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REVIEW ARTICLE

Intelligent process control and stimulus-responsive 4D transformation in extrusion-based 3D food printing: A critical review

Sangjun Jeon1† ,  Ara Go2† ,  Donghui Kim1,3 ,  Seung Ki Moon1,3* ,  Seong Je Park4*
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1 School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
2 Department of Future Convergence Engineering, Kongju National University, Cheonan, Republic of Korea
3 Singapore Centre for 3D Printing, School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
4 School of Mechanical Engineering, Gyeongsang National University, Jinju, Gyeongsang, Republic of Korea
†These authors contributed equally to this work.
IJB, 026200182 https://doi.org/10.36922/IJB026200182
Received: 12 May 2026 | Revised: 9 June 2026 | Accepted: 16 June 2026 | Published online: 16 June 2026
(This article belongs to the Special Issue 3D Food Printing: Materials, Processes and Applications)
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Three-dimensional food printing (3DFP) presents unparalleled opportunities for personalised nutrition, clinical dysphagia management, decentralised on-demand production, and space-mission food provision. However, industrial translation remains constrained by inconsistent rheological characterisation, limited cross-material generalisation of process-control models, and the absence of integrated quality-control frameworks for post-processed and stimulus-responsive constructs. Although extrusion-based 3DFP offers the broadest substrate compatibility among additive manufacturing routes, prior reviews have treated ink formulation, process control, post-processing, and four-dimensional (4D) transformation as separate domains. In this work, extrusion-based 3DFP is reviewed in an integrated manner. Rheological foundations and substrate-specific ink design are examined across hydrocolloid, protein, starch, fruit/vegetable, dairy, meat, and bioactive-loaded systems. Intelligent process control is then discussed through three integrated axes: computational fluid dynamics modelling, data-driven low-field nuclear magnetic resonance with machine-learning prediction, and real-time computer-vision feedback. Pre- and post-processing engineering is examined alongside an integrated quality-control framework, and recent stimulus-responsive 4D studies are organised by trigger and response. Synergistic integration of these domains demonstrates clinical and personalised-nutrition potential beyond that of any single-domain approach. This article systematically reviews the ink design, intelligent process control, post-processing engineering, and stimulus-responsive 4D transformation of extrusion-based 3DFP, aiming to provide valuable insights for the development of intelligent food-printing systems.

Graphical abstract
Keywords
3D food printing
Material extrusion
Intelligent process control
4D stimulus-responsive transformation
Machine learning
Funding
This review was supported by the “Gyeongsangnam-do Regional Innovation System & Education (RISE)” Project, funded by the Ministry of Education and Gyeongsangnam-do. (No. 1-1-1-1-7-9).
Conflict of interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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International Journal of Bioprinting, Electronic ISSN: 2424-8002 Print ISSN: 2424-7723, Published by AccScience Publishing
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