Computer Aided Design of Side Actions for Injection Molding of Complex Parts

Often complex molded parts include undercuts, patches on the part boundaries that are not accessible along the main mold opening directions. Undercuts are molded by incorporating side actions in the molds. Side actions are mold pieces that are removed from the part using translation directions different than the main mold opening direction. However, side actions contribute to mold cost by resulting in an additional manufacturing and assembly cost as well as by increasing the molding cycle time. Therefore, generating shapes of side actions requires solving a complex geometric optimization problem. Different objective functions may be needed depending upon different molding scenarios (e.g., prototyping versus large production runs). Manually designing side actions is a challenging task and requires considerable expertise. Automated design of side actions will significantly reduce mold design lead times. This thesis describes algorithms for generating shapes of side actions to minimize a customizable molding cost function. Given a set of undercut facets on a polyhedral part and the main parting direction, the approach works in the following manner. First, candidate retraction space is computed for every undercut facet. This space represents the candidate set of translation vectors that can be used by the side action to completely disengage from the undercut facet. As the next step, a discrete set of feasible, non-dominated retractions is generated. Then the undercut facets are grouped into undercut regions by performing state space search over such retractions. This search step is performed by minimizing the customizable molding cost function. After identifying the undercut regions that can share a side action, the shapes of individual side actions are computed. The approach presented in this work leads to practically an optimal solution if every connected undercut region on the part requires three or fewer side actions. Results of computational experiments that have been conducted to assess the performance of the algorithms described in the thesis have also been presented. Computational results indicate that the algorithms have acceptable computational performance, are robust enough to handle complex part geometries, and are easy to implement. It is anticipated that the results shown here will provide the foundations for developing fully automated software for designing side actions in injection molding

Algorithms for generating multi-stage molding plans for articulated assemblies

Plastic products such as toys with articulated arms, legs, and heads are traditionally produced by first molding individual components separately, and then assembling them together. A recent alternative, referred to as in-mold assembly process, performs molding and assembly steps concurrently inside the mold itself. The most common technique of performing in-mold assembly is through multi-stage molding, in which the various components of an assembly are injected in a sequence of molding stages to produce the final assembly. Multi-stage molding produces better-quality articulated products at a lower cost. It however, gives rise to new mold design challenges that are absent from traditional molding. We need to develop a molding plan that determines the mold design parameters and sequence of molding stages. There are currently no software tools available to generate molding plans. It is difficult to perform the planning manually because it involves evaluating large number of combinations and solving complex geometric reasoning problems. This dissertation investigates the problem of generating multi-stage molding plans for articulated assemblies. The multi-stage molding process is studied and the underlying governing principles and constraints are identified. A hybrid planning framework that combines elements from generative and variant techniques is developed. A molding plan representation is developed to build a library of feasible molding plans for basic joints. These molding plans for individual joints are reused to generate plans for new assemblies. As part of this overall planning framework, we need to solve the following geometric subproblems -- finding assembly configuration that is both feasible and optimal, finding mold-piece regions, and constructing an optimal shutoff surface. Algorithms to solve these subproblems are developed and characterized. This dissertation makes the following contributions. The representation for molding plans provides a common platform for sharing feasible and efficient molding plans for joints. It investigates the multi-stage mold design problem from the planning perspective. The new hybrid planning framework and geometric reasoning algorithms will increase the level of automation and reduce chances of design mistakes. This will in turn reduce the cost and lead-time associated with the deployment of multi-stage molding process

Manufacturability analysis for non-feature-based objects

This dissertation presents a general methodology for evaluating key manufacturability indicators using an approach that does not require feature recognition, or feature-based design input. The contributions involve methods for computing three manufacturability indicators that can be applied in a hierarchical manner. The analysis begins with the computation of visibility, which determines the potential manufacturability of a part using material removal processes such as CNC machining. This manufacturability indicator is purely based on accessibility, without considering the actual machine setup and tooling. Then, the analysis becomes more specific by analyzing the complexity in setup planning for the part; i.e. how the part geometry can be oriented to a cutting tool in an accessible manner. This indicator establishes if the part geometry is accessible about an axis of rotation, namely, whether it can be manufactured on a 4th-axis indexed machining system. The third indicator is geometric machinability, which is computed for each machining operation to indicate the actual manufacturability when employing a cutting tool with specific shape and size. The three manufacturability indicators presented in this dissertation are usable as steps in a process; however they can be executed alone or hierarchically in order to render manufacturability information. At the end of this dissertation, a Multi-Layered Visibility Map is proposed, which would serve as a re-design mechanism that can guide a part design toward increased manufacturability

A MICROFLUIDIC DIGITAL MELT PLATFORM FOR SENSITIVE BIOMARKER ANALYSIS AND PARALLELIZED PROFILING OF MOLECULAR HETEROGENEITY

Variability in gene regulation is a fundamental characteristic of biology, allowing cellular adaptation in many states, such as development, stress response, and survival. In early disease onset, genetic and epigenetic variability permit the formation of multiple cellular phenotypes. In cancer, increased cellular plasticity ultimately results in the foundation of a tumor with the phenotypic alterations necessary to dynamically adapt, proliferate, metastasize, and acquire therapeutic resistance throughout the course of the disease. One prominent form of cellular regulation is DNA methylation, an epigenetic chemical modification that can alter gene expression. Hypermethylation-induced silencing is known to occur early on in tumorigenesis, often in precursor phases of the disease. Furthermore, tumors have been shown to undergo epigenetic reprogramming throughout progression of the disease. In light of these observations, methylation heterogeneity may serve as a novel biomarker for early cancer detection. Early detection of cancer remains challenging, as symptoms often manifest in later stages and current screening techniques often lack the requisite sensitivity and specificity. To maximize effectiveness, routine screening techniques should be noninvasive, simple, and unbiased. To this end, liquid biopsies (e.g. blood samples) containing cellular debris, such as tumor-derived cell-free DNA in the plasma, are ideally suited towards routine screening. However, detection of tumor-derived molecules in plasma is challenging, as they are often rare and may be eclipsed by a high background of molecules from healthy cells. Thus a sensitive platform capable of quantifying epigenetic heterogeneity could uncover new insights and improve early detection. In this dissertation, I present a microfluidic digital melt platform for facile, highly-sensitive detection and molecule-by-molecule profiling. The platform is applied towards the quantification of epiallelic heterogeneity. Digitization of rare molecules into thousands of microchambers followed by parallelized sequencing interrogation through high resolution melt enables order of magnitude higher sensitivity than current techniques and insight into new intermolecular characteristics. I also demonstrate how this platform may be modified to complement and improve the sensing capabilities of existing commercial technologies. Finally, I validate the potential clinical utility of this platform through detection of methylation heterogeneity in complex clinical samples towards noninvasive screening applications. The technical capabilities along with the operational simplicity of this platform facilitate adoption by other laboratories and offer potential clinical utility. This system may offer new insights into the mechanisms of epigenetic regulation in pathogenesis, and potentially improve early diagnosis

Interlocking structure design and assembly

Many objects in our life are not manufactured as whole rigid pieces. Instead, smaller components are made to be later assembled into larger structures. Chairs are assembled from wooden pieces, cabins are made of logs, and buildings are constructed from bricks. These components are commonly designed by many iterations of human thinking. In this report, we will look at a few problems related to interlocking components design and assembly. Given an atomic object, how can we design a package that holds the object firmly without a gap in-between? How many pieces should the package be partitioned into? How can we assemble/extract each piece? We will attack this problem by first looking at the lower bound on the number of pieces, then at the upper bound. Afterwards, we will propose a practical algorithm for designing these packages. We also explore a special kind of interlocking structure which has only one or a small number of movable pieces. For example, a burr puzzle. We will design a few blocks with joints whose combination can be assembled into almost any voxelized 3D model. Our blocks require very simple motions to be assembled, enabling robotic assembly. As proof of concept, we also develop a robot system to assemble the blocks. In some extreme conditions where construction components are small, controlling each component individually is impossible. We will discuss an option using global controls. These global controls can be from gravity or magnetic fields. We show that in some special cases where the small units form a rectangular matrix, rearrangement can be done in a small space following a technique similar to bubble sort algorithm

Procedimiento para el análisis automatizado de la manufactura de la pieza de plástico y del molde de inyección

El proceso de manufactura mediante moldes de inyección de plástico es uno de los métodos de producción más versátiles y extendidos para la fabricación de piezas de plástico. Actualmente, existe una amplia variedad de software tipo CAD/CAE/CAM para el análisis y diseño asistido de piezas de plástico y moldes de inyección. Sin embargo, estas herramientas comerciales aún requieren de interacción humana y acceso a información geométrica interna de la pieza de plástico vinculada a su modelo CAD. La presente tesis doctoral propone una metodología universal basada en algoritmos automatizados de tipo geométrico – experto que, mediante el análisis de la geometría discreta de la pieza de plástico (malla en formato discreto definida por los elementos notables nodos y facetas), mejore y optimice el proceso actual de análisis, diseño y dimensionamiento del molde de inyección, sin recurrir a técnicas heurísticas e interacción manual por parte del usuario.Plastic injection molding is one of the most versatile and widespread manufacturing process for the plastic parts manufacture. Nowadays, there is a wide variety of CAD/CAE/CAM type software for the analysis and aided design of plastic parts and injection molds. However, these commercial tools still require human interaction and access to internal geometric information (geometric features) of the plastic part linked to their CAD model. The present PhD thesis proposes a universal methodology based on automated geometrical - expert algorithms that, by means of the analysis of the plastic part discrete geometry (mesh in discrete format defined by notable elements nodes and facets), improve and optimize the current analysis, design and dimensioning process of the injection mold, without resorting to heuristic techniques and manual interaction by the user.Tesis Univ. Jaén. Departamento Ingeniería Gráfica, Diseño y Proyectos. Leída el 3 de mayo de 2019

Micro/Nano Structures and Systems

Micro/Nano Structures and Systems: Analysis, Design, Manufacturing, and Reliability is a comprehensive guide that explores the various aspects of micro- and nanostructures and systems. From analysis and design to manufacturing and reliability, this reprint provides a thorough understanding of the latest methods and techniques used in the field. With an emphasis on modern computational and analytical methods and their integration with experimental techniques, this reprint is an invaluable resource for researchers and engineers working in the field of micro- and nanosystems, including micromachines, additive manufacturing at the microscale, micro/nano-electromechanical systems, and more. Written by leading experts in the field, this reprint offers a complete understanding of the physical and mechanical behavior of micro- and nanostructures, making it an essential reference for professionals in this field