Axial Control of Two-Photon Polymerization With Femtosecond Bessel Beam

Stereolithography of three-dimensional, arbitrarily-shaped objects is achieved by successively curing photopolymer on multiple 2D planes and then stacking these 2D slices into 3D objects. Often as a bottleneck for speeding up the fabrication process, this layer-by-layer approach originates from the lack of axial control of photopolymerization. In this paper, we present a novel stereolithography technology with which two-photon polymerization can be dynamically controlled in the axial direction using Bessel beam generated from a spatial light modulator (SLM) and an axicon. First, we use unmodulated Bessel beam to fabricate micro-wires with an average diameter of 100 μm and a length exceeding 10 mm, resulting in an aspect ratio > 100:1. A study on the polymerization process shows that a fabrication speed of 2 mm/s can be achieved. Defect and deformation are observed, and the micro-wires consist of multiple narrow fibers which indicate the existence of the self-writing effect. A test case is presented to demonstrate fast 3D printing of a hollow tube within one second. Next, we modulate the Bessel beam with an SLM and demonstrate the simultaneous generation of multiple focal spots along the laser propagation direction. These spots can be dynamically controlled by loading an image sequence on the SLM. The theoretical foundation of this technology is outlined, and computer simulation is conducted to verify the experimental results. The presented technology extends current stereolithography into the third dimension, and has the potential to significantly increase 3D printing speed.

Measurement of the Melt Pool Length During Single Scan Tracks in a Commercial Laser Powder Bed Fusion Process

This work presents high speed thermographic measurements of the melt pool length during single track laser scans on nickel alloy 625 substrates. Scans are made using a commercial laser powder bed fusion machine while measurements of the radiation from the surface are made using a high speed (1800 frames per second) infrared camera. The melt pool length measurement is based on the detection of the liquidus-solidus transition that is evident in the temperature profile. Seven different combinations of programmed laser power (49 W to 195 W) and scan speed (200 mm/s to 800 mm/s) are investigated and numerous replications using a variety of scan lengths (4 mm to 12 mm) are performed. Results show that the melt pool length reaches steady state within 2 mm of the start of each scan. Melt pool length increases with laser power, but its relationship with scan speed is less obvious because there is no significant difference between cases performed at the highest laser power of 195 W. Although keyholing appears to affect the anticipated trends in melt pool length, further research is required.

Effect of Different Heat Treatments on Mechanical Properties of Laser Sintered Additive Manufactured Parts

One of the most popular additive manufacturing processes is laser based direct metal laser sintering process which enables us to make complex three dimensional parts directly from CAD models. Due to layer by layer formation, parts built in this process tend to be anisotropic in nature. Suitable heat treatment can reduce this anisotropic behaviour by changing the microstructure. Depending upon the applications, a wide range of mechanical properties can be achieved between 482–621° C temperature for precipitation-hardened stainless steels. In the present study effect of different heat treatment processes, namely solution annealing, ageing and overaging, on tensile strength, hardness and wear properties has been studied in detail. Suitable metallurgical and mechanical characterization techniques have been applied wherever required, to support the experimental observations. Results show H900 condition gives highest yield strength and lowest tensile strain at break whereas solution annealing gives lowest yield strength and as-built condition gives highest tensile strain at break. SEM images show that H900 and H1150 condition produces brittle and ductile morphology respectively which in turn gives highest and lowest hardness value respectively.XRD analysis shows presence of austenite phases which can increase hardness at the cost of ductility. Average wear loss for H900 condition is highest whereas it is lowest for solution annealed condition. Further optical and SEM images have been taken to understand the basic wear mechanism involved.

Conceptual Design of an Experiment for the International Space Station About Shape Memory Composite in Space Environment

Shape memory polymers (SMP) and composites (SMPC) may be used for many applications in Space, from self-deployable structures (such as solar sails, panels, shields, booms and antennas), to grabbing systems for Space debris removal, up to new-concept actuators for telescope mirror tuning. Experiments on the International Space Station are necessary for testing prototypes in relevant environment, above all for the absence of gravity which affects deployment of slender structures but also to evaluate the aging effects of the Space environment. In fact, several aging mechanisms are possible, from polymer cracking to cross-linking and erosion, and different behaviors are expected as well, from consolidating the temporary shape to composite degradation. Evaluating the possibility of shape recovery because of sun exposure is another interesting point. In this study, a possible experiment on the ISS is shown with the aim of evaluating the aging effect of Space on material performances. The sample structure is described as well as the testing strategy.

Interlaminar Toughening of GFRP: Part 2 — Characterization and Numerical Simulation of Curing Kinetics

Various methods of toughening the bonding between the interleaf and laminate glass fiber reinforced polymer (GFRP) has been developed due to the increasing applications in industries. A polystyrene (PS) additive modified epoxy is used to improve the diffusion and precipitation region between polysulfone (PSU) interleaf and epoxy due to its influence on the curing kinetics without changing glass transition temperature and viscosity of the curing epoxy. The temperature dependent diffusivities of epoxy, amine hardener, and PSU are determined by using Attenuated Total Reflection-Fourier Transfer Infrared Spectroscopy (ATR-FTIR) through monitoring the changing absorbance of their characteristic peaks. Effects of PS additive on diffusivity in the epoxy system is investigated by comparing the diffusivity between non-modified and PS modified epoxy. The consumption rate of the epoxide group in the curing epoxy reveals the curing reaction rate, and the influence of PS additive on the curing kinetics is also studied by determining the degree of curing with time. A diffusivity model coupled with curing kinetics is applied to simulate the diffusion and precipitation process between PSU and curing epoxy. The effect of geometry factor is considered to simulate the diffusion and precipitation process with and without the existence of fibers. The simulation results show the diffusion and precipitation depths which matches those observed in the experiments.

Investigation of Structure-Property Relationships in Thermoplastic Polyurethane/Multiwalled Carbon Nanotube Composites

In this study, the structure-property relationships in thermoplastic polyurethane (TPU) filled with multi-walled carbon nanotubes (MWCNTs) were investigated. Firstly, the contribution of MWCNTs to the melt shear viscosity and the pressure-volume-temperature (pVT) behavior was investigated. Secondly, injection-molded samples and 2 mm diameter filaments of TPU/MWCNT composites were fabricated and their mechanical and electrical properties analyzed. It was found that the melt processability of TPU/MWCNT composites is not affected by the addition of a small amount (1–5 wt.%) of MWCNTs, all composites displaying shear-thinning at high shear rates. The mechanical and electrical properties of the TPU/MWCNT composites were substantially enhanced with the addition of MWCNTs. However, the conductivity values of composites processed by injection molding were two and three orders of magnitude lower than those of composites processed by extrusion, highlighting the role of melt shear viscosity on the dispersion and agglomeration of nanotubes.

Assessing the Geometric Integrity of Additive Manufactured Parts From Point Cloud Data Using Spectral Graph Theoretic Sparse Representation-Based Classification

This work proposes a novel approach for geometric integrity assessment of additive manufactured (AM, 3D printed) components, exemplified by acrylonitrile butadiene styrene (ABS) polymer parts made using fused filament fabrication (FFF) process. The following two research questions are addressed in this paper: (1) what is the effect of FFF process parameters, specifically, infill percentage (If) and extrusion temperature (Te) on geometric integrity of ABS parts?; and (2) what approach is required to differentiate AM parts with respect to their geometric integrity based on sparse sampling from a large (∼ 2 million data points) laser-scanned point cloud dataset? To answer the first question, ABS parts are produced by varying two FFF parameters, namely, infill percentage (If) and extrusion temperature (Te) through design of experiments. The part geometric integrity is assessed with respect to key geometric dimensioning and tolerancing (GD&T) features, such as flatness, circularity, cylindricity, root mean square deviation, and in-tolerance percentage. These GD&T parameters are obtained by laser scanning of the FFF parts. Concurrently, coordinate measurements of the part geometry in the form of 3D point cloud data is also acquired. Through response surface statistical analysis of this experimental data it was found that discrimination of geometric integrity between FFF parts based on GD&T parameters and process inputs alone was unsatisfactory (regression R2 < 50%). This directly motivates the second question. Accordingly, a data-driven analytical approach is proposed to classify the geometric integrity of FFF parts using minimal number (< 2% of total) of laser-scanned 3D point cloud data. The approach uses spectral graph theoretic Laplacian eigenvalues extracted from the 3D point cloud data in conjunction with a modeling framework called sparse representation to classify FFF part quality contingent on the geometric integrity. The practical outcome of this work is a method that can quickly classify the part geometric integrity with minimal point cloud data and high classification fidelity (F-score > 95%), which bypasses tedious coordinate measurement.

Deposition of Bead Arrays With Variable Diameter by Self-Focusing of Electrohydrodynamic Jets

Electrohydrodynamic processes were used for direct-writing of bead arrays with controllable bead sizes. Experiments were conducted to align layers of bead-on-string structures in an effort to create three-dimensional patterns. The results show that the jet focuses on previously deposited droplets allowing for the selective deposition of material over already deposited patterns. Jet attraction to already deposited solutions on the substrate is attributed to the charge transport at the liquid ink-metal collector interface and the dielectric properties of the water/poly(ethylene oxide) solution under an electric field. The deposition process consists of 3 steps: (1) deposition of a layer of bead-on-string structures, (2) addition of extra volume to the beads by subsequent passes of the jet, and (3) evaporation of the solvent resulting in an array of beads with varying sizes. Patterns with up to 20 passes were experimentally obtained. The beads’ height was seen to be independent of the number of passes. The process reported is a simple, fast, and low-cost method for deposition of bead arrays with varying diameters.

Measuring the Complexity of Additive Manufacturing Supply Chains

Complexity has been one of the focal points of attention in the supply chain management domain, as it deteriorates the performance of the supply chain and makes controlling it problematic. The complexity of supply chains has been significantly increased over the past couple of decades. Meanwhile, Additive Manufacturing (AM) not only revolutionizes the way that the products are made, but also brings a paradigm shift to the whole production system. The influence of AM extends to product design and supply chain as well. The unique capabilities of AM suggest that this manufacturing method can significantly affect the supply chain complexity. More product complexity and demand heterogeneity, faster production cycles, higher levels of automation and shorter supply paths are among the features of additive manufacturing that can directly influence the supply chain complexity. Comparison of additive manufacturing supply chain complexity to its traditional counterpart requires a profound comprehension of the transformative effects of AM on the supply chain. This paper first extracts the possible effects of AM on the supply chain and then tries to connect these effects to the drivers of complexity under three main categories of 1) market, 2) manufacturing technology, and 3) supply, planning and infrastructure. Possible impacts of additive manufacturing adoption on the supply chain complexity have been studied using information theoretic measures. An Agent-based Simulation (ABS) model has been developed to study and compare two different supply chain configurations. The findings of this study suggest that the adoption of AM can decrease the supply chain complexity, particularly when product customization is considered.

Accelerated Geometry Accuracy Optimization of Additive Manufacturing Parts

Despite recent advances in improving mechanical properties of parts fabricated by Additive Manufacturing (AM) systems, optimizing geometry accuracy of AM parts is still a major challenge for pushing this cutting-edge technology into the mainstream. This work proposes a novel approach for improving geometry accuracy of AM parts in a systematic and efficient manner. Initial experimental data show that different part geometric features are not necessary positively correlated. Hence, it may not be possible to optimize them simultaneously. The proposed methodology formulates the geometry accuracy optimization problem as a multi-objective optimization problem. The developed method targeted minimizing deviations within part’s major Geometric Dimensioning and Tolerancing (GD&T) features (i.e., Flatness, Circularity, Cylindricity, Concentricity and Thickness). First, principal component analysis (PCA) is applied to extract key components within multi-geometric features of parts. Then, experiments are sequentially designed in an accelerated and integrated framework to achieve sets of process parameters resulting in acceptable level of deviations within principal components of multi-geometric features of parts. The efficiency of proposed method is validated using simulation studies coupled with a real world case study for geometry accuracy optimization of parts fabricated by fused filament fabrication (FFF) system. The results show that optimal designs are achieved by fewer numbers of experiments compared with existing methods.