A dynamic and static data based matching method for cloud 3D printing

3D printing is widely used in such sectors as industry, medical, sports and education with the rapid development 3D printing technology and continual breakthrough of new material technology. Faced with the continual expansion of 3D printing market and the diversity and rapid growth of the scale of 3D printing devices, efficiently manage 3D print resources in the environment of distributed network manufacturing is a critical problem urgently to resolve. As a novel business paradigm, Cloud manufacturing can effectively integrate and manage manufacturing resources. Therefore, based on the cloud manufacturing paradigm, this study focuses on dynamic and static data based matching method for cloud 3D printing. In this paper, we propose a modeling framework to describe two models of the print task and print resource by model-based systems engineering. This modeling framework can support the efficient matching of the two types of models. Finally, the dynamic and static data based matching method can realistically simulate the supply-demand matching process of cloud 3D printing platform and provide a technical solution for quick supply-demand matching of large-scale resources in the environment of cloud manufacturing. During in the modeling process, we not only consider the static characteristics of 3D printers and analyze quantitatively all the parameter indicators of static characteristics, but also consider the dynamic characteristics of 3D printers to establish a universal dynamic data acquisition system, which can be used for real-time monitoring and automatic diagnosis of the health status of 3D printers. Therefore, this matching method has important theoretical significance and engineering value.     

Nozzle condition monitoring in 3D printing

3D printing and particularly fused filament fabrication is widely used for prototyping and fabricating low-cost customized parts. However, current fused filament fabrication 3D printers have limited nozzle condition monitoring techniques to minimize nozzle clogging errors. Nozzle clogging is one of the most significant process errors in current fused filament fabrication 3D printers, and it affects the quality of the prototyped parts in terms of geometry tolerance, surface roughness, and mechanical properties. This paper proposes a nozzle condition monitoring technique in fused filament fabrication 3D printing using a vibration sensor, which is briefly described as follows. First, a bar mount that supports the liquefier in fused filament fabrication extruder was modeled as a beam excited by a system of process forces. The boundary conditions were identified, and the applied forces were analyzed for Direct and Bowden types of fused filament fabrication extruders. Second, a new 3D printer with a fixed extruder and a moving platform was designed and built for conducting nozzle condition monitoring experiments. Third, nozzle clogging was simulated by reducing the nozzle extrusion temperature, which caused partial solidification of the filament around inner walls of the nozzle. Fourth, sets of experiments were performed by measuring the vibrations of a bar mount during extrusion of polylactic acid, acrylonitrile butadiene styrene, and SemiFlex filaments via Direct and Bowden types of fused filament fabrication extruders. Findings of the current study show that nozzle clogging in fused filament fabrication 3D printers can be monitored using an accelerometer sensor by measuring extruder’s bar mount vibrations. The proposed technique can be used efficiently for monitoring nozzle clogging in fused filament fabrication 3D printers as it is based on the fundamental process modeling.     

3D printing: an emerging tool for novel microfluidics and lab-on-a-chip applications

In the past few years, 3D printing technology has witnessed an explosive growth, penetrating various aspects of our lives. Current best-in-class 3D printers can fabricate micrometer scale objects, which has made fabrication of microfluidic devices possible. The highest achievable resolution is already at nanometer scale, which is continuing to drop. Since geometric complexity is not a concern for 3D printing, novel 3D microfluidics and lab-on-a-chip systems that are otherwise impossible to produce with traditional 2D microfabrication technology have started to emerge in recent years. In this review, we first introduce the basics of 3D printing technology for the microfluidic community and then summarize its emerging applications in creating novel microfluidic devices. We foresee widespread utilization of 3D printing for future developments in microfluidic engineering and lab-on-a-chip technology.     

Recursive symmetries for geometrically complex and materially heterogeneous additive manufacturing

We present a generative method for the creation of geometrically complex and materially heterogeneous objects. By combining generative design and additive manufacturing, we demonstrate a unique form-finding approach and method for multi-material 3D printing. The method offers a fast, automated and controllable way to explore an expressive set of symmetrical, complex and colored objects, which makes it a useful tool for design exploration and prototyping. We describe a recursive grammar for the generation of solid boundary surface models suitable for a variety of design domains. We demonstrate the generation and digital fabrication of watertight 2-manifold polygonal meshes, with feature-aligned topology that can be produced on a wide variety of 3D printers, as well as post-processed with traditional 3D modeling tools. To date, objects with intricate spatial patterns and complex heterogeneous material compositions generated by this method can only be produced through 3D printing.     

Deep learning-based optimal segmentation of 3D printed product for surface quality improvement and support structure reduction

Large-sized product cannot be printed as one piece by a 3D printer because of the volume limitation of most 3D printers. Some products with the complex structure and high surface quality should also not be printed into one piece to meet requirement of the printing quality. For increasing the surface quality and reducing support structure of 3D printed models, this paper proposes a 3D model segmentation method based on deep learning. Sub-graphs are generated by pre-segmenting 3D triangular mesh models to extract printing features. A data structure is proposed to design training data sets based on the sub-graphs with printing features of the original 3D model including surface quality, support structure and normal curvature. After training a Stacked Auto-encoder using the training set, a 3D model is pre-segmented to build an application set by the sub-graph data structure. The application set is applied by the trained deep-learning system to generate hidden features. An Affinity Propagation clustering method is introduced in combining hidden features and geometric information of the application set to segment a product model into several parts. In the case study, samples of 3D models are segmented by the proposed method, and then printed using a 3D printer for validating the performance.     

Automatic balancing of 3D models

3D printing technologies allow for more diverse shapes than are possible with molds and the cost of making just one single object is negligible compared to traditional production methods. However, not all shapes are suitable for 3D print. One of the remaining costs is therefore human time spent on analyzing and editing a shape in order to ensure that it is fit for production. In this paper, we seek to automate one of these analysis and editing tasks, namely improving the balance of a model to ensure that it stands. The presented method is based on solving an optimization problem. This problem is solved by creating cavities of air and distributing dense materials inside the model. Consequently, the surface is not deformed. However, printing materials with significantly different densities is often not possible and adding cavities of air is often not enough to make the model balance. Consequently, in these cases, we will apply a rotation of the object which only deforms the shape a little near the base. No user input is required but it is possible to specify manufacturing constraints related to specific 3D print technologies. Several models have successfully been balanced and printed using both polyjet and fused deposition modeling printers.     

Landscaper: A Modeling System for 3D Printing Scale Models of Landscapes

Landscape models of geospatial regions provide an intuitive mechanism for exploring complex geospatial information. However, the methods currently used to create these scale models require a large amount of resources, which restricts the availability of these models to a limited number of popular public places, such as museums and airports. In this paper, we have proposed a system for creating these physical models using an affordable 3D printer in order to make the creation of these models more widely accessible. Our system retrieves GIS relevant to creating a physical model of a geospatial region and then addresses the two major limitations of affordable 3D printers, namely the limited number of materials and available printing volume. This is accomplished by separating features into distinct extruded layers and splitting large models into smaller pieces, allowing us to employ different methods for the visualization of different geospatial features, like vegetation and residential areas, in a 3D printing context. We confirm the functionality of our system by printing two large physical models of relatively complex landscape regions.     

PackMerger: A 3D Print Volume Optimizer

We propose an optimization framework for 3D printing that seeks to save printing time and the support material required to print 3D shapes. Three‐dimensional printing technology is rapidly maturing and may revolutionize how we manufacture objects. The total cost of printing, however, is governed by numerous factors which include not only the price of the printer but also the amount of material and time to fabricate the shape. Our PackMerger framework converts the input 3D watertight mesh into a shell by hollowing its inner parts. The shell is then divided into segments. The location of splits is controlled based on several parameters, including the size of the connection areas or volume of each segment. The pieces are then tightly packed using optimization. The optimization attempts to minimize the amount of support material and the bounding box volume of the packed segments while keeping the number of segments minimal. The final packed configuration can be printed with substantial time and material savings, while also allowing printing of objects that would not fit into the printer volume. We have tested our system on three different printers and it shows a reduction of 5–30% of the printing time while simultaneously saving 15–65% of the support material. The optimization time was approximately 1 min. Once the segments are printed, they need to be assembled.     

Clever Support: Efficient Support Structure Generation for Digital Fabrication

We introduce an optimization framework for the reduction of support structures required by 3D printers based on Fused Deposition Modeling (FDM) technology. The printers need to connect overhangs with the lower parts of the object or the ground in order to print them. Since the support material needs to be printed first and discarded later, optimizing its volume can lead to material and printing time savings. We present a novel, geometry‐based approach that minimizes the support material while providing sufficient support. Using our approach, the input 3D model is first oriented into a position with minimal area that requires support. Then the points in this area that require support are detected. For these points the supporting structure is progressively built while attempting to minimize the overall length of the support structure. The resulting structure has a tree‐like shape that effectively supports the overhangs. We have tested our algorithm on the MakerBot® Replicator? 2 printer and we compared our solution to the embedded software solution in this printer and to Autodesk® Meshmixer? software. Our solution reduced printing time by an average of 29.4% (ranging from 13.9% to 49.5%) and the amount of material by 40.5% (ranging from 24.5% to 68.1%).     

The predictive compensation path research of the micro tube fabrication process

Inkjet-based organ printing or 3D organ printing can be implemented using orifice-based and orifice-free approaches. Inkjetting, the most widely used orifice-based fabrication approach, has been applied to fabricate various biological constructs, such as alginate tubes. There are two main factors that may lead to failure during the fabrication of the tubular constructs with an overhang using horizontal printing: Structure instability due to the moment imbalance and structure failure due to the droplet impact-induced crash or buckling. This study aims to investigate how to theoretically construct a predicted tube printing path which can compensate for deformation in the printing process. First, we discuss the influence of stress in the printing process, subsequently we proceed to simulate the printing of the tube as a thin curved beam under droplet impact force, and obtain the unchanged shape information from the deformed shape, and then we put forward the predicted-path algorithm of the tube fabrication (PPATF). Second, we verify the method effectiveness and correctness by constructing the predicted path of a tube of 6 mm diameter and using finite element analysis (FEA) to simulate the deformation in the printing process. Lastly, we use the predicted path to print the tube. The cross section of the fabricated constructs can be nearly circular with the predictive compensation path.     

浅析行式热印字机的高速化途径

本文分析了不同控制方式对行式热印字机输出速度的影响。在此基础上提出了一种单ＣＰＵ高速行式热印字机的最优并发控制方式，并在设计实践中得到了验证。最后给出了提高行式热印字机印字输出速度的一般途径     

Diverse three-dimensional printing capacity planning for manufacturers

Three-dimensional (3D) printers are widely used in rapid prototyping and mass customization. However, capacity planning for 3D printers is challenging because 3D printers are usually not dedicated, and estimating the demand for their capacity is not easy. To overcome this problem, in this study, a consistent-decomposition (CD) fuzzy-analytic-hierarchy-process (FAHP) approach is proposed. This approach extracts the various viewpoints of a capacity planner by decomposing his or her fuzzy judgment matrix into several fuzzy subjudgment matrices. On the basis of each fuzzy subjudgment matrix, the performances of various 3D printers are assessed and compared. The best-performing 3D printer from each viewpoint is chosen. The proposed methodology has been applied to a real-world case in which a diverse set of 3D printers was acquired by a manufacturer. The proposed methodology returned a diverse set of optimal 3D printers, whereas a competing set chosen using any existing method lacked diversity. In addition, a decision maker who applied the proposed methodology did not need to specify different requirements for various types of 3D printers.     

Time and freestyle piling: a subjective approach to 3D printing

This paper considers the influence of 3D printers on the temporality and subjectivity of making by looking at current 3D printing processes through the concept of ‘duration’ that was theorized by the philosopher Henri Bergson. The discussion is contextualized within technological developments at the turn of the twentieth century—specifically, European railways—that changed our perception of time. The foundational ideas of duration are introduced as a response to these developments. The contemporary technological concept of ‘real-time computing’ is presented to contrast with duration and set up an in-depth explanation of the delays inherent to the 3D printing process. These delays are discussed within the discourse of 3D printing and technological innovation, in general. Current maker-3D printer interactions are then critiqued. Finally, an alternative method of 3D printing concrete that is founded on working with its inherent delays is introduced, along with its implications for digital making and the act of making time.     

Attribute driven process architecture for additive manufacturing

In additive manufacturing (AM) process, the manufacturing attributes are highly dependent upon the execution of hierarchical plan. Among them, material deposition plan can frequently interrupt the AM process due to tool-path changes, tool start-stop and non-deposition time, which can be challenging during free-form part fabrication. In this paper, the layer geometries for both model and support structure are analyzed to identify the features that create change in deposition modality. First, the overhanging points on the part surface are identified using the normal vector direction of the model surface. A k-th nearest point algorithm is implemented to generate the 3d boundary support contour which is used to construct the support structure. Both model and support structures are sliced and contours are evaluated. The layer contour, plurality, concavity, number of contours, geometric shape, size and interior islands are considered to generate an AM deposition model. The proposed model is solved for minimizing the change in deposition modality by maximizing the continuity and connectivity in the material deposition plan. Both continuity and connectivity algorithms are implemented for model and support structure for free-form object. The proposed algorithm provides the optimum deposition direction that results in minimum number of tool-path segments and their connectivity while minimizing contour plurality effect. This information is stored as a generic digital file format named Part Attributable Motion (PAM). A common application program interface (API) platform is also proposed in this paper, which can access the PAM and generate machine readable file for different existing 3D printers. The proposed research is implemented on three free-form objects with complex geometry and parts are fabricated. Also, the build time is evaluated and the results are compared with the available 3d printing software.     

Compound fabrication: A multi-functional robotic platform for digital design and fabrication

Supporting various applications of digital fabrication and manufacturing, the industrial robot is typically assigned repetitive tasks for specific pre-programmed and singular applications. We propose a novel approach for robotic fabrication and manufacturing entitled Compound Fabrication, supporting multi-functional and multi-material processes. This approach combines the major manufacturing technologies including additive, formative and subtractive fabrication, as well as their parallel integration. A 6-axis robotic arm, repurposed as an integrated 3D printing, milling and sculpting platform, enables shifting between fabrication modes and across scales using different end effectors. Promoting an integrated approach to robotic fabrication, novel combination processes are demonstrated including 3D printing and milling fabrication composites. In addition, novel robotic fabrication processes are developed and evaluated, such as multi-axis plastic 3D printing, direct recycling 3D printing, and embedded printing. The benefits and limitations of the Compound Fabrication approach and its experimental platform are reviewed and discussed. Finally, contemplation regarding the future of multi-functional robotic fabrication is offered, in the context of the experiments reviewed and demonstrated in this paper.     

Koala 3D: A continuous climbing 3D printer

The size of manufactured parts is naturally bound by the size of their production machines. In this paper, we explore the alternative of making a machine that can continuously navigate along an object being fabricated, producing objects larger than itself. The machine combines a climbing robot and a 3D printer. It uses an infinite fabrication loop which includes printing, reanchoring to a new station, and printing again. We present the design, construction, and characterization of the machine along with experiments on the fabrication of vertical columns. We also demonstrate the freeform fabrication capabilities of the machine by printing a moai statue. The results obtained have a wide range of applications for construction, product fabrication and promisingly broaden the current applications of 3D printing.     

Manufacture of microfluidic chips using a gap-control method based on traditional 3D printing technique

The solution to the commercialization of polymer microfluidic chips lies in the development of a low-cost and concise method. We present in this paper a gap-control method for obtaining low cost microfluidic chips on PMMA (polymethyl methacrylate) sheets based on traditional 3D printing technique—fused deposition modeling. The influence of 3D printing parameters such as printing temperature, printing speed, wire flow rate and initial layer thickness on printing quality is studied by experiments. The effect of O₂ plasma parameters such as chamber power and treatment time on the adhesion strength between printed PLA (polylactic acid) structures and PMMA substrate is investigated. The dye filling tests demonstrate that there is no blocking or leakage over the entire microchannels. With this newly developed technology, low-cost and large scale microfluidic chips can be fabricated, which allows commercial manufacturing of microchannels over large areas.

     

Fabrication of microfluidic channels based on melt-electrospinning direct writing

Microfluidics is a flourishing field, enabling a wide range of applications. However, the current fabrication methods for creating the microchannel structures of microfluidic devices, such as photolithography and 3D printing, mostly have the problems of time-consuming, high cost or low resolution. In this work, we developed a simple and flexible method to fabricate PDMS microfluidic channels, based on poly(ε-caprolactone) (PCL) master mold additive manufactured by a technique termed melt-electrospinning direct writing (MEDW). It relies on the following steps: (1) direct writing of micrometric PCL 2D or 3D pattern by MEDW. (2) Casting PDMS on the printed PCL pattern. (3) Peeling off of patterned PDMS from the embedded sacrificial PCL layer. (4) Bonding the PDMS with microchannel to another PDMS layer by hot pressing. The process parameters during MEDW such as collector speed, nozzle dimension and temperature were studied and optimized for the quality and dimension of the printed micropatterns. Multilayer fiber deposition was developed and applied to achieve microscale architectures with high aspect ratio. Thus, the microchannels fabricated by the proposed approach could possess tunable width and depth. Finally, T-shape and cross-channel devices were fabricated to create either laminar flow or microdroplets to illustrate the applicability and potential of this method for microfluidic device manufacture.     

A K/Ka‐band dielectric and metallic 3D printed aperture shared multibeam parabolic reflector antenna for satellite communication

A K/Ka‐band (22‐33 GHz) high‐gain aperture shared multibeam parabolic reflector antenna is proposed. It performs a two‐dimensional beam scanning from a shared single parabolic reflector by introducing off‐focal feeds. The feed array is placed on and off the focal of the parabolic reflector. Traditionally, the feed blockage has a great impact on the performance of the antenna, which reduces the gain and increases the sidelobe level. The purpose of this paper is to suppress the negative effects of feed blockage by using hybrid material processing method. Both dielectric and metallic 3D printing technologies are used for antenna fabrication. The parabolic reflector antenna is printed by selective laser melting using aluminum alloy. The feed array and the supporting structures are printed by stereolithography apparatus in resin to control the blockage. The method helps to suppress the sidelobe level from ?10 to ?15 dB and to enhance gain by up to 2.3 dBi. The reflection coefficient is less than ?10 dB, while the coupling coefficient between the ports is less than ?20 dB over the entire designed band. At 31.5 GHz, the simulated maximum gain of the antenna are 30.7, 29.1, and 29.7 dBi, when different port separately excites. Multiple beams at ±15° and 0° are observed on both E‐ and H‐planes. Besides, it also verifies the possibility to use dielectric and metallic 3D printing technologies in hybrid for microwave device fabrication.     

Dual‐color mixing for fused deposition modeling printers

In this work we detail a method that leverages the two color heads of recent low‐end fused deposition modeling (FDM) 3D printers to produce continuous tone imagery. The challenge behind producing such two‐tone imagery is how to finely interleave the two colors while minimizing the switching between print heads, making each color printed span as long and continuous as possible to avoid artifacts associated with printing short segments. The key insight behind our work is that by applying small geometric offsets, tone can be varied without the need to switch color print heads within a single layer. We can now effectively print (two‐tone) texture mapped models capturing both geometric and color information in our output 3D prints.