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Sensing and control in glass additive manufacturing
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Sensing and control in glass additive manufacturing☆ ⁎
Daniel Peters, Joseph Drallmeier, Douglas A. Bristow , Robert G. Landers, Edward Kinzel Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology, Rolla, MO, USA
A R T I C LE I N FO
A B S T R A C T
Keywords: Additive manufacturing Path planning Process control
There has been tremendous interest in the Additive Manufacturing (AM) of polymers, metals, and ceramics leading to a wealth of research and development of these processes. By contrast, there has been little attention paid to AM processes for glass. This paper presents a custom-made glass additive machine. A CO2 laser is used to generate a molten pool of glass into which glass filaments are fed. A motion system is used to trace a layer, after which the build platform is lowered to fabricate the next layer. Two of the unique issues that must be addressed in the AM of glass are 1) various mechanisms can cause the formation of bubbles that deteriorate part optical and mechanical properties and 2) significant processing forces can move the melt pool away from its desired location. In this paper a melt pool temperature controller is designed to regulate the melt pool temperature at a constant value and a path and trajectory generation algorithm is constructed to maintain a constant glass filament feed direction relative to the scan velocity. The experimental results demonstrate that the melt pool temperature controller is able to avoid bubble formation over a wide range of build speeds and that the path planned directional-control is able to maintain good dimensional accuracy throughout closed contours. The capabilities of the AM for glass machine are demonstrated on a thin-walled, multi-layer star pattern and a spring in which the material is printed in freespace without the need for support structures.
1. Introduction Additive Manufacturing (AM) has received a great deal of attention due to its ability to rapidly prototype parts and its ability to fabricate functional parts that are impossible to manufacture with conventional techniques. These processes allow for nearly limitless design freedom, do not require tooling, and provide excellent material usage and minimal part assembly. In addition, Direct Energy Deposition (DED) AM where material is added via blown powder or a wire allows for the creation of parts with functionally graded materials, the addition of engineering features, and part repair. While these benefits are being rapidly realized for polymers, metals, and ceramics, there has been comparatively little work done in the AM of glass. Glasses are critical for many engineering applications including optics/photonics, chemical handling, metrology frames, and hermetic seals. Glass is also widely used in architectural and artistic applications. Most of the published work in AM of glass has focused on geometric artifacts without regard for the optical properties. Examples include binder jet printing [1], extrusion [2,3], and selective laser sintering [4–6]. Transparency is difficult to achieve in these processes because glass, unlike metal, retains a high viscosity when molten so that bubbles formed or trapped
during deposition do not have time to consolidate and escape the melt region via buoyancy [7]. However, bubbles can be extracted from green parts printed with glass nanoparticles using a very gradual post deposition burn-out/densification thermal treatment. This approach was realized by Nguyen et al. [8] using an extrusion process and by Kotz et al. [9] using a sterolithography process. Klien et al. [2] demonstrated printing intricate vases by allowing molten glass to flow under gravity through an orifice and onto a CNC controlled build plate. Similarly, molten glass can be extruded through a heated nozzle following a Fused Deposition Modeling (FDM) type approach. This process has been developed by Micron3DP [10] and requires significantly more robust nozzles compared to printing plastic parts. An even smaller molten region can be achieved by feeding semi-rigid glass filaments into a laser generated molten region [11]. This process allows the glass to reflow to fill track undulations and is capable of printing solid 3D parts. Further, the rapid cooling of the glass facilitates the printing of free-standing glass structures. Monitoring and control has been applied to regulate many variables in metal DED AM processes including temperature [12,13], melt pool geometry [14], and part height [15], and has been demonstrated to significantly improve part quality [16]. However, monitoring and
☆ ⁎
This paper was recommended for publication by Associate Editor Dr. D Hoelzle. Corresponding author. E-mail address: [email protected] (D.A. Bristow).
https://doi.org/10.1016/j.mechatronics.2018.06.002 Received 4 October 2017; Received in revised form 19 April 2018; Accepted 6 June 2018 0957-4158/ © 2018 Elsevier Ltd. All rights reserved.
Please cite this article as: Peters, D., Mechatronics (2018), https://doi.org/10.1016/j.mechatronics.2018.06.002
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control of the AM of glass has not yet been explored. There are a number of differences that exist between metal and glass that affect the process control of the AM of glass. The most notable difference is that glass is much more viscous than liquid metal and glass gradually transitions from a solid into a liquid (and back) over a range of temperatures instead of melting nearly instantaneously at a specific temperature. This slow melting process allows bubbles to form and remain in the glass, severely reducing optical quality. Further, the high viscosity of glass creates significant processing forces between the filament and the molten pool of glass, which can cause the molten glass to be displaced from its desired location. This paper will explore melt pool temperature regulation to control bubble formation, and path planning to maintain a constant filament feed direction for track morphology control of the AM of glass. The rest of this paper is organized as follows: Section 2 presents an overview of the glass additive machine including the energy source, motion system, filament feeder, and software architecture. Section 3 presents a melt pool temperature controller and experimental results. A four-axis path generation algorithm that maintains a constant filament feed direction is given in Section 4 and experiments are conducted to demonstrate the efficacy of this approach. Section 5 presents the results of printed parts and Section 6 summarizes the paper and draws conclusions of this work. 2. Machine overview In order to print glass in a predictable and repeatable manner, the glass additive process must be able to
• heat the glass in a small area to a temperature where it can flow and • • • •
be deposited, while allowing the glass to cool and solidify quickly after deposition; minimize thermal stresses that can weaken the part as it cools; deposit the glass at a specified rate, in precisely controlled locations; print a wide variety of shapes and patterns with multiple types of glass, multiple sizes of raw stock, and varying process parameters; be capable of reheating previously deposited glass to smooth out irregularities that would decrease its optical properties. Fig. 1. Build area of glass AM machine.
With these considerations, the machine was designed to have a laser entering the build area from the top, with glass filaments being fed in from the side to create a melt pool at a fixed point. The substrate moves relative to the melt pool as the glass is deposited to build a part. A closeup view of the build area is shown in Fig. 1. A heated build plate is used to hold a substrate, which is typically the same material of the glass being printed. This plate is kept at a high temperature to help reduce stresses caused by the thermal expansions of the substrate and printed glass. The laser is focused onto a filament of glass that, once placed on the substrate, creates a melt pool. The build plate and substrate are moved past the stationary melt pool using a four-axis motion system whose motion creates the desired part geometry for a layer. The glass filament is continuously fed into the melt pool using a filament feeder. As the molten glass moves away from the laser, it quickly cools and solidifies in place. Once a layer of glass has been printed, the substrate is lowered and a new layer is printed. A shutter is placed in the path of the laser and is used to block the laser before and after printing a continuous path.
CO2 laser (Synrad Evolution 125, λ0 = 10.6 µm, 162.5 µm spot size) was chosen as the energy source. It is directed at the substrate through a series of optical elements. The laser is defocused such that the spot size is equal to the filament diameter, i.e., 2 mm. A Focal-π Shaper transforms the intensity distribution of the laser beam from a Gaussian distribution into a flattop distribution. The laser power is measured by splitting 1% of its energy into a thermopile type power meter (Ophir 10A-V1). An OceanOptics USB-4000 fiber-coupled spectrometer (calibrated with an OceanOptics LS-1-CA 2800 K light source) is used to observe the spectrum of incandescent light emitted during the printing process. A LumaSense Technologies IMPAC IN140-L pyrometer is also focused on the melt pool in order to measure the temperature of the glass while printing. 2.2. Motion system The motion system must be able to closely follow the commanded path at the commanded speed to precisely place the glass. At the same time, the direction of deposition relative to the filament feed direction affects track morphology and optical quality. Thus, orientation control is also necessary to achieve consistent deposition of good quality glass. While these relationships are explored in more detail in Section 4, it is notable that this appears to be a challenge unique to glass DED. Other filament-fed processes such as polymer FDM use a heated nozzle to direct the material orthogonal to all print directions in the X-Y plane,
2.1. Energy source The energy source must be able to heat the glass filament above the highest transition temperature of all types of glass that will be printed. For this machine, fused quartz glass with a transition temperature of 1665 °C is the glass with the highest transition temperature that has been printed. It must also be able to reheat previously deposited glass to allow it to reflow. To achieve such requirements, a continuous-wave 2
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while the material in metal wire-fed DED processes has such low viscosity that directional dependency may be minor. Therefore, the motion system consists of three orthogonal linear axes, denoted X, Y, and Z, and a rotational axis, denoted C, that rotates around the Z axis. While depositing glass, the maximum linear deposition speed is on the order of 1–5 mm/s. However, even at low deposition speeds, a rotation in the print direction can necessitate rapid rotation of the C axis and rapid traversal of the X and Y linear axes. Some deposition paths presented in Section 4 require rotational speeds above 270°/s and linear axis speeds up to 300 mm/s. The X and Y axes are powered by direct drive linear servomotors (Aerotech ANT130-160-XY) each having a maximum speed of 350 mm/ s, maximum acceleration of 10 m/s2, and a maximum force of 23 N. The position of each linear axis is measured by a linear encoder with a resolution of 1 nm. The Z axis is a linear ball-screw stage driven by a direct drive servomotor (Aerotech ATS100-150) with a maximum speed of 100 mm/s and a maximum load of 98.1 N. Its position is measured by a rotary encoder on the drive motor with a resolution equivalent to 0.1 µm [17]. The C axis is powered by a direct drive servomotor (Aerotech ANT130-360-R) with a maximum speed of 200 rpm, a maximum acceleration of 400 rad/s2, and a maximum continuous torque of 0.2 N-m. Its position is measured by a rotary encoder with a resolution of 0.01′′ [18]. A kinematic model of the machine will be used to convert path planning in the workspace frame into motion commands for the machine axes. Let the baseframe be defined by the frame {x0, y0} and the workspace frame by the frame {xw, yw}, as illustrated in Fig. 2. Given axis positions xc, yc, θc, the transformation from workspace coordinates to base coordinates is,
⎡ cos θc − sin θc x c ⎤ Tw0 (x c , yc , θc ) = ⎢ sin θc cos θc yc ⎥. ⎢ ⎥ 0 1 ⎦ ⎣0
sin θc − x c cos θc − yc sin θc ⎤ ⎡ cos θc T0w (x c , yc , θc ) = ⎢− sin θc cos θc x c sin θc − yc cos θc ⎥. ⎢ ⎥ 0 1 ⎣0 ⎦
(2)
Let the vector s represent the fixed location of the melt pool (i.e., the intersection of the filament and laser) in the baseframe and let θv0 and v0 represent the angular and vector direction, respectively, of the filament feed in the baseframe. Then, the corresponding location and filament feed direction, in the workspace frame, are given by, 0
0 0 w ⎡ sx ⎤ ⎡ (sx − x c )cos θc + (s y − yc )sin θc ⎤ s w = ⎢ s yw ⎥ = ⎢− (s 0 − x c )sin θc + (s 0 − y )cos θc ⎥, x y c ⎥ ⎢ ⎥ ⎢ ⎥ ⎣1 ⎦ ⎢ ⎦ ⎣1
(3)
and
vw
w 0 ⎡ cos θv ⎤ ⎡ cos(θv − θc ) ⎤ w 0 ⎢ = ⎢ sin θv ⎥ = sin(θv − θc ) ⎥, ⎥ ⎢ ⎥ ⎢ ⎣0 ⎦ ⎣0 ⎦
(4)
s 0,
θv0
and desired respectively. Therefore, given alignment information workspace position, sw, and orientation, θvw , axis commands can be obtained by solving (3) and (4),
θc = θv0 + θvw
(5)
x c = sx0 − sxw cos(θv0 + θvw ) + s yw sin(θv0 + θvw ),
(6)
yc = s y0 − sxw sin(θv0 + θvw ) − s yw cos(θv0 + θvw ),
(7)
2.3. Filament feeder A schematic of the filament feeder is shown in Fig. 3. The filament is fed by a drive wheel connected to the motor by two belts. A gear reduction is used to provide finer positioning of the filament. The filament is guided by a stainless steel tube inserted through the body of the feeder, with a PTFE lining to prevent the filament from being scratched, which can be a source of microbubbles in the printed part. The drive wheel is attached to the end of a spring-loaded, rotating arm that allows it to apply pressure to the filament for traction. The drive wheel contacts the filament through a notch in the top of the guide tube, and has a rubber surface to help grip the filament. The filament feeder is powered by a direct drive brushless servomotor (Yaskawa SGMJV-01A3M61) with a maximum speed of 750 rpm, a maximum acceleration of 47800 rad/s2, and an instantaneous peak torque of 1.11 N-m [19]. The feeder positionis measured by a rotary encoder inside the motor with a resolution of 10′′. The gear and belt system reduces the motor rotational speed by a factor of 12. Based on
(1)
T w w Then, a point located at pw = [ px py 1] in the workspace can be 0 w 0 located in the base frame by p = Tw p . Likewise, a vector oriented at T v w = [ vxw vyw 0 ] in the workspace is oriented in the base frame di0 rection, v 0 = Tw v w . Conversely, the inverse transformation from base frame coordinates to workspace coordinates is,
Fig. 2. Two dimensional kinematics of glass AM machine.
Fig. 3. Filament feeder schematic. 3
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Fig. 4. System block diagram.
being added from the laser, losses to the environment via convection, radiation, and conduction to the substrate and the filament, along with the balance of cold glass and hot glass, entering and exiting the molten region, respectively. Practically, this means the molten region temperature is a function of the laser power, scan speed, filament feed rate, and substrate temperature, as well as the geometry of the part being printed. Developing process maps is a time consuming exercise that must be repeated for each part geometry and each type of glass (e.g., soda lime and borosilicate glasses have dramatically different thermal properties). In addition, the process mapping approach cannot adapt to natural disturbances that affect the process (e.g., change in heat transfer conditions when printing the corners of a part). In this section a closedloop melt pool temperature control system is designed to monitor the melt pool temperature and regulate it to a constant value by automatically adjusting the laser power.
the motor’s maximum speed and a drive wheel with a radius of 11 mm, the feeder is capable of feeding at speeds from 0 to 70 mm/s. 2.4. Software architecture The stages, filament feeder, and laser are controlled by a data acquisition and control system (National Instruments PXIe-1082 Chassis, PXIe-8135 Controller, PXIe-6356 Multifunction DAQ, PXIe-6612 Timing and Digital I/O DAQ, PXIe-6733 Analog Output DAQ) using a custom program made using National Instruments LabVIEW. The PXI system uses a deterministic operating system that provides predictable timing behavior, which is necessary for reliable feedback control. Using a sampling frequency of 5000 Hz, this program generates path plans and reference signals for the motion system axes and filament feeder, receives data from the encoders and pyrometer, executes control algorithms for all of the feedback loops, and sends control signals to the motors and laser. A block diagram of the system is shown in Fig. 4. Separate feedback control loops are tuned for position tracking of each of the motion system axes (X,Y,Z,C) and of the filament feeder. While constant speed deposition is typically desired, the necessity of aligning the wire feed direction with the print direction generates complex coordinated X,Y,C stage motions with significant velocity and acceleration variations (discussed in Section 4). Velocity-tracking constraints on these axes can result in decreased deposition speed and, thus, a dynamically changing filament speed reference. Feedback control of the melt pool temperature, necessary to maintain good glass optical and mechanical properties, is discussed in Section 3.
3.1. Melt pool temperature sensing In order to create a closed-loop melt pool temperature control system, the glass additive machine must be able to measure the melt pool temperature while the part is being printed without interfering with the printing process. A pyrometer, which collects infrared radiation to measure temperature, was chosen since it is a noncontact sensor that can sense the melt pool temperature without affecting the melt pool, or itself being damaged by the extreme environment of the processing zone. The temperature sensor is a LumaSense Technologies IMPAC IN140-L pyrometer, which has a temperature range of 500–2500 °C and an uncertainty of 1.2% [21]. This temperature range was selected since borosilicate glass transitions into a liquid at approximately 550 °C and will vaporize well before 2500°C. The pyrometer outputs an analog signal that is read by the PXIe-6356 multifunction card.
3. Melt pool temperature control The clarity (i.e., absence of bubbles of striae) and morphology of the printed glass is strongly dependent on the melt pool temperature. The properties of glass, including viscosity, are highly temperature dependent. If the melt pool is too cool, the glass will not become sufficiently molten and filaments will break or deflect away from the laser beam, generally leading to an unrecoverable build failure. On the other hand, if the melt pool is too hot, the process will overheat the glass, leading to vaporization of the glass and formation of bubbles via precipitation (reboil) or entrapment due to rapid slumping. This leads to reduced optical and mechanical properties [20]. Therefore, reliable control of the melt pool temperature is of critical importance. The temperature of the molten region is dependent on the energy
3.2. Melt pool temperature process modeling An empirical melt pool temperature process model is developed that relates the measured melt pool temperature to the laser power. The model used for controller design is an experimentally-constructed frequency response of the melt pool temperature process. Without feeding glass filaments, the laser traced a circular path having a diameter of 40 mm on a borosilicate substrate at a scan velocity of 1 mm/s. While this scan speed is larger than scan speeds typically used in processing glasses, 1 mm/s was used to avoid overmelting the substrate. Feedback 4
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Fig. 5. Melt pool temperature frequency response.
Fig. 6. Melt pool temperature closed-loop frequency response.
3.4. Melt pool temperature process experiments
will allow the controller to account for modeling uncertainties from using a high scan speed and no filament in the modeling experiments. Glass filaments were not fed during the modeling process as the filaments are not long enough to last the entire duration of the experiment (i.e., 2 h). During the modeling process, the nominal commanded laser power was set to 25 W and the melt pool temperature was measured with the pyrometer. Using an Agilent 35670A Dynamic System Analyzer (DSA), a sinusoidal excitation source with an amplitude of 2 V, which corresponds to ± 10 W, was injected into the nominal commanded laser power signal. The DSA swept over a range of frequencies from 0.1–62.8 rad/s and simultaneously measured the temperature and total laser power (i.e., nominal plus DSA excitation). A lower bound of 0.1 rad/s was selected as this is the lowest frequency the DSA can reliably operate at and an upper frequency of 62.8 rad/s was selected as it will be seen that it is well beyond the bandwidth of the melt pool temperature process. Using the collected data, the DSA generated a frequency response of the melt pool temperature process (i.e., the process relating melt pool temperature to commanded laser power). The melt pool temperature process frequency response is shown in Fig. 5. For frequencies under 20 rad/s the process exhibits a linear, firstorder response. This is expected since the heat transfer process is dominated by conduction to the substrate. For frequencies above 20 rad/s, the magnitude and the phase drop off sharply. This is likely due to sensor dynamics and nonlinear effects such as radiation heat transfer.
In order to test the efficacy of the melt pool temperature control system, two sets of experiments were conducted where a single track with six layers was printed. In each set of experiments, two trials were conducted: one with constant process parameters and one with melt pool temperature control where the controller automatically adjusted the laser power to regulate the melt pool temperature at 1065 °C. The process parameters for the first set of experiments, trials 1 and 2, were a scan speed of 0.2 mm/s, a filament feed rate of 0.2 mm/s, and a height increment between layers of 1.25 mm. In trial 1 the laser power was maintained at a constant value of 32 W. This process parameter set has been shown to print acceptable tracks for borosilicate glass [20]. The resulting wall is shown in Fig. 7(a). In trial 2 the temperature controller was implemented and the resulting wall is shown in Fig. 7(b). Note that neither wall had visible bubbles. The temperature time histories for both trials are shown in Fig. 8 for layers 2, 3, 4, and 5. There are
3.3. Melt pool temperature process control Since there is a tremendous amount of uncertainty in the high frequency range (i.e., above 20 rad/s), loop-shaping techniques were utilized to design a controller that tracks constant references while not exciting frequencies above 20 rad/s. Using the empirical melt pool temperature process model given in Fig. 5, the following controller transfer function was designed
P (s ) s+5 =5 ET (s ) s (s + 2)2
(8)
where P is the commanded laser power (W) and ET is the melt pool temperature error (°C). The integrator allows the controller to track constant reference signals and reject constant disturbances. The closedloop frequency response is shown in Fig. 6. The closed-loop bandwidth is 20 rad/s and has less than 2% error and less than 5° phase deviation for frequencies below 10 rad/s.
Fig. 7. Glass walls printed using (a) 0.2 mm/s scan speed, constant 32 W laser power (trial 1) (b) 0.2 mm/s scan speed, temperature controlled at 1065 °C (trial 2) (c) 0.31 mm/s scan speed, constant 50 W laser power (trial 3) (d) 0.31 mm/s scan speed, temperature controlled at 1065 °C (trial 4). 5
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Fig. 8. Temperature time history response for scan velocity = 0.2 mm/s.
Fig. 9. Temperature time history response for scan velocity = 0.31 mm/s.
variations in the melt pool temperature as each layer begins fabrication. While trial 2 (i.e., with control) regulates the temperature with less variation then trial 1 (50.2 °C compared to 56.3 °C), they both maintain a similar average melt pool temperature (1059 °C and 1060 °C for uncontrolled and controlled, respectively) that is sufficient to print glass without bubbles. In the second set of experiments, trials 3 and 4, the scan speed and filament feed rate were both increased to 0.31 mm/s to increase the build speed by over 50%. In trial 3 a constant laser power with a value of 50 W was used to maintain approximately the same energy density, which is proportional to laser power divided by scan speed, used in the trial 1. The results for trial 3 are shown in Fig. 7(c). In this build, periodic bubble formation was observed. It is believed that even though the energy distribution is the same in both sets of experiments, the heat distribution from the top to the bottom of the filament is different and, in trial 3, the temperature on the top of the filament was much hotter leading to reboil and the formation of bubbles [20]. In trial 4 the temperature controller was implemented, and the resulting wall is shown in Fig. 7(d). It can be seen that the temperature was maintained at a lower value and the wall was free of bubbles. Therefore, the use of melt pool temperature control allowed the build speed to be significantly increased without affecting the part properties. The temperature time histories for both trials are shown in Fig. 9 for layers 2, 3, 4, and 5. In this case trial 2 (i.e., with control) regulates the
Fig. 10. (a) Photograph and (b) 3D scan of glass beads printed at various orientations relative to the wire feed direction.
temperature with significantly less variation then trial 1 (62.2 °C compared to 158 °C) and with an average melt pool temperature much closer to the desired value (1058 °C compared to 1182 °C). The elevated temperature caused bubble formation in trial 3 (i.e., uncontrolled) as seen in Fig. 7(c). The ability to regulate the melt pool temperature allowed for the fabrication of bubble-free glass parts.
4. Five-axis path and trajectory generation One of the primary advantages of additive manufacturing is the ability to create shapes and patterns that would otherwise be difficult or impossible to fabricate using conventional manufacturing methods. Therefore, it is important for the machine to be capable of creating complex geometries rather than placing limits on the features that can be designed. The process itself is limited by factors such as the 6
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Fig. 12. (a) Workspace path with 180° direction change and (b) individual axes along the path showing orientation filtering. Fig. 11. Cross section of bead showing morphology when printing (a) aligned with wire feed direction and (b) opposing wire feed direction.
altering forces. However, at 60°, the differing velocities create a shear on the bottom of the melt pool stretching the melt pool and making it wider and, thus, shallower. More extreme behaviors occur near 180°, also shown in Fig. 10. Here the filament feeds in the opposite direction of the scan velocity. In this case, a relatively stiff filament is pushing into the melt pool, forcing the hotter, softer glass out of the way. At precisely 180°, the melt pool is pushed to either side, resulting in a valley at the center of the track, while angles slightly off of 180° tend to push the track off to the nearer side. In order to achieve precise deposition of the glass, it is therefore necessary to keep the deposition direction near to 0° throughout the process. Here, a constraint of no more than 30° from 0° alignment is used. To achieve this orientation control while printing in different directions, the substrate is placed on a rotational stage. Path planning for the combined system is presented in the following section.
sensitivity of glass morphology to feed direction as well as the capabilities of the motors that drive the machine. In order to prevent these factors from affecting the quality of the fabricated part, they are incorporated into the path and trajectory design. 4.1. Effect of feed direction on bead morphology One important property of glass is that instead of melting at a specific temperature, its viscosity smoothly transitions over a temperature range. As the filament enters the melt pool and is exposed to the laser, it retains some of its viscosity for a short period of time, which means that it can distort the shape of the melt pool and the track of glass it deposits. Therefore, the printed track morphology is significantly affected by the direction from which the filament is fed. Fig. 10 shows an image and 3D scan of tracks printed at 30° increments with respect to the filament feed direction, with 0° referring to the filament feeding in the direction of the scan velocity. The tracks were printed with 2 mm diameter stock, a scan speed of 1 mm/s, a filament feed rate of 1 mm/s, and a laser power of 40 W. Cross sections of the scanned tracks is shown in Fig. 11. As can be seen in Figs. 10 and 11, for a feed direction near 0° the melted track is slightly shorter (1.5 mm) and slightly wider (2.4 mm) than the 2 mm feedstock. Small rotations (<30°) from 0° show similar geometries; however, by 60° the track is noticeably shorter and wider. The changing morphology can be understood as follows. When the glass is fed at 0°, it begins heating via conduction, softening slightly before entering the melt pool where it fully softens, slumps, and adheres to the melt pool traveling at the same velocity and thus, minimizing shape-
4.2. Spatial path generation The spatial path is typically generated by a CAD slicer program that transforms solid model geometries into the path, often consisting of border and rastered in-fills in a layer-by-layer fashion. Let p ∈ [0, L] represent the location along a desired path of length L, and xw(p), yw(p), and zw(p) the corresponding desired spatial coordinates of the path in the part frame. Further, assume that the path is continuously differentiable, x w (p), y w (p), z w (p) ∈ C1. As discussed in the previous section, the print quality is best when the feed direction aligns with the scan velocity. Therefore, the desired print direction is defined as,
θ w (p) = atan2 ⎛⎜ ⎝ 7
dy w (p) dx w (p) ⎞ , ⎟, dp dp ⎠
(9)
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Fig. 13. (a) Photo of star printed with directional control, (b) photo of star without directional control, (c) height of star printed with directional control, and (d) height of star printed without directional control.
Then, the largest orientation error can be determined as,
where atan2(y, x) is the arctangent of a point at location (x, y). While small deviations in the print orientation do not demonstrate measurable impact on print quality, smoothing of the print orientation can significantly reduce the necessary tracking bandwidth. Therefore, we will consider θfw , a smoothed version of θw, as the reference. To maximize accuracy and eliminate delay effects, the smoothed function can be generated using a zero-phase filter, for example with the forwardbackward filtering procedure,
θFw (p) = F (s ) θ w (p),
(10)
θBw (p) = F (s ) θFw (−p),
(11)
θfw (p) = θFw (−p).
(12)
max θfw (p) − θ w (p) ≤ p
180 (1 − e−πar ). 2πar
(13)
In the remainder of this work, the smallest radius utilized with be r = 1 mm, and the maximum desired orientation will be set to 30°. Thus, a filter pole of a = 0.9 mm−1 will be used. The spatial filament feed rate, F(p) is typically desired to be constant to create a uniform morphology throughout the layer. However, the filament feeder is controlled using a position-control loop in order to, for example, ensure metered material addition at filament starts and stops. Thus, the filament feed position command along the path is,
fc (p) =
where F(s) is a suitable lowpass filter. The maximum desired orientation deviation, maxp θfw (p) − θ w (p) , can be constrained through filter design. For example, consider the first-order filter, F (s ) = a/(s + a), where a is the filter bandwidth in rad/mm, and a 180° direction change in the path with radius, r. Such a trajectory is illustrated in Fig. 12.
∫p
p
F (λ ) dλ
0
4.3. Trajectory design The workspace frame path generated in the previous section as 8
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Fig. 14. Multi-layer star wall fabricated using the star trajectory design.
xw(p), yw(p), zw(p), θfw (p), are converted into axis references xc(p), yc(p), zc(p), θc(p) using (5)–(7) and the additional trivial kinematic relation, z c (p) = z w (p) . In the following, the temporal trajectory commands are generated for the axes in order to generate a desired deposition spatial feed rate along the path while also considering actuator velocity and acceleration constraints. Let vdes(p) represent the desired deposition velocity along the path. Further, let x v , yv , zv , θv , fv represent the maximum absolute velocities for the X, Y, Z, C, and F axes, respectively. Then, the desired deposition velocity exceeds the maximum axis velocity in X when
Fig. 15. Glass spring demonstrating good dimensional control in freespace printing.
5. Part fabrication Two parts were fabricated using the AM of glass machine. The first part is a star wall where 6 layers of the star in Section 4.4 was fabricated with the melt pool temperature controller and the path and trajectory generator. A picture of the part is shown in Fig. 14. This part demonstrates the ability of tracks to bond with previous layers without visually altering the previous layer’s morphology. Note that a small amount of local reflow does exist that, when controlled, can be useful when fabricating solid parts. The consisting printing around each layer illustrates the efficacy of the path and trajectory generation methodology, and the fact that each layer is bubble free demonstrates the efficacy of the melt pool temperature controller with changing heat transfer conditions. The second part that was fabricated was a glass spring. A picture of the spring is shown in Fig. 15. Note that the entire spring, with the exception of the first layer, was fabricated without support and nearly in the horizontal direction. Slumping is avoided due to the high viscosity of glass, as well as the quick solidification when operating with the correct process parameters.
dx (p) dx (p) = vdes (p) c ≥ x v, dp dt and similarly for Y, Z, C, and F. Now, the deposition velocity can be reduced to avoid actuator velocity constraints using,
v (p) = vdes (p)·min
⎧ x v , ⎨ dx c (p) ⎩ dp
yv dyc (p) dp
,
zv dz c (p) dp
,
θv dθc (p) dp
,
fv dfc (p) dp
⎫ ⎬ ⎭
. (14)
Acceleration constraints are applied in a similar manner. Then, the trajectories are generated using,
t (p) =
∫p
p
0
1 dτ v (τ )
(15)
6. Summary and conclusions 4.4. Experiments This paper presented a mechatronic system specifically designed for the AM of glass. An overview of the machine was given including descriptions of the energy source used to generate the melt pool, the motion system used to create the scan velocity, the custom-designed filament feeder used to feed the glass stock into the melt pool, and the architecture of the software system used for monitoring and control. An empirical model of the melt pool temperature process was constructed in the frequency domain and loop-shaping techniques were used to design a feedback controller. The temperature control solution was compared against a constant power density solution at two feed rates. At nominal feed rate, both methods demonstrated ability to print glass without bubble defects, but only the temperature feedback method
A star pattern was designed and printed using this path and trajectory planning method, shown in Fig. 13. The sides were each 15 mm in length, and the corners had radii of 1 mm. The path was printed at a nominal scan rate of 1 mm/s, with the filament being fed into the melt pool at a rate of 1 mm/mm of travel. The melt pool temperature was controlled to 2000 °C. Also shown in Fig. 13, for comparison, is the same star generated without orientation change and using a scan velocity of 1 mm/s and a filament feed rate of 1 mm/s. As can be seen in the height scans, the orientation-control of the path-planned solutions shows much stronger uniformity in bead morphology and geometric accuracy. 9
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maintain good quality at elevated feed rate. The effect of feeding glass filaments at various orientations with respect to the scan velocity was also investigated. Tracks printed at a range of orientations around 0°demonstrated a consistent morphology. A path planning methodology was created to ensure the print orientation remained in this range and a trajectory generation method was used to prevent actuator saturation. Compared against a fixed-direction feed orientation, the path planning method demonstrated significant improvement in the uniformity of the track morphology. Finally, the glass AM machine was used to fabricate two parts: a multi-layered star wall and a spring. The effectiveness of the methods were demonstrated in the bubble-free parts with consistent track morphology. Notably, the spring also demonstrated the ability of the process to print in freespace, without structural support. Future work will consist of modeling track morphology as a function of process parameters, including feed direction, for various types of glasses. We will create morphology control schemes and integrate them with our existing temperature controller. This work will be experimentally verified by building thin walls and then expanded to the fabrication of blocks and other parts with infills.
[3] Deliormanli A, Rahaman M. Direct-write assembly of silicate and borate bioactive glass scaffolds for bone repair. J Euro Ceram Soc 2012;32:3637–46. [4] Klocke F., McClung A., Ader C.. Direct laser sintering of borosilicate glass. Solid freeform fabrication symposium, Austin TX2004;:214–219. [5] Fateri M, Gebhardt A. Selective laser melting of soda-lime glass powder. Int J Appl Ceram Technol 2015;12(1):53–61. [6] Khmyrov R, Grigoriev S, Okunkova A, Gusarov A. On the possibility of selective laser melting of quartz glass. Phys Procedia 2014;56:345–56. [7] Luo J, Pan H, Kinzel E. Additive manufacturing of glass. J Mfct Sci Tech 2014;136(061024). [8] Nguyen D, Meyers C, Yee T, Dudukovic N, Destino J, Zhu E, Duoss C, et al. 3Dprinted transparent glass. Adv Matr 2017;29(1701181). [9] Kotz F, Arnold K, Bauer W, Schild D, Keller N, Sachsenheimer K, et al. Three-dimensional printing of transparent fused silica glass. Nature 2017;554:337–9. [10] Micron3dp. http://ww.micro3dp.com. [11] Luo J, Gilbert LJ, Qu C, Landers RG, Bristow DA, Kinzel EC. Additive manufacturing of transparent soda-lime glass using a filament-fed process. J Manuf Sci Eng 2017;139(6):061006–061006–8. [12] Tang L, Landers R. Melt pool temperature control for laser metal deposition processes, part i: online temperature control. ASME J Manuf Sci Eng 2010;132(1). 011010:1–9. [13] Tang L, Landers R. Melt pool temperature control for laser metal deposition processes, part ii: LayertoLayer temperature control. ASME J Manuf Sci Eng 2010;132(1). 011011:1–9. [14] Moralejo S, Penaranda X, Nieto S, Barrios A, Arrizubieta I, Tabernero I, et al. A feedforward controller for tuning laser cladding melt pool geometry in real time. Int J Adv Manuf Technol 2017;89:821–31. [15] Sammons P., Gegel M., Bristow D., Landers R.. Repetitive process control of additive manufacturing with application to laser metal deposition. IEEE Transactions on Control Systems Technology, doi:10.1109/TCST.2017.2781653. [16] Reutzel EW, Nassar AR. A survey of sensing and control systems for machine and process monitoring of directed energy, metal-based additive manufacturing. Rapid Prototyp J 2015;21(2):159–67. [17] ATS100 Series Stage User’s Manual. Aerotech Inc., Rev. 1.1; 2004. [18] ANT130-R Series Stage User’s Manual. Aerotech Inc., Rev. 1.04.00; 2011. [19] Sigma-5 series product catalog: SGMJV series rotary servo motor section. Yaskawa America, Inc.; 2016. [20] Luo J, Hostetler J, Goldstein J, Bristow D, Landers R, Kinzel E. Heat transfer in additive manufacturing of glass. Heat Transfer Conference. 2017. [21] IN 140/5 IN 140/5-H IN 140/5-L IMPAC-Pyrometer operation manual. LumaSense Technologies, Inc.; 2009.
Acknowledgments This work was supported by the National Science Foundation (CMMI-1538464) and the Air Force Research Laboratory. References [1] Marchelli G, Prabhakar R, Storti D, Ganter M. The guide to glass 3d printing: developments, methods, diagnostics and results. Rapid Prototyp J 2011;17(3):187–94. [2] Klein S, Dickin F, Adams G, Simske S. Glass: an old material for the future of manufacturing. Tech. Rep.. Hewlett-Packard Development Company Technical Report; 2012.
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Contents lists available at ScienceDirect
Mechatronics journal homepage: www.elsevier.com/locate/mechatronics
Sensing and control in glass additive manufacturing☆ ⁎
Daniel Peters, Joseph Drallmeier, Douglas A. Bristow , Robert G. Landers, Edward Kinzel Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology, Rolla, MO, USA
A R T I C LE I N FO
A B S T R A C T
Keywords: Additive manufacturing Path planning Process control
There has been tremendous interest in the Additive Manufacturing (AM) of polymers, metals, and ceramics leading to a wealth of research and development of these processes. By contrast, there has been little attention paid to AM processes for glass. This paper presents a custom-made glass additive machine. A CO2 laser is used to generate a molten pool of glass into which glass filaments are fed. A motion system is used to trace a layer, after which the build platform is lowered to fabricate the next layer. Two of the unique issues that must be addressed in the AM of glass are 1) various mechanisms can cause the formation of bubbles that deteriorate part optical and mechanical properties and 2) significant processing forces can move the melt pool away from its desired location. In this paper a melt pool temperature controller is designed to regulate the melt pool temperature at a constant value and a path and trajectory generation algorithm is constructed to maintain a constant glass filament feed direction relative to the scan velocity. The experimental results demonstrate that the melt pool temperature controller is able to avoid bubble formation over a wide range of build speeds and that the path planned directional-control is able to maintain good dimensional accuracy throughout closed contours. The capabilities of the AM for glass machine are demonstrated on a thin-walled, multi-layer star pattern and a spring in which the material is printed in freespace without the need for support structures.
1. Introduction Additive Manufacturing (AM) has received a great deal of attention due to its ability to rapidly prototype parts and its ability to fabricate functional parts that are impossible to manufacture with conventional techniques. These processes allow for nearly limitless design freedom, do not require tooling, and provide excellent material usage and minimal part assembly. In addition, Direct Energy Deposition (DED) AM where material is added via blown powder or a wire allows for the creation of parts with functionally graded materials, the addition of engineering features, and part repair. While these benefits are being rapidly realized for polymers, metals, and ceramics, there has been comparatively little work done in the AM of glass. Glasses are critical for many engineering applications including optics/photonics, chemical handling, metrology frames, and hermetic seals. Glass is also widely used in architectural and artistic applications. Most of the published work in AM of glass has focused on geometric artifacts without regard for the optical properties. Examples include binder jet printing [1], extrusion [2,3], and selective laser sintering [4–6]. Transparency is difficult to achieve in these processes because glass, unlike metal, retains a high viscosity when molten so that bubbles formed or trapped
during deposition do not have time to consolidate and escape the melt region via buoyancy [7]. However, bubbles can be extracted from green parts printed with glass nanoparticles using a very gradual post deposition burn-out/densification thermal treatment. This approach was realized by Nguyen et al. [8] using an extrusion process and by Kotz et al. [9] using a sterolithography process. Klien et al. [2] demonstrated printing intricate vases by allowing molten glass to flow under gravity through an orifice and onto a CNC controlled build plate. Similarly, molten glass can be extruded through a heated nozzle following a Fused Deposition Modeling (FDM) type approach. This process has been developed by Micron3DP [10] and requires significantly more robust nozzles compared to printing plastic parts. An even smaller molten region can be achieved by feeding semi-rigid glass filaments into a laser generated molten region [11]. This process allows the glass to reflow to fill track undulations and is capable of printing solid 3D parts. Further, the rapid cooling of the glass facilitates the printing of free-standing glass structures. Monitoring and control has been applied to regulate many variables in metal DED AM processes including temperature [12,13], melt pool geometry [14], and part height [15], and has been demonstrated to significantly improve part quality [16]. However, monitoring and
☆ ⁎
This paper was recommended for publication by Associate Editor Dr. D Hoelzle. Corresponding author. E-mail address: [email protected] (D.A. Bristow).
https://doi.org/10.1016/j.mechatronics.2018.06.002 Received 4 October 2017; Received in revised form 19 April 2018; Accepted 6 June 2018 0957-4158/ © 2018 Elsevier Ltd. All rights reserved.
Please cite this article as: Peters, D., Mechatronics (2018), https://doi.org/10.1016/j.mechatronics.2018.06.002
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control of the AM of glass has not yet been explored. There are a number of differences that exist between metal and glass that affect the process control of the AM of glass. The most notable difference is that glass is much more viscous than liquid metal and glass gradually transitions from a solid into a liquid (and back) over a range of temperatures instead of melting nearly instantaneously at a specific temperature. This slow melting process allows bubbles to form and remain in the glass, severely reducing optical quality. Further, the high viscosity of glass creates significant processing forces between the filament and the molten pool of glass, which can cause the molten glass to be displaced from its desired location. This paper will explore melt pool temperature regulation to control bubble formation, and path planning to maintain a constant filament feed direction for track morphology control of the AM of glass. The rest of this paper is organized as follows: Section 2 presents an overview of the glass additive machine including the energy source, motion system, filament feeder, and software architecture. Section 3 presents a melt pool temperature controller and experimental results. A four-axis path generation algorithm that maintains a constant filament feed direction is given in Section 4 and experiments are conducted to demonstrate the efficacy of this approach. Section 5 presents the results of printed parts and Section 6 summarizes the paper and draws conclusions of this work. 2. Machine overview In order to print glass in a predictable and repeatable manner, the glass additive process must be able to
• heat the glass in a small area to a temperature where it can flow and • • • •
be deposited, while allowing the glass to cool and solidify quickly after deposition; minimize thermal stresses that can weaken the part as it cools; deposit the glass at a specified rate, in precisely controlled locations; print a wide variety of shapes and patterns with multiple types of glass, multiple sizes of raw stock, and varying process parameters; be capable of reheating previously deposited glass to smooth out irregularities that would decrease its optical properties. Fig. 1. Build area of glass AM machine.
With these considerations, the machine was designed to have a laser entering the build area from the top, with glass filaments being fed in from the side to create a melt pool at a fixed point. The substrate moves relative to the melt pool as the glass is deposited to build a part. A closeup view of the build area is shown in Fig. 1. A heated build plate is used to hold a substrate, which is typically the same material of the glass being printed. This plate is kept at a high temperature to help reduce stresses caused by the thermal expansions of the substrate and printed glass. The laser is focused onto a filament of glass that, once placed on the substrate, creates a melt pool. The build plate and substrate are moved past the stationary melt pool using a four-axis motion system whose motion creates the desired part geometry for a layer. The glass filament is continuously fed into the melt pool using a filament feeder. As the molten glass moves away from the laser, it quickly cools and solidifies in place. Once a layer of glass has been printed, the substrate is lowered and a new layer is printed. A shutter is placed in the path of the laser and is used to block the laser before and after printing a continuous path.
CO2 laser (Synrad Evolution 125, λ0 = 10.6 µm, 162.5 µm spot size) was chosen as the energy source. It is directed at the substrate through a series of optical elements. The laser is defocused such that the spot size is equal to the filament diameter, i.e., 2 mm. A Focal-π Shaper transforms the intensity distribution of the laser beam from a Gaussian distribution into a flattop distribution. The laser power is measured by splitting 1% of its energy into a thermopile type power meter (Ophir 10A-V1). An OceanOptics USB-4000 fiber-coupled spectrometer (calibrated with an OceanOptics LS-1-CA 2800 K light source) is used to observe the spectrum of incandescent light emitted during the printing process. A LumaSense Technologies IMPAC IN140-L pyrometer is also focused on the melt pool in order to measure the temperature of the glass while printing. 2.2. Motion system The motion system must be able to closely follow the commanded path at the commanded speed to precisely place the glass. At the same time, the direction of deposition relative to the filament feed direction affects track morphology and optical quality. Thus, orientation control is also necessary to achieve consistent deposition of good quality glass. While these relationships are explored in more detail in Section 4, it is notable that this appears to be a challenge unique to glass DED. Other filament-fed processes such as polymer FDM use a heated nozzle to direct the material orthogonal to all print directions in the X-Y plane,
2.1. Energy source The energy source must be able to heat the glass filament above the highest transition temperature of all types of glass that will be printed. For this machine, fused quartz glass with a transition temperature of 1665 °C is the glass with the highest transition temperature that has been printed. It must also be able to reheat previously deposited glass to allow it to reflow. To achieve such requirements, a continuous-wave 2
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while the material in metal wire-fed DED processes has such low viscosity that directional dependency may be minor. Therefore, the motion system consists of three orthogonal linear axes, denoted X, Y, and Z, and a rotational axis, denoted C, that rotates around the Z axis. While depositing glass, the maximum linear deposition speed is on the order of 1–5 mm/s. However, even at low deposition speeds, a rotation in the print direction can necessitate rapid rotation of the C axis and rapid traversal of the X and Y linear axes. Some deposition paths presented in Section 4 require rotational speeds above 270°/s and linear axis speeds up to 300 mm/s. The X and Y axes are powered by direct drive linear servomotors (Aerotech ANT130-160-XY) each having a maximum speed of 350 mm/ s, maximum acceleration of 10 m/s2, and a maximum force of 23 N. The position of each linear axis is measured by a linear encoder with a resolution of 1 nm. The Z axis is a linear ball-screw stage driven by a direct drive servomotor (Aerotech ATS100-150) with a maximum speed of 100 mm/s and a maximum load of 98.1 N. Its position is measured by a rotary encoder on the drive motor with a resolution equivalent to 0.1 µm [17]. The C axis is powered by a direct drive servomotor (Aerotech ANT130-360-R) with a maximum speed of 200 rpm, a maximum acceleration of 400 rad/s2, and a maximum continuous torque of 0.2 N-m. Its position is measured by a rotary encoder with a resolution of 0.01′′ [18]. A kinematic model of the machine will be used to convert path planning in the workspace frame into motion commands for the machine axes. Let the baseframe be defined by the frame {x0, y0} and the workspace frame by the frame {xw, yw}, as illustrated in Fig. 2. Given axis positions xc, yc, θc, the transformation from workspace coordinates to base coordinates is,
⎡ cos θc − sin θc x c ⎤ Tw0 (x c , yc , θc ) = ⎢ sin θc cos θc yc ⎥. ⎢ ⎥ 0 1 ⎦ ⎣0
sin θc − x c cos θc − yc sin θc ⎤ ⎡ cos θc T0w (x c , yc , θc ) = ⎢− sin θc cos θc x c sin θc − yc cos θc ⎥. ⎢ ⎥ 0 1 ⎣0 ⎦
(2)
Let the vector s represent the fixed location of the melt pool (i.e., the intersection of the filament and laser) in the baseframe and let θv0 and v0 represent the angular and vector direction, respectively, of the filament feed in the baseframe. Then, the corresponding location and filament feed direction, in the workspace frame, are given by, 0
0 0 w ⎡ sx ⎤ ⎡ (sx − x c )cos θc + (s y − yc )sin θc ⎤ s w = ⎢ s yw ⎥ = ⎢− (s 0 − x c )sin θc + (s 0 − y )cos θc ⎥, x y c ⎥ ⎢ ⎥ ⎢ ⎥ ⎣1 ⎦ ⎢ ⎦ ⎣1
(3)
and
vw
w 0 ⎡ cos θv ⎤ ⎡ cos(θv − θc ) ⎤ w 0 ⎢ = ⎢ sin θv ⎥ = sin(θv − θc ) ⎥, ⎥ ⎢ ⎥ ⎢ ⎣0 ⎦ ⎣0 ⎦
(4)
s 0,
θv0
and desired respectively. Therefore, given alignment information workspace position, sw, and orientation, θvw , axis commands can be obtained by solving (3) and (4),
θc = θv0 + θvw
(5)
x c = sx0 − sxw cos(θv0 + θvw ) + s yw sin(θv0 + θvw ),
(6)
yc = s y0 − sxw sin(θv0 + θvw ) − s yw cos(θv0 + θvw ),
(7)
2.3. Filament feeder A schematic of the filament feeder is shown in Fig. 3. The filament is fed by a drive wheel connected to the motor by two belts. A gear reduction is used to provide finer positioning of the filament. The filament is guided by a stainless steel tube inserted through the body of the feeder, with a PTFE lining to prevent the filament from being scratched, which can be a source of microbubbles in the printed part. The drive wheel is attached to the end of a spring-loaded, rotating arm that allows it to apply pressure to the filament for traction. The drive wheel contacts the filament through a notch in the top of the guide tube, and has a rubber surface to help grip the filament. The filament feeder is powered by a direct drive brushless servomotor (Yaskawa SGMJV-01A3M61) with a maximum speed of 750 rpm, a maximum acceleration of 47800 rad/s2, and an instantaneous peak torque of 1.11 N-m [19]. The feeder positionis measured by a rotary encoder inside the motor with a resolution of 10′′. The gear and belt system reduces the motor rotational speed by a factor of 12. Based on
(1)
T w w Then, a point located at pw = [ px py 1] in the workspace can be 0 w 0 located in the base frame by p = Tw p . Likewise, a vector oriented at T v w = [ vxw vyw 0 ] in the workspace is oriented in the base frame di0 rection, v 0 = Tw v w . Conversely, the inverse transformation from base frame coordinates to workspace coordinates is,
Fig. 2. Two dimensional kinematics of glass AM machine.
Fig. 3. Filament feeder schematic. 3
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Fig. 4. System block diagram.
being added from the laser, losses to the environment via convection, radiation, and conduction to the substrate and the filament, along with the balance of cold glass and hot glass, entering and exiting the molten region, respectively. Practically, this means the molten region temperature is a function of the laser power, scan speed, filament feed rate, and substrate temperature, as well as the geometry of the part being printed. Developing process maps is a time consuming exercise that must be repeated for each part geometry and each type of glass (e.g., soda lime and borosilicate glasses have dramatically different thermal properties). In addition, the process mapping approach cannot adapt to natural disturbances that affect the process (e.g., change in heat transfer conditions when printing the corners of a part). In this section a closedloop melt pool temperature control system is designed to monitor the melt pool temperature and regulate it to a constant value by automatically adjusting the laser power.
the motor’s maximum speed and a drive wheel with a radius of 11 mm, the feeder is capable of feeding at speeds from 0 to 70 mm/s. 2.4. Software architecture The stages, filament feeder, and laser are controlled by a data acquisition and control system (National Instruments PXIe-1082 Chassis, PXIe-8135 Controller, PXIe-6356 Multifunction DAQ, PXIe-6612 Timing and Digital I/O DAQ, PXIe-6733 Analog Output DAQ) using a custom program made using National Instruments LabVIEW. The PXI system uses a deterministic operating system that provides predictable timing behavior, which is necessary for reliable feedback control. Using a sampling frequency of 5000 Hz, this program generates path plans and reference signals for the motion system axes and filament feeder, receives data from the encoders and pyrometer, executes control algorithms for all of the feedback loops, and sends control signals to the motors and laser. A block diagram of the system is shown in Fig. 4. Separate feedback control loops are tuned for position tracking of each of the motion system axes (X,Y,Z,C) and of the filament feeder. While constant speed deposition is typically desired, the necessity of aligning the wire feed direction with the print direction generates complex coordinated X,Y,C stage motions with significant velocity and acceleration variations (discussed in Section 4). Velocity-tracking constraints on these axes can result in decreased deposition speed and, thus, a dynamically changing filament speed reference. Feedback control of the melt pool temperature, necessary to maintain good glass optical and mechanical properties, is discussed in Section 3.
3.1. Melt pool temperature sensing In order to create a closed-loop melt pool temperature control system, the glass additive machine must be able to measure the melt pool temperature while the part is being printed without interfering with the printing process. A pyrometer, which collects infrared radiation to measure temperature, was chosen since it is a noncontact sensor that can sense the melt pool temperature without affecting the melt pool, or itself being damaged by the extreme environment of the processing zone. The temperature sensor is a LumaSense Technologies IMPAC IN140-L pyrometer, which has a temperature range of 500–2500 °C and an uncertainty of 1.2% [21]. This temperature range was selected since borosilicate glass transitions into a liquid at approximately 550 °C and will vaporize well before 2500°C. The pyrometer outputs an analog signal that is read by the PXIe-6356 multifunction card.
3. Melt pool temperature control The clarity (i.e., absence of bubbles of striae) and morphology of the printed glass is strongly dependent on the melt pool temperature. The properties of glass, including viscosity, are highly temperature dependent. If the melt pool is too cool, the glass will not become sufficiently molten and filaments will break or deflect away from the laser beam, generally leading to an unrecoverable build failure. On the other hand, if the melt pool is too hot, the process will overheat the glass, leading to vaporization of the glass and formation of bubbles via precipitation (reboil) or entrapment due to rapid slumping. This leads to reduced optical and mechanical properties [20]. Therefore, reliable control of the melt pool temperature is of critical importance. The temperature of the molten region is dependent on the energy
3.2. Melt pool temperature process modeling An empirical melt pool temperature process model is developed that relates the measured melt pool temperature to the laser power. The model used for controller design is an experimentally-constructed frequency response of the melt pool temperature process. Without feeding glass filaments, the laser traced a circular path having a diameter of 40 mm on a borosilicate substrate at a scan velocity of 1 mm/s. While this scan speed is larger than scan speeds typically used in processing glasses, 1 mm/s was used to avoid overmelting the substrate. Feedback 4
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Fig. 5. Melt pool temperature frequency response.
Fig. 6. Melt pool temperature closed-loop frequency response.
3.4. Melt pool temperature process experiments
will allow the controller to account for modeling uncertainties from using a high scan speed and no filament in the modeling experiments. Glass filaments were not fed during the modeling process as the filaments are not long enough to last the entire duration of the experiment (i.e., 2 h). During the modeling process, the nominal commanded laser power was set to 25 W and the melt pool temperature was measured with the pyrometer. Using an Agilent 35670A Dynamic System Analyzer (DSA), a sinusoidal excitation source with an amplitude of 2 V, which corresponds to ± 10 W, was injected into the nominal commanded laser power signal. The DSA swept over a range of frequencies from 0.1–62.8 rad/s and simultaneously measured the temperature and total laser power (i.e., nominal plus DSA excitation). A lower bound of 0.1 rad/s was selected as this is the lowest frequency the DSA can reliably operate at and an upper frequency of 62.8 rad/s was selected as it will be seen that it is well beyond the bandwidth of the melt pool temperature process. Using the collected data, the DSA generated a frequency response of the melt pool temperature process (i.e., the process relating melt pool temperature to commanded laser power). The melt pool temperature process frequency response is shown in Fig. 5. For frequencies under 20 rad/s the process exhibits a linear, firstorder response. This is expected since the heat transfer process is dominated by conduction to the substrate. For frequencies above 20 rad/s, the magnitude and the phase drop off sharply. This is likely due to sensor dynamics and nonlinear effects such as radiation heat transfer.
In order to test the efficacy of the melt pool temperature control system, two sets of experiments were conducted where a single track with six layers was printed. In each set of experiments, two trials were conducted: one with constant process parameters and one with melt pool temperature control where the controller automatically adjusted the laser power to regulate the melt pool temperature at 1065 °C. The process parameters for the first set of experiments, trials 1 and 2, were a scan speed of 0.2 mm/s, a filament feed rate of 0.2 mm/s, and a height increment between layers of 1.25 mm. In trial 1 the laser power was maintained at a constant value of 32 W. This process parameter set has been shown to print acceptable tracks for borosilicate glass [20]. The resulting wall is shown in Fig. 7(a). In trial 2 the temperature controller was implemented and the resulting wall is shown in Fig. 7(b). Note that neither wall had visible bubbles. The temperature time histories for both trials are shown in Fig. 8 for layers 2, 3, 4, and 5. There are
3.3. Melt pool temperature process control Since there is a tremendous amount of uncertainty in the high frequency range (i.e., above 20 rad/s), loop-shaping techniques were utilized to design a controller that tracks constant references while not exciting frequencies above 20 rad/s. Using the empirical melt pool temperature process model given in Fig. 5, the following controller transfer function was designed
P (s ) s+5 =5 ET (s ) s (s + 2)2
(8)
where P is the commanded laser power (W) and ET is the melt pool temperature error (°C). The integrator allows the controller to track constant reference signals and reject constant disturbances. The closedloop frequency response is shown in Fig. 6. The closed-loop bandwidth is 20 rad/s and has less than 2% error and less than 5° phase deviation for frequencies below 10 rad/s.
Fig. 7. Glass walls printed using (a) 0.2 mm/s scan speed, constant 32 W laser power (trial 1) (b) 0.2 mm/s scan speed, temperature controlled at 1065 °C (trial 2) (c) 0.31 mm/s scan speed, constant 50 W laser power (trial 3) (d) 0.31 mm/s scan speed, temperature controlled at 1065 °C (trial 4). 5
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Fig. 8. Temperature time history response for scan velocity = 0.2 mm/s.
Fig. 9. Temperature time history response for scan velocity = 0.31 mm/s.
variations in the melt pool temperature as each layer begins fabrication. While trial 2 (i.e., with control) regulates the temperature with less variation then trial 1 (50.2 °C compared to 56.3 °C), they both maintain a similar average melt pool temperature (1059 °C and 1060 °C for uncontrolled and controlled, respectively) that is sufficient to print glass without bubbles. In the second set of experiments, trials 3 and 4, the scan speed and filament feed rate were both increased to 0.31 mm/s to increase the build speed by over 50%. In trial 3 a constant laser power with a value of 50 W was used to maintain approximately the same energy density, which is proportional to laser power divided by scan speed, used in the trial 1. The results for trial 3 are shown in Fig. 7(c). In this build, periodic bubble formation was observed. It is believed that even though the energy distribution is the same in both sets of experiments, the heat distribution from the top to the bottom of the filament is different and, in trial 3, the temperature on the top of the filament was much hotter leading to reboil and the formation of bubbles [20]. In trial 4 the temperature controller was implemented, and the resulting wall is shown in Fig. 7(d). It can be seen that the temperature was maintained at a lower value and the wall was free of bubbles. Therefore, the use of melt pool temperature control allowed the build speed to be significantly increased without affecting the part properties. The temperature time histories for both trials are shown in Fig. 9 for layers 2, 3, 4, and 5. In this case trial 2 (i.e., with control) regulates the
Fig. 10. (a) Photograph and (b) 3D scan of glass beads printed at various orientations relative to the wire feed direction.
temperature with significantly less variation then trial 1 (62.2 °C compared to 158 °C) and with an average melt pool temperature much closer to the desired value (1058 °C compared to 1182 °C). The elevated temperature caused bubble formation in trial 3 (i.e., uncontrolled) as seen in Fig. 7(c). The ability to regulate the melt pool temperature allowed for the fabrication of bubble-free glass parts.
4. Five-axis path and trajectory generation One of the primary advantages of additive manufacturing is the ability to create shapes and patterns that would otherwise be difficult or impossible to fabricate using conventional manufacturing methods. Therefore, it is important for the machine to be capable of creating complex geometries rather than placing limits on the features that can be designed. The process itself is limited by factors such as the 6
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Fig. 12. (a) Workspace path with 180° direction change and (b) individual axes along the path showing orientation filtering. Fig. 11. Cross section of bead showing morphology when printing (a) aligned with wire feed direction and (b) opposing wire feed direction.
altering forces. However, at 60°, the differing velocities create a shear on the bottom of the melt pool stretching the melt pool and making it wider and, thus, shallower. More extreme behaviors occur near 180°, also shown in Fig. 10. Here the filament feeds in the opposite direction of the scan velocity. In this case, a relatively stiff filament is pushing into the melt pool, forcing the hotter, softer glass out of the way. At precisely 180°, the melt pool is pushed to either side, resulting in a valley at the center of the track, while angles slightly off of 180° tend to push the track off to the nearer side. In order to achieve precise deposition of the glass, it is therefore necessary to keep the deposition direction near to 0° throughout the process. Here, a constraint of no more than 30° from 0° alignment is used. To achieve this orientation control while printing in different directions, the substrate is placed on a rotational stage. Path planning for the combined system is presented in the following section.
sensitivity of glass morphology to feed direction as well as the capabilities of the motors that drive the machine. In order to prevent these factors from affecting the quality of the fabricated part, they are incorporated into the path and trajectory design. 4.1. Effect of feed direction on bead morphology One important property of glass is that instead of melting at a specific temperature, its viscosity smoothly transitions over a temperature range. As the filament enters the melt pool and is exposed to the laser, it retains some of its viscosity for a short period of time, which means that it can distort the shape of the melt pool and the track of glass it deposits. Therefore, the printed track morphology is significantly affected by the direction from which the filament is fed. Fig. 10 shows an image and 3D scan of tracks printed at 30° increments with respect to the filament feed direction, with 0° referring to the filament feeding in the direction of the scan velocity. The tracks were printed with 2 mm diameter stock, a scan speed of 1 mm/s, a filament feed rate of 1 mm/s, and a laser power of 40 W. Cross sections of the scanned tracks is shown in Fig. 11. As can be seen in Figs. 10 and 11, for a feed direction near 0° the melted track is slightly shorter (1.5 mm) and slightly wider (2.4 mm) than the 2 mm feedstock. Small rotations (<30°) from 0° show similar geometries; however, by 60° the track is noticeably shorter and wider. The changing morphology can be understood as follows. When the glass is fed at 0°, it begins heating via conduction, softening slightly before entering the melt pool where it fully softens, slumps, and adheres to the melt pool traveling at the same velocity and thus, minimizing shape-
4.2. Spatial path generation The spatial path is typically generated by a CAD slicer program that transforms solid model geometries into the path, often consisting of border and rastered in-fills in a layer-by-layer fashion. Let p ∈ [0, L] represent the location along a desired path of length L, and xw(p), yw(p), and zw(p) the corresponding desired spatial coordinates of the path in the part frame. Further, assume that the path is continuously differentiable, x w (p), y w (p), z w (p) ∈ C1. As discussed in the previous section, the print quality is best when the feed direction aligns with the scan velocity. Therefore, the desired print direction is defined as,
θ w (p) = atan2 ⎛⎜ ⎝ 7
dy w (p) dx w (p) ⎞ , ⎟, dp dp ⎠
(9)
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Fig. 13. (a) Photo of star printed with directional control, (b) photo of star without directional control, (c) height of star printed with directional control, and (d) height of star printed without directional control.
Then, the largest orientation error can be determined as,
where atan2(y, x) is the arctangent of a point at location (x, y). While small deviations in the print orientation do not demonstrate measurable impact on print quality, smoothing of the print orientation can significantly reduce the necessary tracking bandwidth. Therefore, we will consider θfw , a smoothed version of θw, as the reference. To maximize accuracy and eliminate delay effects, the smoothed function can be generated using a zero-phase filter, for example with the forwardbackward filtering procedure,
θFw (p) = F (s ) θ w (p),
(10)
θBw (p) = F (s ) θFw (−p),
(11)
θfw (p) = θFw (−p).
(12)
max θfw (p) − θ w (p) ≤ p
180 (1 − e−πar ). 2πar
(13)
In the remainder of this work, the smallest radius utilized with be r = 1 mm, and the maximum desired orientation will be set to 30°. Thus, a filter pole of a = 0.9 mm−1 will be used. The spatial filament feed rate, F(p) is typically desired to be constant to create a uniform morphology throughout the layer. However, the filament feeder is controlled using a position-control loop in order to, for example, ensure metered material addition at filament starts and stops. Thus, the filament feed position command along the path is,
fc (p) =
where F(s) is a suitable lowpass filter. The maximum desired orientation deviation, maxp θfw (p) − θ w (p) , can be constrained through filter design. For example, consider the first-order filter, F (s ) = a/(s + a), where a is the filter bandwidth in rad/mm, and a 180° direction change in the path with radius, r. Such a trajectory is illustrated in Fig. 12.
∫p
p
F (λ ) dλ
0
4.3. Trajectory design The workspace frame path generated in the previous section as 8
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Fig. 14. Multi-layer star wall fabricated using the star trajectory design.
xw(p), yw(p), zw(p), θfw (p), are converted into axis references xc(p), yc(p), zc(p), θc(p) using (5)–(7) and the additional trivial kinematic relation, z c (p) = z w (p) . In the following, the temporal trajectory commands are generated for the axes in order to generate a desired deposition spatial feed rate along the path while also considering actuator velocity and acceleration constraints. Let vdes(p) represent the desired deposition velocity along the path. Further, let x v , yv , zv , θv , fv represent the maximum absolute velocities for the X, Y, Z, C, and F axes, respectively. Then, the desired deposition velocity exceeds the maximum axis velocity in X when
Fig. 15. Glass spring demonstrating good dimensional control in freespace printing.
5. Part fabrication Two parts were fabricated using the AM of glass machine. The first part is a star wall where 6 layers of the star in Section 4.4 was fabricated with the melt pool temperature controller and the path and trajectory generator. A picture of the part is shown in Fig. 14. This part demonstrates the ability of tracks to bond with previous layers without visually altering the previous layer’s morphology. Note that a small amount of local reflow does exist that, when controlled, can be useful when fabricating solid parts. The consisting printing around each layer illustrates the efficacy of the path and trajectory generation methodology, and the fact that each layer is bubble free demonstrates the efficacy of the melt pool temperature controller with changing heat transfer conditions. The second part that was fabricated was a glass spring. A picture of the spring is shown in Fig. 15. Note that the entire spring, with the exception of the first layer, was fabricated without support and nearly in the horizontal direction. Slumping is avoided due to the high viscosity of glass, as well as the quick solidification when operating with the correct process parameters.
dx (p) dx (p) = vdes (p) c ≥ x v, dp dt and similarly for Y, Z, C, and F. Now, the deposition velocity can be reduced to avoid actuator velocity constraints using,
v (p) = vdes (p)·min
⎧ x v , ⎨ dx c (p) ⎩ dp
yv dyc (p) dp
,
zv dz c (p) dp
,
θv dθc (p) dp
,
fv dfc (p) dp
⎫ ⎬ ⎭
. (14)
Acceleration constraints are applied in a similar manner. Then, the trajectories are generated using,
t (p) =
∫p
p
0
1 dτ v (τ )
(15)
6. Summary and conclusions 4.4. Experiments This paper presented a mechatronic system specifically designed for the AM of glass. An overview of the machine was given including descriptions of the energy source used to generate the melt pool, the motion system used to create the scan velocity, the custom-designed filament feeder used to feed the glass stock into the melt pool, and the architecture of the software system used for monitoring and control. An empirical model of the melt pool temperature process was constructed in the frequency domain and loop-shaping techniques were used to design a feedback controller. The temperature control solution was compared against a constant power density solution at two feed rates. At nominal feed rate, both methods demonstrated ability to print glass without bubble defects, but only the temperature feedback method
A star pattern was designed and printed using this path and trajectory planning method, shown in Fig. 13. The sides were each 15 mm in length, and the corners had radii of 1 mm. The path was printed at a nominal scan rate of 1 mm/s, with the filament being fed into the melt pool at a rate of 1 mm/mm of travel. The melt pool temperature was controlled to 2000 °C. Also shown in Fig. 13, for comparison, is the same star generated without orientation change and using a scan velocity of 1 mm/s and a filament feed rate of 1 mm/s. As can be seen in the height scans, the orientation-control of the path-planned solutions shows much stronger uniformity in bead morphology and geometric accuracy. 9
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maintain good quality at elevated feed rate. The effect of feeding glass filaments at various orientations with respect to the scan velocity was also investigated. Tracks printed at a range of orientations around 0°demonstrated a consistent morphology. A path planning methodology was created to ensure the print orientation remained in this range and a trajectory generation method was used to prevent actuator saturation. Compared against a fixed-direction feed orientation, the path planning method demonstrated significant improvement in the uniformity of the track morphology. Finally, the glass AM machine was used to fabricate two parts: a multi-layered star wall and a spring. The effectiveness of the methods were demonstrated in the bubble-free parts with consistent track morphology. Notably, the spring also demonstrated the ability of the process to print in freespace, without structural support. Future work will consist of modeling track morphology as a function of process parameters, including feed direction, for various types of glasses. We will create morphology control schemes and integrate them with our existing temperature controller. This work will be experimentally verified by building thin walls and then expanded to the fabrication of blocks and other parts with infills.
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Acknowledgments This work was supported by the National Science Foundation (CMMI-1538464) and the Air Force Research Laboratory. References [1] Marchelli G, Prabhakar R, Storti D, Ganter M. The guide to glass 3d printing: developments, methods, diagnostics and results. Rapid Prototyp J 2011;17(3):187–94. [2] Klein S, Dickin F, Adams G, Simske S. Glass: an old material for the future of manufacturing. Tech. Rep.. Hewlett-Packard Development Company Technical Report; 2012.
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