Analysis and Modeling of Defects in Unsupported Overhanging Features in Micro-Stereolithography

In the present paper, a numerical approach to model the layer-by-layer construction of cured material during the Additive Manufacturing (AM) process is proposed. The method is developed by a recursive mechanical finite element (FE) analysis and takes into account forces and pressures acting on the cured material during the process, in order to simulate the behavior and investigate the failure condition sources, which lead to defects in the final part geometry. The study is focused on the evaluation of the process capability Stereolithography (SLA), to build parts with challenging features in meso-micro scale without supports. Two test cases, a cantilever part and a bridge shape component, have been considered in order to evaluate the potentiality of the approach. Numerical models have been tuned by experimental test. The simulations are validated considering two test cases and briefly compared to the printed samples. Results show the potential of the approach adopted but also the difficulties on simulation settings.

Design of Self-Supported 3D Printed Parts for Fused Deposition Modeling

One of the primary challenges faced in Additive Manufacturing (AM) is reducing the overall cost and printing time. A critical factor in cost and time reduction is post-processing of 3D printed (3DP) parts, of which removing support structures is one of the most time consuming steps. Support is needed to prevent the collapse of the part or certain areas under its own weight during the 3D printing process. Currently, the design of self-supported 3DP parts follows a set of empirical guide lines. A trial and error process is needed to produce high quality parts by Fused Depositing Modeling (FDM). The usage of chamfer angle with a max 45° angle form the horizontal for FDM is a common example. Inclined surfaces with a smaller angle are prone to defects, however no theoretical basis has been fully defined, therefore a numerical model is needed. The model can predict the problematic areas at a print, reducing the experimental prints and providing a higher number of usable parts. Physical-based models have not been established due to the generally unknown properties of the material during the AM process. With simulations it is possible to simulate the part at different temperatures with a variety of other parameters that have influence on the behavior of the model. In this research, analytic calculations and physical tests are carried out to determine the material properties of the thermoplastic polymer Acrylonitrile - Butadiene - Styrene (ABS) f or FDM at the time of extrusion. This means that the ABS is going to be extruded at 200°C to 245°C and is a viscous material during part construction. Using the results from the physical and analytical models, i.e., Timoshenko’s modified beam theory for micro-structures, a numerical material model is established to simulate the filament deformation once it is deposited onto the part. Experiments were also used to find the threshold for different geometric specifications, which could then be applied to the numerical model to improve the accuracy of the simulation. The result of the finite element analysis is compared to experiments to show the correlation between the prediction of deflection in simulation and the actual deflection measured in physical experiments. A case study was conducted using an application that optimizes topology of complex geometries. After modeling and simulating the optimized part, areas of defect and errors were determined in the simulation, then verified and and measured with actual 3D prints.

Electrical Impedance Measurements of PZT Nanofiber Sensors

Electrical Impedance Measurement of PZT Nanofiber sensors are performed and material properties including resistivity and dielectric constant are derived from the measurements. Nanofibers formed by electro-spinning with diameters ranging from 10 to 150 nm were collected and integrated into sensors using microfabrication techniques. The nanosensor impedance was extremely high at low frequencies and special matching circuitry was fabricated to detect output. The resulting impedance measurements are also compared with those of individual nanofibers that were tested using Scanning Conductive Microscopy (SCM) and Conductive AFM.

Estimation of the Total Fatigue Life of Metallic Structures

The fatigue life of a component is defined as the total number of cycles or time to induce fatigue damage and to initiate a dominant fatigue flaw which is propagated to final failure.(Shigley & Mischke 2002) The aim of this project is to calculate the total fatigue life of metallic structures under cyclic loading by applying equations found by Basquin and Manson-Coffin. The local stresses and strains necessary for the calculation are determined by the finite element method. Former studies concerning this subject have used analytical methods to find the local conditions at the critical section. The analytical methods, based on Neuber and Molski-Glinka’s approaches, permit the calculation of the local stresses and strains at the critical section of the structure’s geometry as a function of the nominal stress (forces) applied. For the finite elements method, ABAQUS is used to determine the local conditions at the critical section of a T-shaped model.

Abstracting Failure Case Database Information for Detecting Failure Mode

Industrial accidents continue to happen despite rapid technological advancement and they are often caused by triggers similar to those of past accidents. If we turn our eyes to the world, especially to the emerging industrial players, we hear news about accidents caused by phenomena that have already caused similar accidents elsewhere. Industries, as they emerge and grow over hundreds of years, learn their lessons throughout their histories and build rules, regulations, and common knowledge to avoid accidents. Each industry is probably well aware of accidents that took place in its own country, especially when the accident led to enforcement of a new law. Nevertheless, we hardly have any knowledge of accidents in foreign countries unless they were of huge sizes. Japan had a national project of building a database of knowledge and lessons learned from past accidents. Failure Knowledge Database (FKDB) went on the Web in 2005. As of today it still attracts a large number of readers with its over 1,600 failure cases. Our research is targeted at making use of this FKDB by abstracting the knowledge, especially what triggered the accidents, and comparing the knowledge with functional and structural elements used in new designs. Design Record Graph (DRG) is a graphical representation of the designer’s intension starting from the left with the product functional requirement which iteratively divides into sub-functions to reach a set of functional elements (FE). Each FE maps to a structural element (SE). Then the SEs iteratively combine to form assemblies and finally the product at the right end. A failure starts from one of the FE-SE pairs and propagates the DRG in both left and right directions to reach the two ends. The propagation leaves a trace of how the point of failure led to disabling the product. For each failure case in FKDB, we identified the origin of failure, the FE-SE pair that started the accident. An FE is abstracted by a verb phrase and a set of noun phrases, and similarly an SE with some noun phrases. By limiting the phrases to use, similar concepts are described by the same abstracted phrases. A new design has a number of FE-SE pairs and their propagations in the DRG to reach the two ends. The designer can then compare all propagations in the design, without the knowledge if any of them are dangerous, with those in FKDB that are known to have led to accidents. We developed quantitative operators to evaluate the similarity between two traces. Our results offer a way of warning the designer about possible flaws in a new design similar with causes of past accidents that the designer has no idea about. Our method of preventing design failure can apply to other fields for novice planners in avoiding failure while still in the planning stage. We can further develop the use of knowledge into overseas countries by mapping the limited number of verb and noun phrases into foreign language.

Preference Aggregation in Lifecycle Decision Making

Rapid innovations in technology lead customers to frequently upgrade to new products. Their current products, now obsolete in terms of technology, aesthetic features and performance, leave behind an ecological footprint that is harmful to the environment. Product take-back systems and remanufacturing methods that promise to minimize the environmental impact are gaining attention among researchers and practitioners in the manufacturing field. A common objective is to find the best option for end of lifecycle (EOL) decisions on whether a product and the components comprising it should be reused, recycled, remanufactured, or disposed. These decisions must entail proper analysis while taking into account customer preferences, which can vary considerably from customer to customer. Mass customization, considered a plausible solution for this problem, is not viable model for many products. In this paper, therefore, we approach this problem from a preference aggregation perspective, particularly, the benevolent dictator model. Using this understanding of aggregated preferences, we address the take-back and possible remanufacturing of products. Once collected, it is questioned whether efficiency enhancing new technology or features should be added in take-back products to improve its performance or add any value. If that is the case, will these remanufactured products, with new technology or features, help in cost-effectively reducing the lifecycle environmental impact of the product, compared to a remanufactured product with original specifications? A home HVAC system was selected to exemplify the design and reuse problem, and show the benefit of favoring environmentally conscious customers in lifecycle decision making.

Understanding the Impact of Occupancy Trends in Sustainable Housing Designs

As sustainable building mandates become more prevalent in new commercial buildings, it is a challenge to create a broad, one-size-fits-all certification process. While designers can estimate energy usage with computation tools such as model based design, anticipating the post occupancy usage is more difficult. Understanding energy usage trends is especially complicated in university student housing buildings, where occupancy varies significantly as a function of enrollment and course scheduling. This research explores the effect of student occupancy on both predicted and actual energy usage in a LEED (Leadership in Energy and Environmental Design) Platinum certified student housing complex. A case study is presented from the California State University Fullerton (CSUF) campus, and examines diversity factor, defined as a building’s instantaneous energy usage as a percentage of the maximum allowable usage during a period of time, trends throughout the academic year. The CSUF case diversity factor is compared to the diversity factor used in predictive models for obtaining LEED certification, and the mandates that govern the models (e.g., ASHRAE 90.1). The results of the analysis show the benefits of considering post occupancy usage in sustainable building designs, and recommendations are presented for creating unique and application based computational models, early in the design process. This research has broad applications, and can extend to sustainable building design in other organizations, whose operational schedule falls outside of current prediction methods for sustainability mandates.

Experimental and Theoretical Studies of Nonlinear Resonances in a Si Microcantilever Constrained by a Polymer Attachment

In micro/nanometer scale mechanical resonators, constructive utilization of intentional nonlinearity has suggested ways to leverage beneficial nonlinear characteristics in their design for various applications. Previous studies have also shown that the geometric nonlinearity is effectively implemented and tailored through integration of nonlinear couplings to an otherwise linear microcantilever. Here, we demonstrate experimentally a nonlinear micromechanical resonator consisting of a silicon microcantilever axially constrained by a polymer attachment exhibiting a strong nonlinear hardening behavior not only in its first flexural mode but also in higher modes. A theoretical model representing the system with geometrically nonlinear stiffness and damping is analyzed by the method of multiple scales, which is favorably validated by good agreement with experimentally obtained nonlinear responses.

Heat Assisted Single Point Incremental Forming of Polymer Sheets

The objective of this research is to study the improvement in the formability of thermoplastics using heat assisted single point incremental forming. Single point incremental forming is a production process for forming sheet materials without the use of dedicated tooling (dies/molds). The process is an alternative to thermoforming for low volume forming of sheets. It involves forming the final shape through a series of localized incremental deformations. It has been observed that heat assisted techniques have shown an improvement in the formability limits for sheet metals. In this research, this concept has been tested for improving the formability of polymer sheets. Hot air us used to increase the temperature within a localized region in front of the tool. A single point incremental forming device is modified through the development of a specialized tool holder and nozzle which heats the polymer sheet to temperatures higher than the room temperature but below the glass transition temperature of the polymer and applies the forming loads. The results from the experiments are summarized as: i) the formability angle increases of polystyrene from 27 degrees to 46 degrees when comparing room temperature forming to forming at an elevated temperature (170°F–180 °F), ii) a reduction in the forces needed for forming is observed qualitatively, and iii) the surface finish on the formed parts do not show visible change. This demonstrates promise of manufacturing complex shapes from thermoplastic polymer sheets using heat assisted incremental forming. Future research includes 1) simulating the localized deformation of the material to enable process planning, 2) quantifying the forming forces and heat control of the system, and 3) exploring the manufacturing technique to other materials.

A Strain Distribution Based Classification of Ortho-Planar Springs: An Outlook to Piezoelectric Applications

Ortho-planar springs are characterized by their planar shape and the dominant out of plane motion. These springs have benefits for integration in piezoelectric energy harvesting transducers, because of their compactness and monolithic planar manufacturing. The operating behavior in the first low frequency bending mode can be optimized by obtaining an appropriate strain distribution. A holistic design approach is proposed that contains both the focus on strain distribution as on the low frequency dynamic operation challenge. Therefore a classification based on the strain distribution has been made, which is derived from the perspective of loading, clamping and geometry of single flexures of ortho-planar springs. A comparison based on the type of strain (bending/torsion ratio), strain inversion,off-axis stiffness and the natural frequency-normalized area factor (NFNA) has been performed. The double clamped folded configuration shows the most potential for future optimal low frequency transducer designs.