AriLinc · Polymerization AI Platform

Smarter batches.
Better quality.
Faster cycles.

Three AI/ML use cases — purpose-built for polymerization reactors. Know what's happening inside every batch, not just at the end.

2–5%
Yield uplift
80%
Fewer lab samples
−35 min
Per batch cycle
Rs 56Cr+
Annual value
01
Golden Batch
Every batch scored against your best-ever run. Deviations caught in real time.
96.4
→
02
Quality Control
Viscosity, solid content & MW predicted every 5 min — not at batch end.
±1.5%
→
03
Batch Cycle Time
How fast can we safely complete a batch? AI finds the optimum.
−35m
→
🏅 Use Case 01 — Consistency

Golden Batch

AriLinc identifies your best-ever batch for each product and builds a dynamic Golden Recipe — the optimal parameter trajectory for temperature, conversion, agitation and dosing. Every subsequent batch is scored and compared in real time.

Compare Batch
96.4
/ 100
Golden Batch Score
BCH-20260406-201 · Fevicol SH
Recipe Adherence by Parameter
CURRENT BATCH
Temperature Profile — Current vs Golden (°C)
LIVE
Consistency Score — Last 14 Batches
TREND
Parameter Deviation from Golden Recipe
🔬 Use Case 02 — Quality

In-Process Quality Control

Don't wait till the end of an 8–16 hour batch to know if quality is on track. AriLinc's soft sensors predict viscosity, solid content and molecular weight every 5 minutes — giving operators a real correction window while the reaction is still running.

Viscosity Trajectory vs Spec (cP)
LIVE · 5 MIN
Quality Event Feed
0 events
⚡ Use Case 03 — Speed

Batch Cycle Time Optimisation

How fast can we safely complete a batch? AriLinc analyses historical batch data, thermal constraints and quality outcomes to find the tightest possible cycle for each reactor-product combination — without compromising yield or spec.

Cycle Time Saving Per Reactor — Baseline vs AriLinc Optimised
FLEET VIEW
Phase-by-Phase Reduction (min) — Baseline vs Optimised
Baseline Optimised
Avg Cycle Time Trend — Last 16 Batches (min)
TREND
Extra Batches per Month from Saved Time
THROUGHPUT
Business Value · ROI Analysis
Three use cases.
One measurable number.
Indicative for a medium polymerization plant · 50,000 MT/year · Full-scale numbers proportionally higher
🏅
Golden Batch
Rs 18–28 Cr
Annual Yield Value
2–5% batch yield uplift · 35–45% off-spec reduction · shift-to-shift recipe consistency
🔬
Quality Control
Rs 8–14 Cr
Rework Cost Avoided
80% fewer lab samples · early correction window · zero surprise off-spec at batch end
⚡
Cycle Time
Rs 6–12 Cr
Throughput Revenue
−35 min avg per batch · +12% throughput · same assets, more output per year
Value Driver Use Case Per Month Per Year Confidence
Monthly Yield (%) — Baseline vs AriLinc
OCT → APR
Off-Spec Batch Rate (%)
IMPROVING
Monthly Chemical Saving (Rs L)
Rs 32–54 Cr
Combined Annual Value (3 use cases)
6–10 Months
Investment Payback Period
Rs 1–2 Cr
Phase 1 Implementation Cost
10–15×
5-Year ROI on AI Investment