Textile Pilling Simulator — AionSystem Grant Studio

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The Challenge

Problem

No Integrated Prediction Tool

Textile manufacturers need to reduce pilling without compromising comfort or appearance. No integrated tool exists that relates all parameters across spinning, weaving, dyeing, and finishing. Most solutions address only one phase or one fabric type.

Solution

Data-Driven Pilling Prediction

Pilling Susceptibility Score (PSS) — parametric model built from published textile engineering rules. Relative influence scoring shows which parameters matter most. ISO 12945-2:2000 compliant. Real‑time simulation with trade‑off analysis.

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Four Processing Stages

Fibre

Type · Blend ratio · Length · Denier · Crimp

Yarn

Twist · Hairiness · Spinning method · Count

Construction

Weave type · Warp/weft density · Fabric mass

Finishing

Singeing · Mercerization · Anti-pilling · Resin

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Scoring Engine

PSS = 0.50 × w_fibre × w_yarn × w_construction × w_finishing

Pilling Class = 1 + (1 - PSS) × 4 · Confidence = 1 - Uncertainty Mass

Class 5

PSS ≤ 0.20 · No pilling

Class 4

PSS 0.21–0.40 · Slight

Class 3

PSS 0.41–0.60 · TARGET

Class 2

PSS 0.61–0.80 · Severe

Class 1

PSS ≥ 0.81 · Very severe

What This Proves

Domain AdaptationWorks

The same epistemic scoring architecture that powers CERTUS for crisis response and toxin detection also powers parametric modeling for textile engineering. 16+ parameters. Four processing stages. ISO 12945-2:2000 compliant. The Grant Studio methodology travels across domains without losing fidelity.

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TextilePilling

The Challenge

Four Processing Stages

Scoring Engine

Evidence Package