More Like this

1. Tension Control in Roll-to-Roll Mechanical Peeling for 2D Material Transfer and Transfer Printing

   Zhao, Q. ( December 2021 , 2021 International Conference on Micro- and Nano-devices Enabled by R2R Manufacturing)

   Sreenivasan, S.V. (Ed.)

   A major challenge of the large-scale application of two-dimensional (2D) materials is the scaling up of the process for its growth and transfer. Mechanical peeling has been demonstrated to be a promising method for transferring graphene in a fast and environmentally friendly manner. However, efforts in scaling up the process have been lacking. Performing mechanical peeling using a roll-to-roll (R2R) system could significantly increase the throughput of graphene transfer. Such a R2R process does not exist in industry. In this paper a novel R2R mechanical peeling system that has both speed and tension control capabilities is presented. Controllers that control the peeling tensions on both sides of the peeling front are developed based on a tension dynamics model. Both controllers contain a feedback and a feedforward term to account for large steady-state error. The control performance is validated using both experiments and simulation, demonstrating that the R2R mechanical peeling technique can be a viable method for dry transfer of 2D materials in a high-throughput industrial setting. 

   more » « less
2. Data-Driven Model Predictive Control for Roll-to-Roll Process Register Error

   https://doi.org/10.1115/IAM2022-96840  

   Shah, Karan ; He, Anqi ; Wang, Zifeng ; Du, Xian ; Jin, Xiaoning ( October 2022 , Proceedings of the 2022 International Additive Manufacturing Conference. 2022 International Additive Manufacturing Conference. Lisbon, Portugal.)

   Roll-to-Roll (R2R) printing techniques are promising for high-volume continuous production of substrate-based products, as opposed to sheet-to-sheet (S2S) approach suited for low-volume work. However, meeting the tight alignment tolerance requirements of additive multi-layer printed electronics specified by device resolution that is usually at micrometer scale has become a major challenge in R2R flexible electronics printing, preventing the fabrication technology from being transferred from conventional S2S to high-speed R2R production. Print registration in a R2R process is to align successive print patterns on the flexible substrate and to ensure quality printed devices through effective control of various process variables. Conventional model-based control methods require an accurate web-handling dynamic model and real-time tension measurements to ensure control laws can be faithfully derived. For complex multistage R2R systems, physics-based state-space models are difficult to derive, and real-time tension measurements are not always acquirable. In this paper, we present a novel data-driven model predictive control (DD-MPC) method to minimize the multistage register errors effectively. We show that the DD-MPC can handle multi-input and multi-output systems and obtain the plant model from sensor data via an Eigensystem Realization Algorithm (ERA) and Observer Kalman filter identification (OKID) system identification method. In addition, the proposed control scheme works for systems with partially measurable system states.

    

   more » « less
3. A Dynamic System Model for Roll-to-Roll Dry Transfer of Two-Dimensional Materials and Printed Electronics

   https://doi.org/10.1115/1.4054187  

   Zhao, Qishen ; Hong, Nan ; Chen, Dongmei ; Li, Wei ( July 2022 , Journal of Dynamic Systems, Measurement, and Control)

   Abstract Roll-to-roll (R2R) dry transfer is an important process for manufacturing of large-scale two-dimensional (2D) materials and printed flexible electronics. Existing research has demonstrated the feasibility of dry transfer of 2D materials in a roll-to-roll setting with mechanical peeling. However, the process presents a significant challenge to system control due to the lack of understanding of the mechanical peeling behavior and the complexity of the nonlinear system dynamics. In this study, an R2R peeling process model is developed to understand the dynamic interaction among the peeling process parameters, including adhesion energy, peeling force, angle, and speed. Both simulation and experimental studies are conducted to validate the model. It is shown that the dynamic system model can capture the transient behavior of the R2R mechanical peeling process and be used for the process analysis and control design. 

   more » « less
4. Spatial-Terminal Iterative Learning Control for Registration Error Elimination in High-Precision Roll-to-Roll Printing Systems

   https://doi.org/10.1115/MSEC2023-106259  

   Wang, Zifeng ; Jin, Xiaoning ( June 2023 , American Society of Mechanical Engineers)

   Roll-to-roll (R2R) printing techniques are promising for high-volume continuous production of substrate-based electronic products, as opposed to the sheet-to-sheet approach suited for low-volume work. However, one of the major challenges in R2R flexible electronics printing is achieving tight alignment tolerances, as specified by the device resolution (usually at micrometer level), for multi-layer printed electronics. The alignment of the printed patterns in different layers, known as registration, is critical to product quality. Registration errors are essentially accumulated positional or dimensional deviations caused by un-desired variations in web tensions and web speeds. Conventional registration control methods rely on model-based feedback controllers, such as PID control, to regulate the web tension and the web speed. However, those methods can not guarantee that the registration error always converges to zero due to lagging problems. In this paper, we propose a Spatial-Terminal Iterative Learning Control (STILC) method combined with PID control to enable the registration error to converge to zero iteratively, which achieves unprecedented control in the creation, integration and manipulation of multi-layer microstructures in R2R processes. We simulate the registration error generation and accumulation caused by axis mismatch between roller and motor that commonly exists in R2R systems. We show that the STILC-PID hybrid control method can eliminate the registration error completely after a reasonable number of iterations. We also compare the performances of STILC with a constant-value basis and a cosine-form basis. The results show that the control model with a cosine-form basis provides a faster convergence speed for R2R registration error elimination.

    

   more » « less
5. Spatial-Terminal Iterative Learning Control for Registration Error Elimination in High-Precision Roll-to-Roll Printing Systems

   Zifeng Wang, Xiaoning Jin ( September 2023 , Proceedings of the ASME 2023 18th International Manufacturing Science and Engineering Conference)

   Roll-to-roll (R2R) printing techniques are promising for high-volume continuous production of substrate-based electronic products, as opposed to the sheet-to-sheet approach suited for low-volume work. However, one of the major challenges in R2R flexible electronics printing is achieving tight alignment tolerances, as specified by the device resolution (usually at micrometer level), for multi-layer printed electronics. The alignment of the printed patterns in different layers, known as registration, is critical to product quality. Registration errors are essentially accumulated positional or dimensional deviations caused by un-desired variations in web tensions and web speeds. Conventional registration control methods rely on model-based feedback controllers, such as PID control, to regulate the web tension and the web speed. However, those methods can not guarantee that the registration error always converges to zero due to lagging problems. In this paper, we propose a Spatial-Terminal Iterative Learning Control (STILC) method combined with PID control to enable the registration error to converge to zero iteratively, which achieves unprecedented control in the creation, integration and manipulation of multi-layer microstructures in R2R processes. We simulate the registration error generation and accumulation caused by axis mismatch between roller and motor that commonly exists in R2R systems. We show that the STILC-PID hybrid control method can eliminate the registration error completely after a reasonable number of iterations. We also compare the performances of STILC with a constant-value basis and a cosine-form basis. The results show that the control model with a cosine-form basis provides a faster convergence speed for R2R registration error elimination. 

   more » « less