A semi-continuous Roll-to-Roll (R2R) electrohydrodynamic jet printing system

Mechatronics 31 (2015) 243–254

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Mechatronics journal homepage: www.elsevier.com/locate/mechatronics

A semi-continuous Roll-to-Roll (R2R) electrohydrodynamic jet printing system Erick Sutanto a, Andrew Alleyne b,⇑ a b

Dow Chemical Company, IR – Robotics and Lab Automation, 400 Arcola Rd, Collegeville, PA 19406, USA University of Illinois at Urbana Champaign, Mechanical Science and Engineering Department, 1206 W. Green St, Urbana, IL 61801, USA

a r t i c l e

i n f o

Article history: Received 16 February 2015 Accepted 18 August 2015 Available online 26 September 2015 Keywords: Manufacturing Flexible electronics Roll-to-roll fabrication Electrohydrodynamic jet printing Iterative Learning Control

a b s t r a c t This article presents the initial integration of a new and novel additive manufacturing process with a web-based transport of a flexible substrate. The manufacturing process is the Electro-hydrodynamic Jet (E-Jet) printing process and the transport is a Roll-to-Roll (R2R) system. E-Jet printing affords a wide array of materials to be deposited at very fine resolutions, on the order of microns. The combination of E-Jet printing and R2R enables fabrication of flexible electronics and other novel flexible systems such as bio-sensors and optics. The design of a custom R2R system is presented, including the mechatronic integration of hardware and software architectures. A Norm-Optimal Iterative Learning Controller is coupled with a Linear Quadratic controller to control web motion and tension, both of which are important for accurate E-Jet printing. Results are presented demonstrating the ability to accurately position the web for printing. Subsequently, printing results are demonstrated for both conductive and non-conductive inks. The results demonstrate the clear feasibility for fine scale printing, suitable for flexible electronics, on a continuous R2R process. Ó 2015 Elsevier Ltd. All rights reserved.

1. Introduction Nano and micro-manufacturing has emerged to be an essential component to progress in many areas of science with a huge potential to foster innovation and economic growth. Recent advances in micro/nano-manufacturing have transitioned from batch modes of fabrication on the traditionally rigid substrates to continuous modes of fabrication on flexible substrates. The majority of these continuous systems utilize a Roll to Roll (R2R) system approach [1–4]. Both subtractive and additive processes are possible within a R2R manufacturing system. However, the additive processes have received significant recent attention from the industry for the many benefits they offer. It is projected that by the year 2019, the printed electronics industry may reach a market value of around US$ 59 billion [2]. Some of the advantages of additive processes include the scalability to cover a large area, the flexibility to manufacture highly customizable patterns, and generating less environmental waste. Many experts believe that the adaptation of additive processes to R2R systems is the solution for achieving low cost products in the future [2,5].

⇑ Corresponding author. E-mail address: [email protected] (A. Alleyne). http://dx.doi.org/10.1016/j.mechatronics.2015.08.002 0957-4158/Ó 2015 Elsevier Ltd. All rights reserved.

Gravure printing, flexographic printing, inkjet printing, and nano-imprint lithography (NIL) are a few examples of readily available additive manufacturing processes that are compatible with R2R approaches. Among these processes, inkjet printing is thus far the only non-contact additive process adopted in commercial R2R platforms. Inkjet printing is a flexible manufacturing process because it is digitally driven. It is suitable for applications which require a high degree of pattern customization, such as radio frequency identification (RFID) and smart labels. One of the limiting factors of inkjet printing is the maximum achievable feature resolution, which is in the order of tens of microns [6]. In recent years, Electrohydrodynamic-jet (E-Jet) printing has emerged as a high resolution alternative to the previously mentioned direct solution-based fabrication approaches [7]. It is an alternate printing technique for solution-based deposition applications requiring resolutions between 100 nm and 10 lm. Recent advancements in E-Jet printing speed and reliability have transformed this technology from a laboratory research tool to a viable manufacturing process [7–9]. However, the needs to obtain high resolution features on a R2R manufacturing system motivates this feasibility study of E-Jet printing in a R2R system environment. E-Jet printing uses an electric field to induce fluid flows from micro capillary nozzles to create devices in the micro/nano-scale range [7]. This method easily surpasses the feature resolution for

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even state-of-the-art ink-jet fabrication technology. Unlike ink-jet, E-Jet can also be used for 3 dimensional printing of solid materials such as polymers [10]. Further manufacturing issues such as speed/throughput, droplet resolution/repeatability, ink variations and potential applications of the process have been addressed. In 2007, Park et al. reported various applications of the E-Jet process, primarily in the area of printed electronics [7]. Additional work [8] made improvements to the process including the resolution, reliability, and throughput. Since E-Jet is very flexible with respect to printing materials, including heterogeneous integration [9], there is a wide array of promising opportunities for printed electronics, biological sensing applications, and micro-optics [11–14]. What has been missing, to date, is the opening up of these opportunities to applications requiring flexible substrates. Filling this gap is the focus of the current work. Previous efforts have demonstrated success of E-Jet printing on rigid substrates, including the design and operation of basic E-Jet components [7–14]. The current work uses this expertise and, for the first time, presents an integration and demonstration of the E-Jet process printing on a continuous flexible substrate. The rest of this article presents successful initial efforts to integrate fine-scale additive manufacturing features from E-Jet printing into a R2R process and is organized as follows. Section 2 presents the design of the particular R2R web handling system under study and the integration with a custom-designed E-Jet printer. This section includes discussion on both the mechanical and electrical design. Section 3 discusses the operational procedure of the web handling system including the control of the web transport and tension, two key process control variables. Several printed results are presented on Section 4 and a conclusion in Section 5 provides an overview of the main contributions. 2. Experimental R2R/E-Jet system design and integration This section presents briefly describes the mechanical integration of the E-Jet printing system into a R2R platform. Additionally, we present the electronic schematics which enables the operation of this system. The interested reader is referred to [15] for detailed information on the design and the complete list of the mechanical and electrical components used assemble the R2R system described in this article. 2.1. Mechanical design of a R2R system A typical R2R system consists of a set of actuated and idler rollers interconnected by a web. By and large, a web is described as any flexible material processed in a continuous manner, e.g., paper, plastics, textiles and metal foil. Although R2R systems are a relatively mature technology, many batch processes are not readily compatible with the R2R approach. The focus in this section is on integrating the E-Jet printing system to the R2R environment. The physical picture of the R2R testbed system is presented in Fig. 1, where all modules are assembled on a 2 ft by 3 ft optical breadboard (TD-13, Newport). The breadboard allows for reconfiguration of the system and is secured on two pieces of heavy duty steel posts on both ends. Within the web handling module, two actuated rollers, commonly termed the winder (unwinder and re-winder) rollers, translate the web in the longitudinal direction. These are rollers #1 and #11 in Fig. 2(a). To complement the actuated rollers, several idler rollers (UL-300-050 X7”MOD, Webex) are used to define the trajectory which the web undergoes. The shafts of the idler rollers are statically mounted on an aluminum hub except for one idler roller (#3) attached to a load cell for measuring instantaneous web tension. All idlers utilize roller bearings. A high resolution ring

encoder (RESM20USA075, Renishaw) is attached to one of the idler rollers (#9) adjacent to the E-Jet printhead to provide an accurate measurement of web translation. This position measurement, in conjunction with the tension measurement from the load cell, are necessary for handling the web in the longitudinal direction. As will be seen, the web tension is important for maintaining a suitably flat printing surface. In conjunction with the longitudinal web positioning control, a laser scanner is used to monitor the web lateral position and a web-guide is utilized to actuate the web in the lateral direction. With other E-Jet printers, the nozzle tip is held stationary at approximately 30 lm above the conductive substrate [7]. Additionally, patterns are printed by translating the substrate relative to the stationary nozzle. E-Jet printing on a R2R configuration is operated inversely, where the web or the substrate on which the E-Jet droplets are printed does not move during printing; rather the nozzle tip is translated to produce the intended pattern. Moreover, since the web is a flexible material, such as a polymer, it is not electrically conductive and thus cannot dissipate charge as efficiently as printing on a silicon wafer. Therefore, a stainless steel backing plate is connected to the ground terminal of the E-Jet voltage amplifier and placed underneath the web to connect the electric field generated between the nozzle and the ground plate shown in Fig. 2(b). A uniform electric field is critical to high performance printing and uniformity requires a flat printing surface. For this reason, good tension control is important. As shown in Fig. 2(b), the E-Jet printing station is placed slightly higher with respect to the neighboring idler rollers. Consequently, when tension is applied, the web will always pull the web downward against the printing ground plate and thereby minimize any insulating air gap. The ground plate is also polished to ease the sliding of the web and improve the reflectivity of the light that is used for process monitoring. The E-Jet printhead is mounted on a motorized precision XY stage (MX80L, Parker) and a manual tip tilt stage (NT66-549, Edmund Optics) is placed underneath to align the nozzle tip with respect to the substrate. The nozzle holder is fabricated using rapid prototyping 3D printing and screwed on a manual linear Z stage. The Z stage is fixed beneath the XY stage and is used to adjust the standoff distance between the nozzle and substrate. A camera is placed adjacent to the E-Jet printing station and directed towards the nozzle tip to assist the calibration process and monitor the printing performance. On the R2R system, while the camera is mounted statically, the E-Jet printhead translates in the XY direction and may leave the field of view of the camera. For this reason, the camera cannot monitor the entire printing process. Nevertheless, the camera is still necessary to perform initial calibration of the E-Jet printer including setting the nozzle standoff distance and obtaining the optimal E-Jet printing voltage. 2.2. Electronics system design The electronics control systems governing the R2R E-Jet system are divided into three parts. There is a primary CPU which coordinates the motion of the E-Jet system with the voltage duty cycle described in Section 4. This communicates with two National Instruments Real Time (RT) targets. One of the RT targets is responsible for controlling the web transport and the other is responsible for controlling the E-Jet XY stage. The motivation for this was modularity to allow other items such as UV curing to be smoothly incorporated into the hardware platform in a piecewise fashion. A hierarchical connection diagram describing how the electronic modules are interfaced is presented in Fig. 3. The functionalities and coordination of both the RT targets are programmed using LabVIEW. The front panel of the LabVIEW graphical user interface (GUI) that controls the overall R2R E-Jet

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Fig. 1. A Roll to Roll platform for the E-Jet printing system. The web transport system is handled by a set of actuated and idler rollers. It enables high resolution printing on a continuous flexible media and reduces the overhead time to switch substrate.

Fig. 2. (a) The roller arrangement on the R2R system. The winder rollers (red color) coordinate the web tension and position using the encoder and the load as the feedback signal. (b) E-Jet printing station on the R2R system. Printed patterns are obtained by translating the XY stage on which the nozzle is mounted. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

printing system is presented in Fig. 4. This GUI allows the user to manually intervene and control the position and tension of the web, if desired, as well as to manually adjust the XY position and voltage level of the E-Jet printhead. The manual control of the EJet printhead is of use during alignment of the nozzle with the printing surface area. 3. R2R system modeling and control The control of the E-Jet process has been previously presented in the literature [8]. Therefore, we focus on the modeling and control of the R2R web handling system below. In the following several key assumptions are made. For the linear time invariant model of web transport the static friction is omitted. Additionally, we assume the web moves perfectly perpendicular to the axis of rotation of the rollers and all rollers are perfectly aligned. 3.1. Web handling model The R2R system presented in Fig. 2 consists of 9 idler and 2 actuated rollers which are interconnected with Kapton tape. A

detailed description of the transport dynamics is given in [15,16] with salient elements given here. The Free Body Diagram (FBD) of each of the rollers, Mi, can be generalized into Fig. 5, where the subscript i denotes the roller number. According to this FBD, the corresponding equation of motion is defined in (1). Here, hi ; h_ i

and € hi indicate the roller angular position and its time derivatives. For driven rollers, the motor torque, si, is proportional to the control input (2). The friction on each roller, fi, is assumed proportional  to the roller angular velocity as in (3). The web tension T þ i and T i rotate Mi in the positive and negative direction respectively as indicated by the green arrow in Fig. 5. Additionally, the web is assumed iþ1

to be a linear spring described by (4), where ki is the spring constant equivalence of the web in between the adjacent rollers. Most R2R systems in the existing literature [17–19] operate at several hundred feet per minute (fpm). At this speed, the radius, Ri, and inertia, Ji, of the rewinder and unwinder change rapidly due to web material transfer. However, since the R2R system in Fig. 2 will operate at less than 1 fpm, a Linear Time Invariant (LTI) model becomes a valid assumption.

J i €hi ¼ si þ Ri ðT þi  T i Þ  f i

ð1Þ

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Fig. 3. Electrical connection diagram of the R2R System. The Desktop RT system is responsible for the web handling system while the Compact RIO is responsible to control the E-Jet printhead XY motion and printing trigger.

Fig. 4. Graphical user interface of the R2R E-Jet printing system.

si ¼ K T ui ; i 2 f1; 11g

ð2Þ

f i ¼ bi h_ i

ð3Þ

T þi ¼ ki ðRiþ1 hiþ1  Ri hi Þ; iþ1

T i ¼ T þi1 ;

i 2 f2; . . . ; 11g

i 2 f1; . . . ; 10g

ð4Þ ð5Þ

Substituting (2)–(5) in (1), we obtain a MIMO LTI state-space representation describing the open loop system dynamics, P OL , where the system states are defined in (7). The inputs of POL are the analog signals sent to the motor drives, uM1 and uM2 , which actuate M1 and M11 respectively. The measureable system outputs are the angular position of M1, M9, and M11, as well as the web tension, TM. Here, þ TM is defined as the average value of T  3 and T 3 , and can thereby

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( POL $

Fig. 5. Free Body Diagram of a generalized roller. Forces acting on the roller are indicated by the red arrows. The green arrows indicate the direction of positive displacement and the blue arrows indicate the positive direction of motor torque. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

~ x41 þ B42~ u21 x_ ¼ A44~ ~ ~ y ¼ C 24 x41

The states of the reduced system are defined in (10) and the system dynamics, A, B, and C, are defined in (11). In POL, the instantaneous position of the web is assumed equal to h2 and the tension of the web is redefined in (12). The lumped spring constant equivalence of the web, k, can be obtained empirically from the experimental testbed by monitoring the change of web tension, DT M , as a function of Dðh2  h1 Þ. Based on experimental data, the approximate value of k is 7725.8 N/m for the particular thickness and width of Kapton tape used [15].

 ~ x ¼ h1

h_ 1

2

0 1 6 0  b1 6 J1 A¼6 60 0 4

u1 [V]

5

0

-5

0

0

2

4

6

8

10

u2 [V]

h_ 2



ð10Þ 3

2 0 7 6 KT 0 0 7 6 7 B ¼ 6 J1 60 0 1 7 5 4 b2 0  J2 0

0

0

0

3

  07 7 1 0 0 0 7C¼ 07 0 0 1 0 5

ð11Þ

KT J2

ð12Þ

3.2. Web handling model validation

0

0

2

4

6

8

10

12

Time [s] Fig. 6. Input signal generated by the controller to track the chirp reference.

be related to system states by (8). The formal state-space representation of the R2R system defined in (6) has 22 system states, 2 system inputs, and 4 measurable outputs. This configuration is neither controllable nor observable when analyzed using the parameters obtained in [15]; therefore, a model reduction is necessary.

~ x_ ¼ A2222~ x221 þ B222~ u21 ~ y ¼ C 422~ x221

ð6Þ


x2i1 ¼ hi i 2 f1; . . . ; 11g x2i ¼ h_ i

ð7Þ

T 3 þ T þ3 k2 ðR3 x5  R2 x3 Þ þ k3 ðR4 x7  R3 x5 Þ ¼ 2 2 3

TM ¼

0

h2

T M ¼ kðR2 h2  R1 h1 Þ ¼ kðR2 x3  R1 x1 Þ

12

5

-5

ð9Þ

4

ð8Þ

There is a harmonic drive attached to the motor shaft on each winder roller. The harmonic drive not only reduces the output speed of the motor, but also reduces the effect of any external torque applied at the end effector. This implies the dynamics of the winder rollers are relatively insensitive to the torque induced by the web tension. Assuming zero torque induced by the web tension on both winder rollers, the R2R system model can be greatly simplified into a 2 roller systems, i.e., the unwinder roller (M1) and the rewinder roller (M11) only. Since there are only two rollers being considered in the model, the indexing scheme will be slightly altered for notational convenience. Hereafter, the index i = 1 is assigned for the unwinder roller, while i = 2 is assigned for the rewinder roller. The reduced state-space model of the R2R system is presented in (9).

Reduction of the state space model from a 22 state system to a 4 state system may compromise the fidelity of the model, particularly if there are high frequency resonant modes that are ignored. It is therefore necessary to empirically validate the reduced order model with data taken from the experimental R2R system to determine if the level of compromise is sufficient for feedback controller design for the frequency range of use. The R2R system is a quasi-stable MIMO system thereby making open loop system identification impractical. Assuming the state space model closely represents the experimental system, a feedback controller can be designed to close the loop of the R2R system. Details on designing the simple LQ feedback controller can be found in [15]. This feedback controller allows the R2R system to track user defined position and tension reference profiles. Both reference signals are perturbed from a nominal value using chirp signals with a frequency content ranging from 0.01 Hz to 2 Hz. The resulting input signal generated by the feedback controller is presented in Fig. 6. The validation of the 4th order state-space model can be done by comparing the output response of the simulated model with the empirical data subject to the input signals presented in Fig. 6. Fig. 7 compares the web position signal from both the simulation model and the experiment with a resulting normalized RMS error of approximately 20% across the entire 12 s duration. Clearly, the model does better at lower frequencies but the overall RMS error makes the position model well within the bounds of effective feedback control. An examination of both the 4th order and 22nd order model in the frequency domain further justify the use of the lower order model. Fig. 8 shows the multi-variable input output relationship between the input torques at the unwinder and rewinder rollers and the respective roller angular positions. Above 1 Hz, the two models deviate significantly as some of the higher frequency modes are not captured. However, below 1 Hz, the models are very similar. Since the stepping motion of the web used for the E-Jet process is at a frequency below 1 Hz, as shown in Section 3, the 4th order model is sufficient for feedback design of the system. The comparison of the tension measurement between the simulation model and experiment is presented in Fig. 9. This tension model is not as accurate as the position model but is sufficient for regulation needs. As illustrated in Fig. 9, there is an

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Model

10

Experiment

0.8

8

0.6

6

0.4

4

0.2

2

TM [N]

Position [rad]

1

0 -0.2 -0.4

-4

-0.6

-6

-0.8

-8 12

14

16

18

20

Time [s]

Experiment

0 -2

-1 10

Model

-10 10

12

14

16

18

20

Time [s]

Fig. 7. Comparison of the web velocity responses between the simulation model and experimental results.

Fig. 9. Comparison of the web tension response between the simulation model and experimental results.

approximately 10° phase lag observed on the empirical web tension results, along with amplitude attenuation. The phase and magnitude errors are caused by the friction in the actuators. The friction model is challenging to capture accurately. The interested reader is referred to [20] for a rigorous friction modeling approach that, while effective, greatly increases the complexity of the parameter identification and potential compensation. Therefore, the approach taken here is to treat friction as a disturbance and uti-

lize appropriate feedback and feedforward controller designs to compensate for it. The low phase lag in the reduced order model (<10°) is more important than the magnitude offset since the tension will be treated as a regulation problem. Any offset in tension amplitude can be accommodated by an integrator in the feedback loop. According to the validation results, the reduced order model is sufficiently accurate to be used for designing feedback and our learning-based feedforward controllers.

Fig. 8. Frequency responses: (a) from unwinder torque (roller 1) to unwinder position (roller 1); (b) from rewinder torque (roller 2) to unwinder position (roller 1); (c) from unwinder torque (roller 1) to rewinder position (roller 2); from rewinder torque (roller 2) to rewinder position (roller 2).

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3.3. Web handling controller design: Linear Quadratic Feedback and Iterative Learning Control The web handling controller goals are to move the web in a series of modified steps to present the material for printing by the E-Jet system. Simultaneously, the web tension must be regulated so as to provide a flat printing surface. The semi-batch nature of E-Jet printing was necessary due to the constraints placed by the system design. In full manufacturing practice, it may be possible to perform continuous printing on a moving web but that was not afforded by the current design. Based on the plant model given in (9), a state feedback controller can be synthesized using Linear Quadratic Regulator (LQR) design principles with an objective of regulating both the position and tension of the web. The step by step procedures for obtaining the feedback controller gains to perform the web handling on the R2R system, along with the numerical parameters, can be found in [15]. The feedback gain obtained by the LQR technique is implemented on the web-handling realtime controller and the resulting tracking performance of the web handling system is presented in Fig. 10. The reference for the position is a modified step with a rate limit. Supplementing the time domain results given in Fig. 10 are frequency domain sensitivity plots shown in Fig. 11. As can be seen from the figures, the MIMO sensitivity plots illustrate diagonal dominance and the disturbance rejection bandwidth for the reference-to-error sensitivity functions have a bandwidth suitable for feedback control. The lower bandwidth of the position loop in Fig. 11(a) is reflected in the position regulation performance of Fig. 10. The regulation and tracking performance for the web positioning in Fig. 10 may not be adequate for R2R-based fabrication, particularly with respect to positioning overshoot. Therefore, a Norm Optimal Iterative Learning Controller (NOILC) was implemented e CL ). The to improve the performance of the closed loop plant ( P

0.2 0.15 0.1

r

0.05

y

Web Tension [N]

Web Position [rad]

serial form of the ILC architecture [21,22] as presented in Fig. 12 is employed along with the lifted domain Norm Optimal ILC (NOILC) framework [23,24] to generate the ILC input signals. The serial architecture is preferred because most industrial manufacturing systems have a closed architecture but still provide access to configure the references or set points to the system. At each iteration, the error and ILC input signals are stored in the system’s memory and are used to modify the ILC input signal at the next iteration. NOILC is a k  k2 optimization framework which minimizes a quadratic cost function described in (13), where j indicates

0

1 1

0

1

2

3

4

5

6

8

7

42 41 40

r2

39

y

2

38

0

1

2

3

4

5

6

7

8

Time [s] Fig. 10. Position tracking and tension regulation performance of the web handling system. The LQ feedback control introduces phase lag and overshoot on the position tracking but tightly regulates the web tension.

the iteration index. Here, e and u are the lifted error and input vectors, defined in (14). In (14), Q, R and S are symmetric positive definite matrices, commonly expressed as ðqI; rI; sIÞ where q; s; r 2 Rþ and I is an Identity Matrix of appropriate dimension.

 T J ¼ eTjþ1 Q ejþ1 þ uTjþ1 Sujþ1 þ ujþ1  uj Rðujþ1  uj Þ

ð13Þ

 e¼ ~ eð1ÞT eð0ÞT l ~  T u¼ ~ uð1ÞT uð0Þ ~

ð14Þ

   ~ eðN  1ÞT    ~ uðN  1ÞT

The resulting ILC control input from the quadratic optimization process, ujþ1 , is presented in (15). P 2 Rmo Nmi N is a lower triangular ~ CL to the system outToeplitz matrix that maps all system inputs of P puts in the lifted domain, where mi and mo denote the number of ~ CL , respectively. The matrix can be coninputs and outputs of P structed using (16), where each element in this matrix is a block matrix of size mo  mi. The interested reader is referred to [23] for detailed derivation of the learning gains in (15). For the solution of the NOILC algorithm to monotonically converge, (17) must be satisfied. By substituting (15) into (17), we obtain (18) which is required to be positive definite.

ujþ1 ¼ LU uj þ LE ej

1

LU ¼ P T Q P þ S þ R PT Q P þ R

1

PT Q LE ¼ P T Q P þ S þ R 2

C CL BCL

6 C A B 6 CL CL CL P¼6 .. 6 4 . C CL AN1 CL BCL

ð15Þ

0

0

0

C CL BCL

0 .. .

0 0

C CL ACL BCL

C CL BCL



kLu  Le Pki2 < 1

3 7 7 7 7 5

ð16Þ

ð17Þ



1    T  P QP þ S þ R R  <1 

ð18Þ

i2

The practical limitation for the lifted NOILC lies in the trial length, N. As N grows large, computation of the learning gains LU and LE becomes intractable [25,26]. In this work, we operate with trajectories short enough to stay within the computational constraints. The feedback controller of the R2R system operates at a 5 kHz sampling frequency. For a 10 s experiment the number of sampled data points will be 50,000 on each measurement channel. In reference to (15), this implies an inversion of a square matrix with a size of 100,000  100,000 which is infeasible on most real time computing platforms. In order to lower the computational expense, and create a tractable ILC solution, the measurement signals are downsampled to a 5 ms sample time for the ILC feedforward, thereby reducing the size of P to a manageable 4000  4000. Note, the feedback controllers for both position and tension retain their 0.2 ms sample time. The NOILC algorithm is evaluated on the R2R system subjected to the previously modified stepping position profile with a constant tension regulation. The performance target for positioning error is kek2 < 1:0 mm; there should be less than 1 mm error in web positioning. Within this range the camera system can register the web motion and calibrate the positioning of the E-Jet’s Parker XY stage. Empirical evidence determined that the best tension setting for smooth printing, with minimal web deformation, was approximately 40.0 N + 5.0 N. Therefore, an error of kek2 < 1:0 N was used as a specification for the tension performance. The j = 0 performance is with only LQR feedback while j = 20 is after 20 iterations of NOILC. Results presented in Fig. 13 show that the ILC sig-

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Fig. 11. Sensitivity plots: (a) from reference position to position error, (b) from reference position to tension error, (c) from reference tension to position error, and (d) from reference tension to tension error.

Fig. 12. Serial ILC configuration for the R2R system position and tension control. The error and input signal from the previous iteration are stored on the system’s memory and used to generate ILC input signals to better the regulation and tracking performance of the R2R system.

nal allows the web to track the reference ramps and settle at the intended target position at each step, without any overshoot, before the next stepping motion resumes. The output error presented in Fig. 14 details the improvement on the output tracking error due to the NOILC. The corresponding normalized RMS error plot is presented in Fig. 15 showing that the performance is within the specifications needed for effective printing. Whilst there is significant benefit in the positioning output there is less improvement on the web tension tracking since the constant tension profile reference is relatively simple. The basic feedback LQR already keeps the tension within specification and the tension NOILC could be foregone for this system with little resulting impact to overall printing performance. This is a useful practical result for the benchtop system of Fig. 1 but may not be true for all systems. Therefore, the NOILC is recommended for controller inclusion until it is known whether or not it is critical to system performance. Based on the results of Fig. 14, the NOILC could have been terminated after 5–6 trials, instead of 20, with little penalty in performance improvement.

Fig. 13. NOILC tracking performance on the experimental system. The position tracking performance at the j = 0 iteration (blue line) shows phase lag and overshoot with respect to the reference signal (black dashed line). The position tracking performance is significantly improved at the j = 20 iteration. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

In Fig. 16, we observe a very distinctive reference pattern occurring for each step. This suggests that the NOILC could generate appropriate reference trajectories that can be utilized in a standalone fashion for web stepping. Similar approaches examined the creation of these types of basis functions for recurring motion primitives [27]. The results in Figs. 13–16 utilized encoder-based positioning of the web. In [28,29], a vision-based NOILC approach is utilized to directly position the web within the operating domain of the E-Jet printhead. Apart from the different sensing modalities and the direct positioning of the web, the results are very similar to those of Figs. 13–16 and the interested reader is referred to [28] for details on implementation.

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used to measure the standoff distance with respect to the ground plate at various XY locations. A surface map, assumed planar, is generated by the interferometer as presented in Fig. 17(a). Successive manual adjustment of the tip-tilt stage results in a leveling of the XY stage with respect to the ground plate, and hence substrate, and the final alignment map is Fig. 17(b). Once aligned, the motion of the XY stage will remain parallel with respect to the ground plate. This could be automated if it were required to be performed often. For the system utilized here, adjustment was infrequent and so a manual adjustment was preferred for cost reasons. The E-Jet printing pressure and voltage regulation are programmed inside the cRIO target computer in Fig. 3 along with the XY axis position control. This enables synchronization between the XY positioning and the E-Jet printing. A Matlab based program is written to automatically generate G-Code from bitmap images [15]. The GUI for the G-Code generator is presented in Fig. 18 and the details of the G-Code background algorithm can be found in [30]. Fig. 14. Output error of the regulation and tracking performance at the j = 0 iteration and the j = 20 iteration. The position error signal is significantly reduced after 20 iterations of learning. The tension error is small to begin with so any reductions in tension error are less significant.

Fig. 15. Normalized RMS error of the experimental R2R system. The RMS error value at the j = 20 iteration of the position tracking is reduced to less than 20% of the initial value. The tension regulation performed by the LQ regulator is sufficient, and therefore not much improvement is provided by the NOILC algorithm.

4. Experimental printing results 4.1. E-Jet printing on a flexible and non-conductive substrate Printing onto a 50 lm thick non-conductive substrate, such as Kapton tape, sets the standoff distance between the nozzle and the ground plate to be greater than the 30 lm standoff distance that is more typical for E-Jet printing [7]. At a 30 lm standoff distance between the nozzle and the ground plate, a nominal E-Jet printing voltage is approximately 300 V. In the current setup, the tip of the nozzle is placed approximate 80–100 lm above the ground plate requiring 600 V to generate a sufficient electric field for droplet ejection. Another challenge to printing on a non-conductive substrate is the lack of charge dissipation when the printed droplets impinge upon the substrate surface. The accumulation of charge induces undesirable printing behaviors such as spraying, which may result in a reduction of printing resolution. One way to minimize spraying on the substrate is by switching the polarity of the jetting voltage as developed in [8]. Using the printing voltage profile depicted in Fig. 19(a) and a stage speed of 2 mm/s, continuous lines can be patterned on the Kapton tape. A test case on a stationary substrate is shown in Fig. 17(b) uses a nozzle with a 1 lm inner diameter and a syringe back pressure

3.4. E-Jet printhead control The control of the XY stages in Fig. 2 is relatively straightforward. The servo control is relegated to built-in NI Motion modules that communicate directly with the Parker XY stage. However, a tilt calibration algorithm is necessary to ensure the XY stage moves parallel with respect to the ground plate. In E-Jet printing [7], the nozzle must be placed fairly close (<100 lm) to the voltage ground in order to generate a sufficient electric field. Any slight misalignment could cause the nozzle to impact the substrate while scanning over it. Alternately, too large a standoff distance reduces the strength of the electric field and results in poor printing quality. In several other E-Jet printing systems, the nozzle remains stationary and the substrate is translated by a Cartesian stage. This setup allows for tilt calibration to be done visually using a camera feed. In the R2R system presented here, the nozzle moves via the stage motion and may leave the field of view of the camera. Consequently, tilt calibration using a camera system becomes less practical. To calibrate the tilt of the nozzle, a laser interferometer is

Fig. 16. Modified reference trajectory (red) generated by NOILC. The non-causal nature of NOILC allows the system to preemptively initiate motion on the R2R system. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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Fig. 17. Tip-Tilt calibration setup of the XY stage. A laser interferometer is mounted in place of the nozzle tip to take standoff measurements across the ground plate. (a) Initial topology map of the ground plate prior to adjustment. (b) Resulting topology map after tip tilt adjustment. (c) Calibration setup of the E-Jet printhead.

Fig. 18. Image to G-Code converter program for the R2R system. The program converts any bitmap image into a 2D binary data array. The binary data is used to trigger the E-Jet voltage amplifier to print the intended image.

of 1.5 psi. The lines shown in Fig. 19(b) are 2 lm in width and printed with photo-curable polymer (NOA 61, Norland Products). 4.2. E-Jet printing results on the R2R system Using the image to G-Code converter presented in Fig. 18, arbitrary patterns can be E-Jet printed with the R2R system. Once a

Fig. 19. (a) Pulse width modulation signal used to perform E-Jet printing on the Kapton film. The alternating polarity neutralizes the charge from the previously printed droplet, which reduces electrostatic repulsion between droplets on the substrate. (b) Printed photo-curable polymer (NOA 61, Norland Products) lines on Kapton film.

printing process is completed, the web will step forward, as described in Section 3.3, to allow for printing of the next pattern in the queue. The images in Fig. 20 show patterns that were printed consecutively using the E-Jet printhead on the R2R system.

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connects as 45 X. This give the conductivity of the silver interconnects to be 5  104 S/m. Although this is only 0.25% of bulk silver, it does show feasibility of the direct printing of interconnects onto flexible substrates in a R2R setting. Further work with different materials, printing conditions, and post processing of the printed pattern could be tuned to obtain a higher conductivity. Although out of scope of this article, the wealth of E-Jet printed silver lines available in the literature [31,32] give a good measure of confidence that performance could be improved if desired. 5. Conclusions and future work

Fig. 20. Successive E-Jet printing results on the R2R system with Kapton film as the substrate media. (a) Photo-curable polymer with tagged fluorescent agent. The printed pattern glows under UV light exposure. (b) Conductive organic silver material.

The letter ‘‘I” in the top image of Fig. 20 is printed using NOA 61 that is tagged with a UV sensitive dye material, and the image is shown under UV illumination. The lower image in Fig. 20 is printed using an organic silver ink (IJ – 010, Inktec). The printed patterns presented in Fig. 20 are intentionally magnified for better macroscopic viewing of the printing process results. In order to further investigate the printing functionality, a 2dimensional array of E-Jet printed silver interconnects (IJ – 010, Inktec) are printed onto the Kapton substrate. The microscope image presented in Fig. 21(a) indicates the width of the silver interconnects are approximately 18 lm using a nozzle with a 2 lm inner diameter. After 20 min of sintering at 150 °C most of the ink solvent evaporates, leaving the conductive silver interconnects behind. The three measurements presented in Fig. 21(b) consistently give the resistance of the printed inter-

The E-Jet printing process has shown a wide array of promising opportunities for various industrial applications, including printed electronics and biological sensing applications. However, E-Jet printing has only been performed to date on rigid and conductive substrates such as silicon. The results of this paper demonstrate that E-Jet printing can also be integrated into a R2R manufacturing process so as to print on a continuous, nonconductive, and flexible substrate material. Demonstration patterns printed with conductive or fluorescent inks are presented to indicate the flexibility of this high resolution additive manufacturing technology. A key to the successful integration of E-Jet printing with R2R material transport is the mechatronic combination of design, instrumentation, and controller algorithms. The current design was focused primarily on feasibility demonstration and certain cost constraints were observed in making an effective fabrication tool, akin to the cost effective desktop approach to E-Jet presented in [32]. The primary control benefit was the precise longitudinal placement of the web for printing patterns. This article demonstrated the performance benefits associated with the incorporation of NOILC feedforward techniques to get smooth and precise stepping behavior. Future work will examine the integration of additional elements to the R2R system presented in Fig. 1. These will be additional processing elements, such as a UV curing station, and possibly additional printheads each with unique inks. It will also be important to integrate the E-Jet process on elements existing on the web so as to provide multi-functional or multi-material integration. This will test the overlay registration capabilities afforded by the smooth and precise web transport enabled by the NOILC.

Fig. 21. (a) A 2D Array of E-Jet printed silver interconnects. The width of the silver interconnects is approximately 18 micron, printed using a 2 micron nozzle. (b) Resulting conductivity measurement plot of the silver interconnects. The conductivity of the silver interconnect is 5  104 S/m.

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