Search results

Fabrication of customized products in low volume through conventional manufacturing incurs a high cost, longer processing time and huge material waste. Hence, the concept of additive manufacturing (AM) comes into existence and fused deposition modelling (FDM), is at the forefront of researches related to polymer-based additive manufacturing. The purpose of this paper is to summarize the research works carried on the applications of FDM.

In the present paper, an extensive review has been performed related to major application areas (such as a sensor, shielding, scaffolding, drug delivery devices, microfluidic devices, rapid tooling, four-dimensional printing, automotive and aerospace, prosthetics and orthosis, fashion and architecture) where FDM has been tested. Finally, a roadmap for future research work in the FDM application has been discussed. As an example for future research scope, a case study on the usage of FDM printed ABS-carbon black composite for solvent sensing is demonstrated.

The printability of composite filament through FDM enhanced its application range. Sensors developed using FDM incurs a low cost and produces a result comparable to those conventional techniques. EMI shielding manufactured by FDM is light and non-oxidative. Biodegradable and biocompatible scaffolds of complex shapes are possible to manufacture by FDM. Further, FDM enables the fabrication of on-demand and customized prosthetics and orthosis. Tooling time and cost involved in the manufacturing of low volume customized products are reduced by FDM based rapid tooling technique. Results of the solvent sensing case study indicate that three-dimensional printed conductive polymer composites can sense different solvents. The sensors with a lower thickness (0.6 mm) exhibit better sensitivity.

This paper outlines the capabilities of FDM and provides information to the user about the different applications possible with FDM.

The purpose of this paper is to design, implement and evaluate the usage of the password-authenticated secure channel protocol SRP to protect the communication of a mobile application to a Java Card applet. The usage of security and privacy sensitive systems on mobile devices, such as mobile banking, mobile credit cards, mobile ticketing or mobile digital identities has continuously risen in recent years. This development makes the protection of personal and security sensitive data on mobile devices more important than ever.

A common approach for the protection of sensitive data is to use additional hardware such as smart cards or secure elements. The communication between such dedicated hardware and back-end management systems uses strong cryptography. However, the data transfer between applications on the mobile device and so-called applets on the dedicated hardware is often either unencrypted (and interceptable by malicious software) or encrypted with static keys stored in applications.

To address this issue, this paper presents a solution for fine-grained secure application-to-applet communication based on Secure Remote Password (SRP-6a and SRP-5), an authenticated key agreement protocol, with a user-provided password at run-time.

By exploiting the Java Card cryptographic application programming interfaces (APIs) and minor adaptations to the protocol, which do not affect the security, the authors were able to implement this scheme on Java Cards with reasonable computation time.

This paper aims to present a hierarchical multiscale model to evaluate the effect of fused deposition modeling (FDM) process parameters on mechanical properties. Asymptotic homogenization mathematical theory is developed into two scales (micro and macro scales) to compute the effective elastic and shear modulus of the printed parts. Four parameters, namely, raster orientation, layer height, build orientation and porosity are studied.

The representative volume elements (RVEs) are generated by mimicking the microstructure of the printed parts. The RVEs subjected to periodic boundary conditions were solved using finite element. The experimental characterization according to ASTM D638 was conducted to validate the computational modeling results.

The computational model reports reduction (E1, ∼>38%) and (G12, ∼>50%) when porosity increased. The elastic modulus increases (1.31%–47.68%) increasing the orthotropic behavior in parts. Quasi-solids parts (100% infill) possess 10.71% voids. A reduction of 11.5% and 16.5% in elastic modulus with layer height is reported. In total, 45–450 oriented parts were highly orthotropic, and 0–00 parts were strongest. The order of parameters affecting the mechanical properties is porosity > layer height > raster orientation > build orientation.

This study adds value to the state-of-the-art terms of construction of RVEs using slicing software, discarding the necessity of image processing and study of porosity in FDM parts, reporting that the infill density is not the only measure of porosity in these parts.

Material extrusion additive manufacturing processes inevitably produce bead-shaped surface patterns on the walls of parts, which create stress concentrations under load. This study aims to investigate the influence of such stress concentrations on the strength along the build direction (“Z-strength”).

This work consists of two main parts – an experimental demonstration to show the significance of stress concentrations on the Z-strength, followed by numerical modeling to evaluate the theoretical stress concentration factors (k_t) for such shapes. Meso-scale finite element analysis (FEA) was performed to evaluate k_t at the roots of the intersecting bead shapes. The critical bead shape parameters influencing k_t were identified, and parametric FEA studies were performed on different bead shapes by varying the normalized parameters.

The experimental results showed that up to a 40% reduction in the effective Z-strength could be attributed only to the presence of surface bead shapes. Bead overhang and root radius were identified as critical shape parameters influencing k_t. The results of the parametric FEA studies were used to generate a single empirical equation to determine k_t for any bead shape.

Predictive models for Z-strength often focus on crystallization kinetics and polymer chain interdiffusion to predict interlayer adhesion strength. The authors propose that the results of such studies must be combined with surface bead-shape induced stress concentration factors to obtain the combined, “effective” Z-strength.

3D printing is gaining attention in the medical sector for the development of customized solutions for a wide range of applications such as temporary external implants. The materials used for the manufacturing process are critical, as they must provide biocompatibility and adequate mechanical properties. This study aims to evaluate and model the influence of the printing parameters on the mechanical properties of two biocompatible materials.

In this study, the mechanical properties of 3D-printed specimens of two biocompatible materials (ABS medical and PLActive) were evaluated. The influence of several printing parameters (infill density, raster angle and layer height) was studied and modelled on three response variables: ultimate tensile strength, deformation at the ultimate tensile strength and Young’s modulus. Therefore, statistical models were developed to predict the mechanical responses based on the selected printing parameters.

The used methodology allowed obtaining compact models that show good fit, particularly, for both the ultimate tensile strength and Young’s modulus. Regarding the deformation at ultimate tensile strength, this output was found to be influenced by more factors and interactions, resulting in a slightly less precise model. In addition, the influence of the printing parameters was discussed in the work.

The presented paper proposed the use of statistical models to select the printing parameters (infill density, raster angle and layer height) to optimize the mechanical response of external medical aids. The models will help users, researchers and firms to develop optimized solutions that can reduce material costs and printing time but guaranteeing the mechanical response of the parts.

The purpose of this study is to identify, analyse and model the post-processing barriers of 3D-printed medical models (3DPMM) printed by fused deposition modelling to overcome these barriers for improved operational efficiency in the Indian context.

The methodology used interpretive structural modelling (ISM), cross-impact matrix multiplication applied to classification (MICMAC) analysis and decision-making trial and evaluation laboratory (DEMATEL) to understand the hierarchical and contextual relations among the barriers of the post-processing.

A total of 11 post-processing barriers were identified in this study using ISM, literature review and experts’ input. The MICMAC analysis identified support material removal, surface finishing, cleaning, inspection and issues with quality consistency as significant driving barriers for post-processing. MICMAC also identified linkage barriers as well as dependent barriers. The ISM digraph model was developed using a final reachability matrix, which would help practitioners specifically tackle post-processing barriers. Further, the DEMATEL method allows practitioners to emphasize the causal effects of post-processing barriers and guides them in overcoming these barriers.

There may have been a few post-processing barriers that were overlooked by the Indian experts, which might have been important for other country’s perspective.

The presented ISM model and DEMATEL provide directions for operation managers in planning operational strategies for overcoming post-processing issues in the medical 3D-printing industry. Also, managers may formulate operational strategies based on the driving and dependence power of post-processing barriers as well as the causal effects relationships of the barriers.

This study contributes to identifying, analyzing and modelling the post-processing barriers of 3DPMM through a combined ISM and DEMATEL methodology, which has not yet been reviewed. This study also contributes to decision makers developing suitable strategies to overcome the post-processing barriers for improved operational efficiency.

This paper aims to investigate the effects of build parameters and strain rate on the mechanical properties of three-dimensional (3D) printed polylactic acid (PLA) by integrating digital image correlation and desirability function analysis. The build parameters included in this paper are the infill density, build orientation and layer height. These findings provide a framework for systematic mechanical characterization of 3D-printed PLA and potential ways of choosing process parameters to maximize performance for a given design.

The Taguchi method was used to shortlist a set of 18 different combinations of build parameters and testing conditions. Accordingly, 18 specimens were 3D printed using those combinations and put through a series of uniaxial tensions tests with digital image correlation. The mechanical properties deduced for all 18 tests were then used in a desirability function analysis where the mechanical properties were optimized to determine the ideal combination of build parameters and strain rate loading conditions.

By comparing the tensile mechanical experimental properties results between Taguchi's recommended parameters and the optimal parameter found from the response table of means, the composite desirability had increased by 2.08%. The tensile mechanical properties of the PLA specimens gradually decrease with an increase in the layer height, while they increase with increasing the infill densities. On the other hand, the mechanical properties have been affected by the build orientation and the strain rate in similar increasing/decreasing trends. Additionally, the obtained optimized results suggest that changing the infill density has a notable impact on the overall result, with a contribution of 48.61%. DIC patterns on the upright samples revealed bimodal strain patterns rendering them more susceptible to failures because of printing imperfections.

These findings provide a framework for systematic mechanical characterization of 3D-printed PLA and potential ways of choosing process parameters to maximize performance for a given design.

The purpose of this study is twofold: firstly, to investigate the effect of the infill value and build orientation on the fatigue behaviour of polylactic acid (PLA) specimens made by fused filament fabrication (FFF), also known as fused deposition modelling; and secondly, to model the fatigue behaviour of PLA specimens made by FFF and similar additive manufactured parts.

A new methodology based on filament characterisation, infill measuring, axial fatigue testing and fatigue strength normalisation is proposed and implemented. Sixty fatigue FFF specimens made of PLA were fabricated and evaluated using variable infill percentage and build orientation. On the other hand, fatigue modelling is based on the normalised stress amplitude and the fatigue life in terms of number of cycles. In addition, a probabilistic model was developed to predict the fatigue strength and life of FFF components.

The infill percentage and build orientation have a great influence on the fatigue behaviour of FFF components. The larger the infill percentage, the greater the fatigue strength and life. Regarding the build orientation, the specimens in the up-right orientation showed a much smaller fatigue strength and life than the specimens in the flat and on-edge orientations. Regarding the fatigue behaviour modelling, the proposed Weibull model can predict with an acceptable reliability the stress-life performance of PLA-FFF components.

This study has been limited to axial fatigue loading conditions along three different build orientations and only one type of material.

The results of this study are valuable to predict the fatigue behaviour of FFF parts that will work under variable loading conditions. The proposed model can help designers and manufacturer to reduce the need of experimental tests when designing and fabricating FFF components for fatigue conditions.

A fatigue study based on a novel experimental methodology that considers the variation of the FFF process parameters, the measurement of the real infill value and the normalisation of the results to be comparable with other studies is proposed. Furthermore, a new fatigue model able to predict the stress-life fatigue behaviour of PLA-FFF components considering variable process parameters is also proposed.

Two-level support with Level 1 consisting of a set of beams and Level 2 consisting of a tree-like structure is an efficient support structure for extrusion-based additive manufacturing (EBAM). However, the literature for finding a slim two-level support is rare. The purpose of this paper is to design a lightweight two-level support structure for EBAM.

To efficiently solve the problem, the lightweight design problem is split into two subproblems: finding a slim Level 1 support and a slim Level 2 support. To solve these two subproblems, this paper develops three efficient metaheuristic algorithms, i.e. genetic algorithm (GA), genetic programming (GP) and particle swarm optimization (PSO). They are problem-independent and are powerful in global search. For the first subproblem, considering the path direction is a critical factor influencing the layout of Level 1 support, this paper solves it by splitting the overhang region into a set of subregions, and determining the path direction (vertical or horizontal) in each subregion using GA. For the second subproblem, a hybrid of two metaheuristic algorithms is proposed: the GP manipulates the topologies of the tree support, while the PSO optimizes the position of nodes and the diameter of tree branches. In particular, each chromosome is encoded as a single virtual tree for GP to make it easy to manipulate Crossover and Mutation. Furthermore, a local strategy of geometric search is designed to help the hybrid algorithm reach a better result.

Simulation results show that the proposed method is preferred over the existing method: it saves the materials of the two-level support up to 26.34%, the materials of the Level 1 support up to 6.62% and the materials of the Level 2 support up to 37.93%. The proposed local strategy of geometric search can further improve the hybrid algorithm, saving up to 17.88% of Level 2 support materials.

The proposed approach for sliming Level 1 support requires the overhanging region to be a rectilinear polygon and the path direction in a subregion to be vertical or horizontal. This limitation limits the further material savings of the Level 1 support. In future research, the proposed approach can be extended to handle an arbitrary overhang region, each with several choices of path directions.

The details of how to integrate the proposed algorithm into the open-source program CuraEngine 4.13.0 is presented. This is helpful for the designers and manufacturers to practice on their own 3D printers.

The path planning of the overhang is a critical factor influencing the distribution of supporting points and will thus influence the shape of the support structure. Different from existing approaches that use single path directions, the proposed method optimizes the volume of the support structure by planning hybrid paths of the overhangs.

Intellectual capital (IC) is essential to the success of new technology-based firms. However, young firms only possess some of the resources and capabilities needed to develop, produce and market their innovative products and services. Hence, many form alliances to access complementary resources. This paper investigates the signaling effect of technology-based start-ups’ stock of IC on alliance formation.

This study analyzes primary data concerning specific classes of IC and the alliances formed. Data were collected from founders of 233 technology-based new ventures in the USA. Hypotheses were tested via hierarchical linear regression.

This study demonstrates that firms' IC, in the form of founders with doctorates and patents, is positively related to the classes of alliances formed. These stocks of IC send signals about credibility to the market for alliance partners, enabling the firms to form alliances and gain access to complementary resources. The number of founders with doctorates was positively related to R&D alliances and alliance partners in a similar place in the value chain as the focal firm. In contrast, the number of patents was positively related to total alliances, production-oriented alliances and alliances considered upstream from the focal firm.

This paper collects retrospective data from founders of technology-based new ventures. The research contributes to the literature with its results that founder human capital and patent portfolios are essential for technology-based firms' innovation and growth. However, little research has investigated how firms' possession of IC facilitates alliance formation. This paper investigates this connection explicitly.