Recent Advances in AI-Driven Inkjet Printing

Seongju Kim^*

¹Hanbat National University, Daejeon 34158, Korea.

^*Corresponding Author: Seongju Kim, Phone: +82 042-828-8804. E-mail: seongju@hanbat.ac.kr.

© Copyright 2026 Korea Flexible & Printed Electronics Society. This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received: May 16, 2026; Revised: Jun 09, 2026; Accepted: Jun 12, 2026

Published Online: Jun 24, 2026

Abstract

The inkjet printing process requires an understanding of the physical behavior that governs droplet generation, deposition, and film formation. Artificial intelligence (AI) is becoming a key technology for the inkjet printing technologies by extracting meaningful patterns in relationships between complicated features. This review summarizes recent AI based methodologies for jetting behavior prediction, abnormal jetting detection, waveform optimization, process monitoring, and film formation control. The remaining challenges and future opportunities are discussed toward intelligent inkjet printing systems for display manufacturing and electrical applications.

Keywords: Inkjet printing; Machine learning; Optimization; Smart manufacturing