Vision based iterative learning control for a roll to roll micro/nano-manufacturing system

Nano and micro-manufacturing has emerged to be an essential component to progress in many areas of science and has 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. Regardless of the manufacturing technique being employed, the transition from a multistep batch processes to a R2R environment will naturally pose many multidisciplinary challenges. The broad objective of the thesis is to enable a customizable and high resolution device fabrication through printing on a R2R system. A reconfigurable R2R system which serves as a continuous manufacturing platform for various micro/nano-manufacturing processes is built. Here, a particular focus is placed on integrating the Electrohydrodynamic-Jet (E-Jet) printing system to the R2R system environment. Regardless of the micro/nano-manufacturing processes that are employed, the presence of hybrid stepping/scanning motions, both continuous and start/stop motions, should be performed with similar levels of precision. Since the web undergoes a repetitive trajectory, Iterative Learning Control (ILC) can thereby be used to improve the position tracking precision, as well as the web tension regulation. We seek to further improve the position tracking performance by combining ILC with direct visual observation on the pre-existing features on the web. The pre-existing features may serve as fiduciary markers for the vision sensing and, thus, one can accurately place the E-Jet nozzle relative to the feature location on the web. Additionally, the thesis also explores the potential application of E-jet printing on a non-conductive substrate.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Mechanical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Sutanto, Erick

Contributors dc:contributor

• Alleyne, Andrew G.
• Ferreira, Placid M.
• Cunningham, Brian T.
• Salapaka, Srinivasa M.
• Pagilla, Prabhakar R.

• Manufacturing
• Precision Motion Control
• Electrohydrodynamic-Jet Printing
• Roll to Roll
• Machine Vision
• Iterative Learning Control

Statement dc:rights

• Copyright 2014 Erick Sutanto

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/72777

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/72777