Search results

This paper endeavors to create a predictive model for the energy consumption associated with the multi-material fused deposition modeling (FDM) printing process.

An online measurement system for monitoring power and temperature has been integrated into the dual-extruder FDM printer. This system enables a comprehensive study of energy consumption during the dual-material FDM printing process, achieved by breaking down the entire dual-material printing procedure into distinct operational modes. Concurrently, the analysis of the G-code related to the dual-material FDM printing process is carried out.

This work involves an investigation of the execution instructions that delineate the tooling plan for FDM. We measure and simulate the nozzle temperature distributions with varying filament materials. In our work, we capture intricate details of energy consumption accurately, enabling us to predict fluctuations in power demand across different operational phases of multi-material FDM 3D printing processes.

This work establishes a model for quantifying the energy consumption of the dual-material FDM printing process. This model carries significant implications for enhancing the design of 3D printers and advancing their sustainability in mobile manufacturing endeavors.

Left atrial appendage occlusion (LAAO) is a structural interventional cardiology procedure that offers several possibilities for the application of additive manufacturing technologies. The literature shows a growing interest in the use of 3D-printed models for LAAO procedure planning and occlusion device choice. This study aims to describe a full workflow to create a 3D-printed LAA model for LAAO procedure planning.

The workflow starts with the patient’s computed tomography diagnostic image selection. Segmentation in a commercial software provides initial geometrical models in standard tessellation language (STL) format that are then preprocessed for print in dedicated software. Models are printed using a commercial stereolithography machine and postprocessing is performed.

Models produced with the described workflow have been used at the Careggi Hospital of Florence as LAAO auxiliary planning tool in 10 cases of interest, demonstrating a good correlation with state-of-the-art software for device selection and improving the surgeon’s understanding of patient anatomy and device positioning.

3D-printed models for the LAAO planning are already described in the literature. The novelty of the article lies in the detailed description of a robust workflow for the creation of these models. The robustness of the method is demonstrated by the coherent results obtained for the 10 different cases studied.

The purpose of this paper is to study the introduction of 3D-printing of concrete in the construction sector.

A survey was conducted to collect professional view on ongoing innovations in the construction sector, including 3D-printing. Participants were selected among the members of Norwegian networks for project and construction management research.

The survey highlighted effective leadership, collaboration with partners and industry-academia collaboration as primary enablers of innovation. Few of the respondents to the survey have used 3D-printing technologies.

It is difficult to obtain representative samples in this type of research, including this study. The study can be seen as a snapshot of attitudes in the sector.

3D-printing appear as a potentially interesting technology, especially for unstandardized construction components. Further work is needed to materialise the expectation for technological development in the construction sector.

Most research on 3D-printing has focused on demonstrating technical potential. This study adds a practitioners’ perspective, with a large dose of pragmatism.

The purpose of this paper is to evaluate and exploit the combination of additive manufacturing polymeric technology and structural adhesives. The main advantage is to expand the maximum dimension of the 3D printed parts, which is typically limited, by joining the parts with structural adhesive, without losing strength and stiffness and keeping the major asset of polymeric 3 D printing: freedom of shape of the system and low cost of parts.

The materials used in the paper are the following. The adhesive considered is a commercial inexpensive acrylic, quite similar to superglue, applicable with almost no surface preparation and fast curing, as time constraint is one of the key problems that affects industrial adhesive applications. The 3D printed parts were in acrylonitrile butadiene styrene (ABS), obtained with a Fortus 250mc FDM machine, from Stratasys. The work first compares flat overlap joint with joints designed to permit mechanical interlocking of the adherends and then to a monolithic component with the same geometry. Single lap, joggle lap and double lap joints are the configurations experimentally characterized following a design of experiment approach.

The results show a failure in the substrate, due to the low strength of the polymeric adherends for the first batch of typical bonded configurations, single lap, joggle lap and double lap. The central bonded area, with an increased global thickness, never does fail, and the adhesive is able to transfer the load both with and without mechanical interlocking. An additional set of scarf joints was also tested to promote adhesive failure as well as to retrieve the adhesive strength in this application. The results shows that bonding of polymeric AM parts is able to express its full potential compared with a monolithic solution even though the joint fails prematurely in the adherend due to the bending stresses and the notches present in the lap joints.

Because of the 3D printed polymeric material adopted, the results may be generalized only when the elastic properties of the adherends and of the adhesive are similar, so it is not possible to extend the findings of the work to metallic additive manufactured components.

The paper shows that the adhesives are feasible way to expand the potentiality of 3 D printed equipment to obtain larger parts with equivalent mechanical properties. The paper also shows that the scarf joint, which fails in the adhesive first, can be used to extract information about the adhesive strength, useful for the designers which have to combine adhesive and additive manufactured polymeric parts.

To the best of the researchers’ knowledge, there are scarce quantitative information in technical literature about the performance of additive manufactured parts in combination with structural adhesives and this work provides an insight on this interesting subject. This manuscript provides a feasible way of using rapid prototyping techniques in combination with adhesive bonding to fully exploit the additive manufacturing capability and to create large and cost-effective 3 D printed parts.

The study aims to investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand patterns.

This work evaluates various AM-enabled supply chain configurations through Monte Carlo simulation. Historical demand simulation and intermittent demand forecasting are used in conjunction with a mixed integer linear program to determine optimal network nodal inventory policies. By varying demand characteristics and AM capacity this work assesses how to best employ AM capability within the network.

This research assesses the preferred AM-enabled supply chain configuration for varying levels of intermittent demand patterns and AM production capacity. The research shows that variation in demand patterns alone directly affects the preferred network configuration. The relationship between the demand volume and relative AM production capacity affects the regions of superior network configuration performance.

This research makes several simplifying assumptions regarding AM technical capabilities. AM production time is assumed to be deterministic and does not consider build failure probability, build chamber capacity, part size, part complexity and post-processing requirements.

This research is the first study to link realistic spare part demand characterization to AM supply chain design using quantitative modeling.

The purpose of this study is to assess a novel method for creating tangible three-dimensional (3D) morphologies (scaled models) of neuronal reconstructions and to evaluate its cost-effectiveness, accessibility and applicability through a classroom survey. The study addresses the challenge of accurately representing intricate and diverse dendritic structures of neurons in scaled models for educational purposes.

The method involves converting neuronal reconstructions from the NeuromorphoVis repository into 3D-printable mold files. An operator prints these molds using a consumer-grade desktop 3D printer with water-soluble polyvinyl alcohol filament. The molds are then filled with casting materials like polyurethane or silicone rubber, before the mold is dissolved. We tested our method on various neuron morphologies, assessing the method’s effectiveness, labor, processing times and costs. Additionally, university biology students compared our 3D-printed neuron models with commercially produced counterparts through a survey, evaluating them based on their direct experience with both models.

An operator can produce a neuron morphology’s initial 3D replica in about an hour of labor, excluding a one- to three-day curing period, while subsequent copies require around 30 min each. Our method provides an affordable approach to crafting tangible 3D neuron representations, presenting a viable alternative to direct 3D printing with varied material options ensuring both flexibility and durability. The created models accurately replicate the fidelity and intricacy of original computer aided design (CAD) files, making them ideal for tactile use in neuroscience education.

The development of data processing and cost-effective casting method for this application is novel. Compared to a previous study, this method leverages lower-cost fused filament fabrication 3D printing to create accurate physical 3D representations of neurons. By using readily available materials and a consumer-grade 3D printer, the research addresses the high cost associated with alternative direct 3D printing techniques to produce such intricate and robust models. Furthermore, the paper demonstrates the practicality of these 3D neuron models for educational purposes, making a valuable contribution to the field of neuroscience education.

This paper aims to focus on 11 digital technologies (i.e. building information modeling, artificial intelligence and machine learning, 3D scanning, sensors, robots/automation, digital twin, virtual reality, 3D printing, drones, cloud computing and self-driving vehicles) that are portrayed in future trend reports and hype curves. The study concentrates on the current usage and knowledge of digital technologies in the Swedish architecture, engineering and construction (AEC) industry to gain an insight in the possible expectations and future trajectory of these digital technologies.

The study applies an abductive approach which is based on three different types of methods. These methods are a literature and document study which focused on 11 digital technologies, two workshops with industry (13 participants) and an online survey (N = 84).

The paper contributes to a current state analysis of the Swedish AEC industry concerning digital technologies and discusses the trajectory of these technologies for the AEC industry. The paper identifies hype factors, in which the knowledge of a digital technology is related to its usage. From the hype factors, four zones that show different stages of digital technology usage and maturity in the industry are induced.

The contribution of the paper is twofold. The paper shows insight into opportunities, the current barriers, use and knowledge of digital technologies for the different actors in the AEC industry. Furthermore, the study shows that the AEC industry is behind the traditional Gartner hype curves and contributes with defining four zones for digital technologies for the Swedish AEC industry: confusion, excitement, experimentation and integration.

This paper aims to report on the findings of an investigation to compare three different three-dimensional printing (3DP) or additive manufacturing technologies [i.e. fused deposition modeling (FDM), stereolithography (SLA) and material jetting (MJ)] and four different equipment (FDM, SLA, MJP 2600 and Object 260) in terms of their dimensional process capability (dimensional accuracy and surface roughness). It provides a comprehensive and comparative understanding about the level of attainable dimensional accuracy, repeatability and surface roughness of commonly used 3DP technologies. It is expected that these findings will help other researchers and industrialists in choosing the right technology and equipment for a given 3DP application.

A benchmark model of 5 × 5 cm with several common and challenging features, such as around protrusion and hole, flat surface, micro-scale ribs and micro-scale long channels was designed and printed repeatedly using four different equipment of three different 3DP technologies. The dimensional accuracy of the printed models was measured using non-contact digital measurement methods. The surface roughness was evaluated using a digital profilometer. Finally, the surface quality and edge sharpness were evaluated under a reflected light ZEISS microscope with a 50× magnification objective.

The results show that FDM technology with the used equipment results in a rough surface and loose dimensional accuracy. The SLA printer produced a smoother surface, but resulted in the distortion of thin features (<1 mm). MJ printers, on the other hand, produced comparable surface roughness and dimensional accuracy. However, ProJet MJP 3600 produced sharper edges when compared to the Objet 260 that produced round edges.

This paper, for the first time, provides a comprehensive comparison of three different commonly used 3DP technologies in terms of their dimensional capability and surface roughness without farther post-processing. Thus, it offers a reliable guideline for design consideration and printer selection based on the target application.