- Info@counton.ai
Manual fabric inspection is slow and prone to human error.
Variations in yarn tension and elastane slippage cause defects.
Tracking Overall Equipment Effectiveness (OEE) across multiple machines is difficult.
AI‑Powered real-time Defect Detection: Deep‑learning models identify yarn density variations, needle lines, holes, oil stains and elastane issues in real time.
Automated Control: If defects are detected, necessary steps are taken automatically by Knit-I
Management Dashboard: To get the key insights to run textile factory error-free with much higher productivity
Real‑time inspection eliminates fabric defects and reduces rework.
Operators focus on high‑value tasks; labour requirements drop by more than 90 %.
Predictive maintenance cuts unplanned stoppages by up to 50 %.
OEE reports help managers schedule maintenance, optimise machine settings and improve yield.
Maintain uniform texture and color across production batches with intelligent monitoring.
Instantly detect anomalies and notify operators to prevent defective fabric from progressing further.
Streamline production workflows by analyzing machine and material performance data.
Minimize resource usage and downtime, leading to lower operating expenses and higher profitability.
Adapt our AI systems to meet the needs of small units or large-scale textile plants.
Support your workforce with AI tools that guide and improve daily tasks without adding complexity.
Generate comprehensive reports that track performance trends and highlight areas for improvement.
Ensure manufacturing standards are met and maintain complete traceability for audits and certifications.
A leading knitwear manufacturer deployed CountOnAI’s Knit‑i Insight across 40 knitting machines. Within three months, defect rates fell by 35 % and first‑pass yield increased by 30 %, allowing the company to meet international quality standards and reduce waste.”
