify the causes of warpage and propose strategies to mitigate it. The research involves the use of preforms manufactured through the large-scale AM, which are then combined with the neat resin for CM manufacturing. A finite element-based numerical simulation model is developed, employing a sequentially coupled thermomechanical approach. Through a parametric study using the simulation models, optimization of printing direction and preform geometry is performed to minimize warpage. This contributes to the advancement and wider adoption of AM/CM hybrid manufacturing to produce structurally functional parts.
Jo, Eonyeon↗
Effect of fiber reinforcement on the process parameters of injection molding manufacturing process
Use of fillers with the resin is common in injection molding manufacturing technique to enhance the stiffness and strength of the manufactured components. However, the addition of fillers changes the rheological and mechanical properties of the material, required adjustments in the process parameters used for the manufacturing. The present study aims to investigate this impact of fillers on the process parameters of the injection molding manufacturing process. Neat Acrylonitrile Butadiene Styrene (ABS) and ABS reinforced with short glass fibers are used as the materials to perform the comprehensive numerical analysis including complete process sequence, namely filling, packing, cooling and warpage. Parametric studies are conducted to optimize the manufacturing process for minimal warpage (or shrinkage) in the produced part. The selected process parameters for the parametric study include cooling time, packing pressure, and mold temperature, all of which directly impact the quality of the manufactured parts. The optimal values obtained for these parameters are compared to examine the effect fiber reinforcement has on the manufacturing process.
Garg, Nikhil↗
Experimental and Numerical Investigations on Dynamic Mechanical Properties of TPMS Structures
Triply Periodic Minimal Surface (TPMS) lattice structures have been of increasing interest due to their light weighting, enhanced mechanical properties, and energy absorption characteristics for automotive and biomedical applications. With the advent of additive manufacturing and geometric modeling software, TPMS lattices with complex geometries can be realized. In this work, TPMS lattice structures were fabricated with PLA using fused filament fabrication (FFF) and their dynamic properties are characterized through drop tower experiments. Although lightweight TPMS lattices are beneficial for their impact absorption capability, most of the existing works are limited to quasi-static compression and dynamic impact tests are rarely performed. The current study investigates the stress-strain and energy absorption characteristics of TPMS lattices through drop tower testing and numerical modeling. Finite element modeling for TPMS lattices is carried out to validate the experimental responses. The mechanical properties, deformation, and failure mechanisms of TPMS lattices under dynamic impact are summarized for potential future applications.
Pokkalla, Deepak↗
THERMAL ANALYSIS AND DESIGN OF SELF-HEATING MOLDS USING LARGE-SCALE ADDITIVE MANUFACTURING FOR OUT-OF-AUTOCLAVE APPLICATIONS
Autoclave processing is a commonly used state-of-the-art fiber-reinforced composite manufacturing technology, albeit high capital cost, long cycle times and high energy consumption. Alternatively, out-of-autoclave processing reduces the initial and operating costs while producing composite structures with similar quality as that of autoclave parts. Additive Manufacturing (AM) the scaled-up molds for out-of-autoclave process using carbon fiber (CF) reinforced composite offers design flexibility, enhanced mechanical, and thermal properties in addition to reduction in weight and cost. However, heating of these molds using an oven is still expensive and necessitates an energy-efficient heating process. In this study, resistive heating through heating elements embedded within fiber reinforced composite molds is used as an efficient heating mechanism. The goal is to design wire embeddings and determine the optimal heat flux density to achieve a target uniform temperature of 1000C across the mold surface. To this end, numerical analyses were performed to evaluate the temperature distribution across the composite mold surface for a given wire placement and mold configuration. Constant thermal properties of the 20 wt.% short CF reinforced acrylonitrile butadiene styrene (ABS) were used in the thermal analysis. Time taken to reach the steady state temperature was also estimated. Design guidelines for wire embeddings were included to enable efficient manufacturing of fiber-reinforced composites through out-of-autoclave molds.
Pokkalla, Deepak↗
MODELLING FIBER ORIENTATION DURING ADDITIVE MANUFACTURING COMPRESSION MOLDING PROCESSES
The production of high-performance thermoplastic composites reinforced with short carbon fibers can be achieved by a novel “additive manufacturing-compression molding” technique. An advantage of such combination is two-fold: controlled fiber orientation in additive manufacturing and less void content by compression molding. In this study, a computational fluid dynamics model has been developed to predict the behavior of printed layers during fiber-reinforced thermoplastic extrusion and subsequent compression molding. The fiber orientation was modelled with a simple quadratic closure model. The interaction between the fibers is included using a rotary diffusion coefficient which becomes significant in concentrated regimes. Finally, the second order orientation tensor is coupled with the momentum equation as an anisotropic part of the stress term. The effect of processing parameters on the behavior of printed layers was investigated to determine the favorable printing scenarios. The developed numerical model enables design of high-performance composites with tunable mechanical properties.
Seta, Berin↗
MODELLING OF ADDITIVE MANUFACTURING – COMPRESSION MOLDING PROCESS USING COMPUTATIONAL FLUID DYNAMICS
A computational fluid dynamics model has been developed to predict the behavior of a printed strands during a novel material extrusion additive manufacturing and compression molding process. While the traditional additive manufacturing process enables control over the fiber orientation within the part, it would also result in high void content. On the other hand, compression molding produces parts with low porosity levels at rapid processing cycle time but lacks control over the microstructure. The novel additive manufacturing – compression molding (AM-CM) integrating both these processes offers control over both the microstructure and porosity to manufacturing high performance composite parts. The numerical model developed here enables to analyze the effect of processing parameters on the behaviour of printed layer that is subsequently compressed and to determine the optimal printing parameters for high-performance composite part design.
Seta, Berin↗
Design and Use of a Penetrating Deposition Nozzle for Z-Pinning Additive Manufacturing
Fused Filament Fabrication (FFF) involves depositing material layer-by-layer to create athree-dimensional object. This method often demonstrates high mechanical anisotropy in theprinted structure, leading to a drop in the material strength of the part when comparing structuresalong the deposition plane (X/Y-Axis) versus across layers in the build direction (Z-Axis). Initialefforts to improve anisotropy led to the development of the Z-Pinning process, where continuouspins are deposited across layers in the Z-Axis. Z-pinning has demonstrated significant gains intoughness and inter-layer strength, particularly in fiber-reinforced materials. However, thisprocess can also create flaws in the structure that increase in severity and frequency as the pinsgrow in length and diameter. To mitigate this, a penetrating nozzle has been developed thatextends a fine-tipped extrusion nozzle deep into the pin cavity and simultaneously extrudesmaterial as it retracts. This study investigates the printability of the penetrating nozzle for simplegeometries and evaluates the resulting Z-pinning mesostructure. As a result of this study, theprototype penetrating nozzle design was analyzed and built. Through a pressure driven flowanalysis it was determined that the penetrating nozzle extruder can not only flow extrudefilament. After a transient thermal simulation it was found that after a pause of 15 secondsresume printing with no drop in heat at nozzle exit.
Bales, Brenin↗
THE DESIGN OF LAYER TIME OPTIMIZATION IN LARGE SCALE ADDITIVE MANUFACTURING WITH FIBER REINFORCED POLYMER COMPOSITES
In this study, we have developed a method to optimize a layer deposition time (a.k.a. layer time) for large-scale additive manufacturing (AM) via physics-based simulations. A long layer time leads to an over-cooled surface on which a new layer is deposited, and therefore, it may result in a weak bonding or debonding between layers, cracking, or warping. A short layer time leads to a high temperature of the structure due to insufficient cooling, and therefore, the structure may not be stiff enough and may collapse during manufacturing. Therefore, it is important to estimate the optimal layer time in additive manufacturing for a high-quality product. The temperature of a top layer right before deposition is recommended to be slightly higher than the glass temperature of the material. A temperature cooling was approximated to an exponential function of time, and the optimized layer time was obtained based on a target temperature while maintaining a minimal printing time. The material used is carbon fiber-reinforced polycarbonate (CF/PC), and the large-scale deposition system used is LSAM TM from Thermwood Corporation. Three different layer time cases were used for experiments, and a series of thermal images were obtained via an infra-red (IR) camera during the entire AM processes. AM process simulations were performed using a finite element method and the temperature profiles from the simulation were in good agreement with those from experiments. The layer time optimization was performed based on the temperature profiles from the simulations. A layer temperature with the optimal layer time was confirmed as the target temperature through simulation.
Jo, Eonyeon↗
Characterization of anisotropic mechanical properties of polymer composites from a hybrid additive manufacturing-compression molding process using x-ray computer tomography
In this study, anisotropic stiffness tensors were reconstructed based on fiber orientation distributions obtained from X-ray computer tomography (xCT). A preform was manufactured via a big area additive manufacturing (BAAM) system with carbon fiber (CF) filled acrylonitrile butadiene styrene (ABS). The tailored preform from additive manufacturing (AM) was used in the compression molding (CM) process to produce a low-void high-performance thermoplastic composite panel. An xCT technique was employed to detect the fiber orientations in CF/ABS composites manufactured via three different methods: AM from BAAM, extrusion compression molding (ECM), and AM-CM. The anisotropic stiffness tensor was obtained from the composite panel manufactured via the three manufacturing methods (AM, ECM, and AMCM). A micromechanics theory was used to obtain the orthotropic stiffness tensors of the composite panels and compared with the experimental values. The predicted stiffness tensors of AM and AM-CM composite panels were used to study the deformation characteristics of a steering wheel during airbag deployment by performing finite element analysis (FEA). The approach developed in this study can be utilized for evaluating high-performance composites.
Pokkalla, Deepak↗