This project was funded by the Natural Sciences and Engineering Research Council (NSERC) of Canada Industrial Research Chair in Automated Composites Manufacturing and the Fonds de recherche du Qu&#233;bec &#8211; Natrue et technologies (FRQNT).

1. Frame Definitions of the CCM system
NOTE: The optical CMM is a dual camera sensor, which can track the object with a rigid set of reflectors as the targets in real time. The placement principle of these targets is that the targets are stuck at the asymmetric locations with certain distance among them. The targets need to be fixed on the robots or the placement head and remain in the field of view (FOV) of the optical CMM. At least four targets should be observed for each defined frame by the optical CMM all the time. The base frame of the parallel robot, the end-effector frame of the parallel robot, and the tool frame of the serial robot are denoted as Fb, FtP, and FtS, respectively. The definitions of those frames are shown in Figure 1. Because the base frames of the parallel robot and the serial robot are fixed, the transformation matrix between the two base frames can be derived by calibration.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/59969/59969fig1.jpg" /> 
Figure 1. Collaborative Composite Manufacturing (CCM) System Setup. The hardware of the CCM system consists of a 6-RSS parallel robot, a 1-DoF rotational stage, a 6-DoF serial robot, a placement head, and the optical CMM. The mandrel is clamped on the rotational stage, and the rotational stage is mounted on the parallel robot. <a href="https://www.jove.com/files/ftp_upload/59969/59969fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol>
	<li>Definition of the base frame of the parallel robot
	<ol>
		<li>Load the frame definition file through the software of the optical CMM (see the Table of Materials).</li>
		<li>Click Positioning &#62; Detect Targets. Select the targets that are attached on the motors of the parallel robot. Click Accept to take those targets as the positioning reference of the whole system.</li>
		<li>In the Entities list, click Base Frame and select Make this Reference Frame the Origin. 
		NOTE: The purpose of Step 1.1 is to take Fb as the reference frame of the whole system. The frame definition file can be obtained at the following link: &#60;https://users.encs.concordia.ca/~wfxie/Jove_program/P3.csf&#62;.</li>
	</ol>
	</li>
	<li>Definition of the tracking model of the end-effector platform frame
	<ol>
		<li>Select Tracking Models in the navigation area. Click Detect Model, and then select the targets fixed on the end-effector platform of the parallel robot. Click Accept.</li>
		<li>Click the generated detection model. Select Up_Frame in the drop-down list of the Origin Offset. Then click Apply. 
		NOTE: This step is to set up the fixed relationships between the end-effector platform frame FtP and the targets attached on the end-effector platform.</li>
		<li>Click File-Export-Tracking model, and enter a file name to save the tracking model.</li>
	</ol>
	</li>
	<li>Definition of the tracking model of the tool frame
	<ol>
		<li>Select Tracking Models. Click Detect Model, then select the targets fixed on the tool frame of the serial robot. Click Accept.</li>
		<li>Click the generated detection model. Select SerToolFrame in the drop-down list of the Origin offset. Click Apply and save the defined tracking model.</li>
	</ol>
	</li>
</ol>
2. System Preparation
NOTE: The control system layout of the CCM system is shown in Figure 2.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/59969/59969fig2.jpg" /> 
Figure 2. System Layout. Two computers (A &#38; B) are used for controlling the CCM system. The communication between them is via RS232. Computer A controls the rotational state, photogrammetry senor and serial robot. Computer B controls the parallel robot, motors and valves etc. <a href="https://www.jove.com/files/ftp_upload/59969/59969fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol>
	<li>Preparation of the rotational stage
	<ol>
		<li>Load the integrated control interface programed by event-driven programming language on computer A. 
		NOTE: The control interface is shown in Figure 3. The interface program can be obtained at the following link: &#60;https://users.encs.concordia.ca/~wfxie/Jove_program/pcdk-ctrack.rar&#62;.</li>
		<li>Click Connect to connect the controller of the rotational stage. Click Enable to connect the motor of rotational stage. Then click Home to move the rotational stage to the home position.</li>
	</ol>
	</li>
</ol>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/59969/59969fig3.jpg" /> 
Figure 3. Control Interface. The control software programmed by event-driven programming language. The interface is composed of 6 sections: serial robot, parallel robot, rotational stage, path import, optical CMM and cooperative control. <a href="https://www.jove.com/files/ftp_upload/59969/59969fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol start="2">
	<li>Preparation of the serial robot
	<ol>
		<li>Power on the controller of the serial robot (see the Table of Materials).</li>
		<li>Click Connect on the integrated control interface to connect the robot server.</li>
	</ol>
	</li>
	<li>Preparation of the Optical CMM
	<ol>
		<li>Power on the controller of the optical CMM and wait until the screen of the controller shows Ready.</li>
		<li>Click Connect on the integrated control interface to connect the optical CMM via Application Programming Interface (API).</li>
		<li>Import the models built in section 1, which includes the Base model, the Upper platform model and the End-effector model of the serial robot.</li>
		<li>Click Add Sequence. Add the relative sequence between the models if it is necessary. Then click Start Tracking to track the pose of the models.</li>
	</ol>
	</li>
	<li>Preparation of the Parallel robot
	<ol>
		<li>Power on the controller of the parallel robot.</li>
		<li>Load the SerialPort_Receive program and select Normal mode. 
		NOTE: The SerialPort_Receive program cannot control the parallel robot directly. It is used to receive the remote data from computer A via serial communication port. The SerialPort_Receive program can be obtained at the following link: &#60;https://users.encs.concordia.ca/~wfxie/Jove_program/SerialPort_Receive.mdl&#62;.</li>
		<li>Load the ParaRemoteControl program and select External mode. Then click Incremental Build to connect to target. 
		NOTE: The ParaRemoteControl program is used to receive the desired pose from SerialPort_Receive program and control the parallel robot. The ParaRemoteControl program can be obtained at the following link: &#60;https://users.encs.concordia.ca/~wfxie/Jove_program/ParaRemoteControl.mdl&#62;.</li>
		<li>Click Start Simulation of the two programs to initialize the controller of the parallel robot.</li>
	</ol>
	</li>
</ol>
3. Generating the off-line path
<ol>
	<li>Load the path planning interface through the numerical computing software (see the Table of Materials). 
	NOTE: The interface is shown in Figure 4. The path planning interface is the off-line software to generate the path for the system and can be obtained at the following link: &#60;https://users.encs.concordia.ca/~wfxie/Jove_program/AFP_PathPlanning_Pcode.zip&#62;.</li>
</ol>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/59969/59969fig4.jpg" /> 
Figure 4. Path Planning Interface. The path planning software is composed of 3 sections: Visual Area, Command Area and Information Box. The &#34;Viewing Area&#34; section allows the 3D display of the parts to be processed. The &#34;Command Area&#34; section is to perform the main actions for generating the off-line path. The &#34;Information Box&#34; section displays the information about the status of the program. <a href="https://www.jove.com/files/ftp_upload/59969/59969fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol start="2">
	<li>Click Import STL and choose the part file. Then click Segmentation. 
	NOTE: The part is divided into separated regions (cylinders and junctions of Y-shape part). The different regions are displayed in different colors.</li>
	<li>Click Add Work Region and select the region on the extraction of cylinders.</li>
	<li>Adjust the slider to 100% and click Extract Cylinders.</li>
	<li>Click Add Work Region to select the starting branch of the path.</li>
	<li>Click Generate Path. Choose the third option: Constant Placement Angle (CPA) in the pop-up dialog window.</li>
	<li>Choose the desired placement angle 90&#176; in the pop-up dialogue window. Then choose the red dot.</li>
	<li>To display the generated path, click Select a Path drop-down menu. Then, select the path.</li>
	<li>To save this path, click File &#62; Save and enter a file name.</li>
</ol>
4. Individual decomposition of the trajectory for the serial robot and rotational stage
<ol>
	<li>Run the Methode_Jacobian function in the numerical computing software (see Table of Materials). 
	NOTE: Methode_Jacobian function is used to decompose the generated path in Step 3 into two individual trajectories for the serial robot and the rotational stage.</li>
	<li>Select the desired path file (generated by path planning interface) and click open.</li>
	<li>Enter the desired path number.</li>
	<li>The first point of the trajectory is then calculated. Choose the desired configuration for the manipulator to reach this pose. 
	NOTE: When Step 4.4 is completed, a graph showing the evolution of joint values is displayed. A file containing the trajectory for the serial robot and the rotational stage is generated.</li>
</ol>
5. Running the off-line path without the path modification algorithm
<ol>
	<li>Press Select on the teach pendant and choose the name of the imported file. Press Enter to load the path file.</li>
	<li>Turn the switch of the robot controller to Auto mode. Turn the teach pendant ON/OFF switch to Off.</li>
	<li>Press Cycle Start of the controller of the serial robot to run the path.</li>
	<li>Click Cooperative Move located at the Cooperative Control panel. 
	NOTE: The system will execute the offline path without the on-line path modification algorithm. If the joint reaches to the singularity or constraint condition, the system will stop.</li>
</ol>
6. Running the off-line path with the path modification algorithm
<ol>
	<li>Repeat steps 5.1&#8211;5.3. Then click DPM Connect located at the Cooperative Control panel in Figure 3 to add the on-line path modification ability for the system.</li>
	<li>Click Cooperative Move located at the Cooperative Control panel. 
	NOTE: The system will execute the offline path with the on-line path modification algorithm. During the execution, the singularities and joints&#8217; constraints are monitored through the encoder measurement of the serial robot. The system can smoothly pass the singularity or constraint limitation points without termination.</li>
</ol>

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The authors have nothing to disclose.

The experimental results show the manufacturing process of 90&#176; ply placement angles of the designed CCM system. The methodologies proposed in this paper can be used to lay up the fiber with 0&#176; and 45&#176; ply placement angles on the mandrel with Y-Shape and other shapes. While the built-in controller of the serial robot is able to provide the singularity avoidance feature17, only linear movement of the end-effector is supported. When the end-effector executes the task of the circle move...

Recently, the increasing need for high performance composite structures in various industries has greatly driven the development of the composite manufacturing technologies1,2. The traditional manual production cannot meet the high efficiency, accuracy and quality requirement of emerging industry. This aspect has encouraged the development of new production technologies such as AFP systems. The AFP technology automates the production of composite material structures using prepregs, which are present in the form of strips composed of impregnated fiber tapes (glass, carbon, etc.) of semi-polymerized resin. In the AFP system, a deposition head with the ability of heating and compacting the resin prepregs is mounted on a fiber placement machine or an industrial robot. The fiber placement machine or robot carrying the deposition head lays up the prepregs traversing the surface of the tooling mandrels. In the process of manufacturing, the tooling mandrel is used as a mold to be wound around by the prepregs to form a certain structure of composite part. The mandrel will be removed after the part is cured. The current AFP systems can significantly improve the efficiency and quality of the production of composite materials3,4,5. However, they are limited to the production of the open surfaces presenting a flat or contoured surface, or simple revolution parts such as cylinders or cones due to the insufficient DoF of the system and the difficulties in generating trajectories. Especially, the aerospace industry and the production industries of sports equipment are now interested in this technique for the production of structures with more complex geometries, like &#34;Y&#34; tubes or the structures forming closed-loops such as bicycle frames.
To be able to manufacture the structures with complex geometries, the flexibility of the AFP system should be improved. For example, an 8 DoF AFP system has been proposed6 by adding a linear track to a 6 DoF industrial robot and a rotational stage to the mandrel holding platform. However, the system is still not suitable for manufacturing the above-mentioned parts with complex geometries. The collaborative robotic system consisting of two robots is a promising solution to increase the dexterity by employing one robot to hold the fiber placement head at the end-effector and another robot to hold the mandrel. The two-serial-robot collaborative system may not solve the fiber placement problem, since the serial robots tend to deform and lose the accuracy due to its cantilever structure, considering the weight of the mandrel and the compaction force7. Compared with the serial robots, 6 DoF parallel robots, which have been utilized in the flight simulator and medical tools, enjoy better stiffness and accuracy8. Therefore, a parallel-serial collaborative robot system, in additional to a rotational stage mounted on the platform of the parallel robot, is built for handling the complex structures manufacturing in this paper.
However, the built collaborative robotic system yields difficulties in designing the controller for each robot to meet the high accuracy requirement of fiber placement. The accurate position measurement of the end-effector could be achieved by using laser tracking system, which is commonly used to guide the industrial robot in various aerospace drilling applications9,10. Although the laser tracking system can provide high accurate position measurement, the main drawbacks lie in the cost of the system and the occlusion issue. The laser tracking system is expensive, e.g., a commercial laser tracker and its accessories cost up to US$90,000, and the laser beam is easily occluded during the movement of the robots. Another promising solution is the vision measurement system, which can provide 6D pose measurement of the end-effector with a considerable accuracy at a low cost. The pose is referred to as the combination of the 3D position and 3D orientation of the end-effector with respect to the base frame of the robot. The optical CMM (see Table of Materials) is a dual camera-based visual sensor. By observing several reflector targets attached on the end-effectors of the two robots, the relative poses between the robots can be measured in real time. The optical CMM has been successfully applied to the robotic calibration11 and dynamic path tracking12 and thus is introduced to provide the feedback measurement to the closed-loop control systems of the proposed CCM system in this study.
The quality of the end composite product is largely dependent on how the original fiber path is generated for the AFP13,14. The path generation process is normally performed by using off-line programming software. The generated path consists of a series of tag points on the mandrel, which indicate the pose of the fiber placement head. Unlike other trajectory planning applications such as paint deposition, polishing or machining, where different types of coverage paths are possible, the choice is limited in the case of AFP, since the fiber is continuous and it is not possible to perform abrupt changes in direction (sharp corners) without damaging it and the placement head should be kept in the norm of the surface of the parts. The first development of trajectory generation technique for AFP has been concentrated on manufacturing large flat panels5 before moving towards the manufacturing the objects of 3D shapes such as open curved surfaces or cones5,14. But, no practical methodology has been developed for generating off-line path for the parts with complex geometries such as Y-shape or the other shapes. Therefore, an effective path planning algorithm for the parts with complex-contoured surfaces is designed to ensure uniform lay-up of subsequent fibers without gaps or overlaps in our previous research15. Considering the practicality and the effectiveness of the path generating algorithm, only the 6-DoF serial robot with the placement head and 1-DoF rotational stage as the mandrel holder are considered as the target system to find the optimum trajectory planning in joint space with minimum time criteria. It could be too complicated and time-consuming to generate the off-line trajectory for the whole 13 DoF CCM system due to the heavy kinematics calculation and the consideration of various constraints like singularities, collisions, smooth direction changing and keeping the placement head in the norm of the parts surface, etc.
The proposed off-line trajectory planning can generate the servo reference for the 6 DoF serial robot and the rotational stage respectively with exact timing. Even with this off-line trajectory planning, it could be impossible to generate a feasible path under all the constraints for certain geometry parts. Moreover, the positioning errors of the robots may cause the robots to collide with the mandrel or another device in the working environment. The on-line path modification is implemented based on the visual feedback from the optical CMM. Therefore the on-line pose correction algorithm is proposed to correct the path of the parallel robot and to tune a corresponding offset on the path of the serial robot simultaneously through the visual feedback. When the collision and other constraints are detected, the relative pose between the two robots is also kept unchanged while following the off-line generated path. Through the correction of the on-line path, the CCM system can avoid these points smoothly without any termination. Due to the flexibility of the parallel robot, the 6D correction offsets can be generated with respect to different constraints. This manuscript presents a detailed operation procedure of the CCM system using on-line pose correction algorithm.

<table><tbody><tr><td>AeroBasic</td><td>Aerotech</td><td></td><td>Motion control software</td></tr><tr><td>Collaborative Composite Manufacturing (CCM) System</td><td>Concordia University</td><td></td><td>A CCM system is proposed to manufacture more complex composite components which pose high demand for trajectory planning than those by the current AFP system. The system consists of a 6 degree-of-freedom (DOF) serial robot holding the fiber placement head, a 6-DOF revolute-spherical-spherical (RSS) parallel robot on which a 1-DOF mandrel holder is installed and an eye-to-hand optical CMM sensor, i.e. C-track, to detect the poses of both end-effectors of parallel robot and serial robot.</td></tr><tr><td>C-track</td><td>Creaform Inc.</td><td></td><td>An eye-to-hand optical CMM sensor</td></tr><tr><td>Fanuc M-20iA</td><td>Fanuc Inc.</td><td></td><td>Serial robot</td></tr><tr><td>Matlab</td><td>MathWorks</td><td></td><td>A multi-paradigm numerical computing software</td></tr><tr><td>Quanser</td><td>Quanser Inc.</td><td></td><td>Providing the engineering lab equipments for teaching and research.</td></tr><tr><td>VB</td><td>Microsoft</td><td></td><td>Visual Basic</td></tr><tr><td>Vxelements</td><td>Creaform Inc.</td><td></td><td>Software for C-track</td></tr></tbody></table>

operation of the collaborative composite manufacturing (ccm) system

The automated tape placement and the automated fiber placement (AFP) machines provide a safer working environment and reduce the labor intensity of workers than the traditional manual fiber placement does. Thus, the production accuracy, repeatability and efficiency of composite manufacturing are significantly improved. However, the current AFP systems can only produce the composite components with large open surface or simple revolution parts, which cannot meet the growing interest in small complex or closed structures from industry.
In this research, by employing a 1-degree of freedom (DoF) rotational stage, a 6-RSS parallel robot, and a 6-DoF serial robot, the dexterity of the AFP system can be significantly improved for manufacturing complex composite parts. The rotational stage mounted on the parallel robot is utilized to hold the mandrel and the serial robot carries the placement head to mimic two human hands that have enough dexterity to lay the fiber to the mandrel with complex contour.
Although the CCM system increases the flexibility of composite manufacturing, it is quite time-consuming or even impossible to generate the feasible off-line path, which ensures uniform lay-up of subsequent fibers considering the constraints like singularities, collisions between the fiber placement head and mandrel, smooth fiber direction change and keeping the fiber placement head along the norm of the part&#39;s surface, etc. Moreover, due to the existing positioning error of the robots, the on-line path correction is needed. Therefore, the on-line pose correction algorithm is proposed to correct the paths of both parallel and serial robots, and to keep the relative path between the two robots unchanged through the visual feedback when the constraint or singularity problems in the off-line path planning occur. The experimental results demonstrate the designed CCM system can fulfill the movement needed for manufacturing a composite structure with Y-shape.

The experiment aims at demonstrating the process of realizing the motion of laying up the fiber on the Y-shape mandrel of the proposed CCM system. The process is carried out in three steps: path generation; trajectory decomposition; and singularity and constraint avoidance.
Path generation 
Normally, the standard orientation is used in industry to define the different plies of the laminate. In this paper, t...

Watch this Scientific Journal Video about Operation of the Collaborative Composite Manufacturing CCM System at JoVE.com

Operation of the Collaborative Composite Manufacturing CCM System

A collaborative composite manufacturing system is developed for robotic lay-up of composite laminates using the prepreg tape. The proposed system allows the production of composite laminates with high levels of geometrical complexity. The issues in the path planning, coordination of the robots and control are addressed in the proposed method.

Operation of the Collaborative Composite Manufacturing (CCM) System

The automated tape placement and the automated fiber placement (AFP) machines provide a safer working environment and reduce the labor intensity of ...

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6.5K Views.  Concordia University. A collaborative composite manufacturing system is developed for robotic lay-up of composite laminates using the prepreg tape. The proposed system allows the production of composite laminates with high levels of geometrical complexity. The issues in the path planning, coordination of the robots and control are addressed in the proposed method.

Video: Operation of the Collaborative Composite Manufacturing CCM System

Manufacturing of Three-dimensionally Microstructured Nanocomposites through Microfluidic Infiltration

Microstructured composite beams reinforced with complex three-dimensionally (3D) patterned nanocomposite microfilaments are fabricated via nanocomposite in&#64257;ltration of 3D interconnected microfluidic networks. The manufacturing of the reinforced beams begins with the fabrication of microfluidic networks, which involves layer-by-layer deposition of fugitive ink filaments using a dispensing robot, filling the empty space between filaments using a low viscosity resin, curing the resin and finally removing the ink.&#160;Self-supported 3D structures with other geometries and many layers (e.g.&#160;a few hundreds layers) could be built using this method. The resulting tubular micro&#64258;uidic networks are then infiltrated with thermosetting nanocomposite suspensions containing nanofillers (e.g.&#160;single-walled carbon nanotubes), and subsequently cured. The infiltration is done by applying a pressure gradient between two ends of the empty network (either by applying a vacuum or vacuum-assisted microinjection). Prior to the infiltration, the nanocomposite suspensions are prepared by dispersing nanofillers into polymer matrices using ultrasonication and three-roll mixing methods. The nanocomposites (i.e.&#160;materials infiltrated) are then solidified under UV exposure/heat cure, resulting in a 3D-reinforced composite structure. The technique presented here enables the design of functional nanocomposite macroscopic products for microengineering applications such as actuators and sensors.

Three-dimensional (3D) microstructured composite beams are fabricated through the directed and localized infiltration of nanocomposites into 3D porous microfluidic networks. The flexibility of this manufacturing method enables the utilization of different thermosetting materials and nanofillers in order to achieve a variety of functional 3D reinforced nanocomposite macroscopic products.

Microstructured composite beams reinforced with complex three-dimensionally (3D) patterned nanocomposite microfilaments are fabricated via nanocomposite ...

Chemistry

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes

The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substitution of steel components with aluminum alloy alternatives in the automotive and aerospace sectors has increased the need to simulate the forming behavior of such alloys for ever more complex component geometries. However these alloys, and in particular their high strength variants, exhibit limited formability at room temperature, and high temperature manufacturing technologies have been developed to form them. Consequently, advanced constitutive models are required to reflect the associated temperature and strain rate effects. Simulating such behavior is computationally very expensive using conventional FE simulation techniques.
This paper presents a novel Knowledge Based Cloud FE (KBC-FE) simulation technique that combines advanced material and friction models with conventional FE simulations in an efficient manner thus enhancing the capability of commercial simulation software packages. The application of these methods is demonstrated through two example case studies, namely: the prediction of a material's forming limit under hot stamping conditions, and the tool life prediction under multi-cycle loading conditions.

The following paper presents a novel FE simulation technique (KBC-FE), which reduces computational cost by performing simulations on a cloud computing environment, through the application of individual modules. Moreover, it establishes a seamless collaborative network between world leading scientists, enabling the integration of cutting edge knowledge modules into FE simulations.

The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the ...

Microfluidic Fabrication of Polymeric and Biohybrid Fibers with Predesigned Size and Shape

A &#8220;sheath&#8221; fluid passing through a microfluidic channel at low Reynolds number can be directed around another &#8220;core&#8221; stream and used to dictate the shape as well as the diameter of a core stream.&#160;Grooves in the top and bottom of a microfluidic channel were designed to direct the sheath fluid and shape the core fluid.&#160;By matching the viscosity and hydrophilicity of the sheath and core fluids, the interfacial effects are minimized and complex fluid shapes can be formed.&#160;Controlling the relative flow rates of the sheath and core fluids determines the cross-sectional area of the core fluid.&#160;Fibers have been produced with sizes ranging from 300 nm to ~1 mm, and fiber cross-sections can be round, flat, square, or complex as in the case with double anchor fibers. Polymerization of the core fluid downstream from the shaping region solidifies the fibers.&#160;Photoinitiated click chemistries are well suited for rapid polymerization of the core fluid by irradiation with ultraviolet light.&#160;Fibers with a wide variety of shapes have been produced from a list of polymers including liquid crystals, poly(methylmethacrylate), thiol-ene and thiol-yne resins, polyethylene glycol, and hydrogel derivatives. Minimal shear during the shaping process and mild polymerization conditions also makes the fabrication process well suited for encapsulation of cells and other biological components.

Two adjacent fluids passing through a grooved microfluidic channel can be directed to form a sheath around a prepolymer core; thereby&#160;determining both shape and cross-section. Photoinitiated polymerization, such as thiol click chemistry, is well suited for rapidly solidifying the core fluid into a microfiber with predetermined size and shape.

A &#8220;sheath&#8221; fluid passing through a microfluidic channel at low Reynolds number can be directed around another &#8220;core&#8221; stream and ...

Bioengineering

Microfluidic-based Synthesis of Covalent Organic Frameworks (COFs): A Tool for Continuous Production of COF Fibers and Direct Printing on a Surface

Covalent Organic Frameworks (COFs) are a class of porous covalent materials which are frequently synthesized as unprocessable crystalline powders. The first COF was reported in 2005 with much effort centered on the establishment of new synthetic routes for its preparation. To date, most available synthetic methods for COF synthesis are based on bulk mixing under solvothermal conditions. Therefore, there is increasing interest in developing systematic protocols for COF synthesis that provide for fine control over reaction conditions and improve COF processability on surfaces, which is essential for their use in practical applications. Herein, we present a novel microfluidic-based method for COF synthesis where the reaction between two constituent building blocks, 1,3,5-benzenetricarbaldehyde (BTCA) and 1,3,5-tris(4-aminophenyl)benzene (TAPB), takes place under controlled diffusion conditions and at room temperature. Using such an approach yields sponge-like, crystalline fibers of a COF material, hereafter called MF-COF. The mechanical properties of MF-COF and the dynamic nature of the approach allow the continuous production of MF-COF fibers and their direct printing onto surfaces. The general method opens new potential applications requiring advanced printing of 2D or 3D COF structures on flexible or rigid surfaces.

Microfluidic-based Synthesis of Covalent Organic Frameworks COFs: A Tool for Continuous Production of COF Fibers and Direct Printing on a Surface

We present a novel microfluidic-based method for synthesis of covalent organic frameworks (COFs). We demonstrate how this approach can be used to produce continuous COF fibers, and also 2D or 3D COF structures on surfaces.

Covalent Organic Frameworks (COFs) are a class of porous covalent materials which are frequently synthesized as unprocessable crystalline powders. The ...

Experimental Implementation of a New Composite Fabrication Method: Exposing Bare Fibers on the Composite Surface by the Soft Layer Method

The bipolar plate is a key component in proton exchange membrane fuel cells (PEMFCs) and vanadium redox flow batteries (VRFBs). It is a multi-functional component that should have high electrical conductivity, high mechanical properties, and high productivity.
In this regard, a carbon fiber/epoxy resin composite can be an ideal material to replace the conventional graphite bipolar plate, which often leads to the catastrophic failure of the entire system because of its inherent brittleness. Though the carbon/epoxy composite has high mechanical properties and is easy to manufacture, the electrical conductivity in the through-thickness direction is poor because of the resin-rich layer that forms on its surface. Therefore, an expanded graphite coating was adopted to solve the electrical conductivity issue. However, the expanded graphite coating not only increases the manufacturing costs but also has poor mechanical properties.
In this study, a method to expose fibers on the composite surface is demonstrated. There are currently many methods that can expose fibers by surface treatment after the fabrication of the composite. This new method, however, does not require surface treatment because the fibers are exposed during the manufacture of the composite. By exposing bare carbon fibers on the surface, the electrical conductivity and mechanical strength of the composite are increased drastically.

A protocol to expose bare fibers on the composite surface by eliminating resin rich area is presented. The fibers are exposed during fabrication of the composites, not by the post surface treatment. The exposed carbon composites exhibit high electrical conductivity in the through-thickness direction and high mechanical property.

The bipolar plate is a key component in proton exchange membrane fuel cells (PEMFCs) and vanadium redox flow batteries (VRFBs). It is a multi-functional ...

Magnet Assisted Composite Manufacturing: A Flexible New Technique for Achieving High Consolidation Pressure in Vacuum Bag/Lay-Up Processes

This work demonstrates a protocol to improve the quality of composite laminates fabricated by wet lay-up vacuum bag processes using the recently developed magnet assisted composite manufacturing (MACM) technique. In this technique, permanent magnets are utilized to apply a sufficiently high consolidation pressure during the curing stage. To enhance the intensity of the magnetic field, and thus, to increase the magnetic compaction pressure, the magnets are placed on a magnetic top plate. First, the entire procedure of preparing the composite lay-up on a magnetic bottom steel plate using the conventional wet lay-up vacuum bag process is described. Second, placement of a set of Neodymium-Iron-Boron permanent magnets, arranged in alternating polarity, on the vacuum bag is illustrated. Next, the experimental procedures to measure the magnetic compaction pressure and volume fractions of the composite constituents are presented. Finally, methods used to characterize microstructure and mechanical properties of composite laminates are discussed in detail. The results prove the effectiveness of the MACM method in improving the quality of wet lay-up vacuum bag laminates. This method does not require large capital investment for tooling or equipment and can also be used to consolidate geometrically complex composite parts by placing the magnets on a matching top mold positioned on the vacuum bag.

A new technique for applying consolidation pressure on the vacuum bag lay-up to fabricate composite laminates is described. The goal of this protocol is to develop a simple, cost-effective technique to improve the quality of laminates fabricated by the wet lay-up vacuum bag method.

This work demonstrates a protocol to improve the quality of composite laminates fabricated by wet lay-up vacuum bag processes using the recently developed ...

Multi-material Ceramic-Based Components &#8211; Additive Manufacturing of Black-and-white Zirconia Components by Thermoplastic 3D-Printing (CerAM - T3DP)

To combine the benefits of Additive Manufacturing (AM) with the benefits of Functionally Graded Materials (FGM) to ceramic-based 4D components (three dimensions for the geometry and one degree of freedom concerning the material properties at each position) the Thermoplastic 3D-Printing (CerAM -&#160;T3DP) was developed. It is a direct AM technology which allows the AM of multi-material components. To demonstrate the advantages of this technology black-and-white zirconia components were additively manufactured and co-sintered defect-free.
Two different pairs of black and white zirconia powders were used to prepare different thermoplastic suspensions. Appropriate dispensing parameters were investigated to manufacture single-material test components and adjusted for the additive manufacturing of multi-color zirconia components.

Here we describe a protocol for additively manufacturing black-and-white zirconia components by Thermoplastic 3D-Printing (CerAM -&#160;T3DP) and co-sintering defect-free.

To combine the benefits of Additive Manufacturing (AM) with the benefits of Functionally Graded Materials (FGM) to ceramic-based 4D components (three ...

Fused Filament Fabrication (FFF) of Metal-Ceramic Components

Technical ceramics are widely used for industrial and research applications, as well as for consumer goods. Today, the demand for complex geometries with diverse customization options and favorable production methods is increasing continuously. With fused filament fabrication (FFF), it is possible to produce large and complex components quickly with high material efficiency. In FFF, a continuous thermoplastic filament is melted in a heated nozzle and deposited below. The computer-controlled print head is moved in order to build up the desired shape layer by layer. Investigations regarding printing of metals or ceramics are increasing more and more in research and industry. This study focuses on additive manufacturing (AM) with a multi-material approach to combine a metal (stainless steel) with a technical ceramic (zirconia: ZrO2). Combining these materials offers a broad variety of applications due to their different electrical and mechanical properties. The paper shows the main issues in preparation of the material and feedstock, device development, and printing of these composites.

Fused Filament Fabrication FFF of Metal-Ceramic Components

This study shows multi-material additive manufacturing (AM) using fused filament fabrication (FFF) of stainless steel and zirconia.

Technical ceramics are widely used for industrial and research applications, as well as for consumer goods. Today, the demand for complex geometries with ...

Additive Manufacturing of Functionally Graded Ceramic Materials by Stereolithography

An additive manufacturing technology is applied to obtain functionally graded ceramic parts. This technology, based on digital light processing/stereolithography, is developed within the scope of the CerAMfacturing European research project. A three-dimensional (3-D) hemi-maxillary bone-like structure is 3-D printed using custom aluminum oxide polymeric mixtures. The powders and mixtures are fully analyzed in terms of rheological behavior in order to ensure proper material handling during the printing process. The possibility to print functionally graded materials using the Admaflex technology is explained in this document. Field-emission scanning electron microscopy (FESEM) show that the sintered aluminum oxide ceramic part has a porosity lower than 1% and no remainder of the original layered structure is found after analysis.

This manuscript describes the processing of single multifunctional ceramic components (e.g., combinations of dense-porous structures) additively manufactured by stereolithography.

An additive manufacturing technology is applied to obtain functionally graded ceramic parts. This technology, based on digital light ...

Data Communication Based on MQTT in a Polymer Extrusion Process

This work aims at building a flexible data communication structure for a polymer processing machine by employing a publisher-subscriber based protocol called Message Queuing Telemetry Transport (MQTT), which is operated over TCP/IP. Even when using conventional equipment, processing data can be measured and recorded by various devices anywhere through an Internet communication. A message-based protocol allows flexible communication that overcomes the shortcomings of the existing server-client protocol. Multiple devices can subscribe to the processing data published by source devices. The proposed method facilitates data communication between multiple publishers and subscribers. This work has implemented a system that publishes data from the equipment and additional sensors to a message broker. The subscribers can monitor and store the process data relayed by the broker. The system has been deployed and run for a film extrusion line to demonstrate the effectiveness.

This work proposes a flexible method for data communication between a film extrusion system and monitoring devices based on a message protocol called Message Queuing Telemetry Transport (MQTT).

This work aims at building a flexible data communication structure for a polymer processing machine by employing a publisher-subscriber based protocol ...