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Cleaner-production performance of digital textile printing and the pre-press cost of AI-generated designs: a field investigation at three Indian commercial facilities

Year: 2026

Type: article

Abstract: Digital textile printing is a cleaner alternative to rotary-screen printing (RSP), but the operational effects of coupling it with AI-generated design are underexamined in commercial practice. This study combines the published Creditex production comparison with field data from three Indian facilities visited in March 2026: R1, a hybrid rotary-screen and reactive-inkjet plant printing cotton and blends; R2, a disperse-sublimation polyester specialist in Surat; and R3, a digital-only reactive-inkjet enterprise printing cotton. In the Creditex like-for-like comparison on reactive cotton, digital printing used 36% less water, 35% less electricity and 28% fewer chemicals than RSP. At R1, the only facility running both processes, the digital line used 2.9 L/m of water against 12-16 L/m on the screen line (facility-reported). Digital water use ranged from 0.175 L/m for sublimation on polyester to 2.9-3.5 L/m for reactive inkjet on cotton, showing that ink chemistry, not printing technology alone, governs water intensity. In one paired print test per facility, AI-generated motifs, once passed through standard pre-press, differed little from CAD designs in reported colour accuracy (mean ΔE 00 1.77 vs 1.75), first-pass yield (94.8% vs 95.3%) and wash fastness (grade 4-5), descriptively and without replicates. However, 68-82% of AI files needed resolution upscaling and 48-60% seamless-repeat correction, adding about 53 min of pre-press work per incoming AI file (37-74 min by facility) against 15-20 min for CAD files. In this exploratory, facility-reported study, the environmental gains therefore appear to come from the digital-versus-screen transition and ink chemistry rather than from AI; AI’s contribution is workflow agility, offset by a measurable pre-press cost. A four-stage framework operationalises AI-generated designs at production scale within the intelligent-manufacturing and Industry 6.0 agenda.

Source: Cleaner Engineering and Technology

DOI: 10.1016/j.clet.2026.101356

Authors: Tripti Singh, Durgesh Singh, Abhishek

Institution: Indian Institute of Information Technology Design and Manufacturing Jabalpur

Language: English

Topic: Dyeing and Modifying Textile Fibers

Subfield: Polymers and Plastics

Field: Materials Science

Domain: Physical Sciences

SDGs: Responsible consumption and production, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,220