Textile Industry Applications

Leveraging advanced AI technology to predict moisture content in setting machines effectively reduces quality issues caused by unstable moisture levels.

This technology is not only applicable to moisture content control, but also addresses other critical quality indicators such as heat shrinkage rates, ensuring stability and quality consistency throughout the production process.

Our solution leverages AI technology to precisely predict fabric hand feel. It optimizes various parameters based on production needs and recommends the most energy-efficient production settings to ensure consistency and quality in fabric hand feel.

This prediction technology is applicable to a variety of textile machines, including setting machines, padding machines, and dyeing machines. It helps businesses reduce energy consumption, achieve carbon reduction and energy-saving goals, and enhance production flexibility and efficiency.

Leveraging AI technology for predicting dyeing lab color shifts and analyzing their root causes, our solution identifies key factors affecting color deviation based on extensive data and provides support for decision-making.

This predictive and analytical approach enhances color matching accuracy and stability, effectively improves yield, and ensures consistency and high-quality performance throughout the dyeing process.

Our solution recommends optimal production parameter combinations with low rework rates, providing decision-makers with actionable insights.

This approach not only increases output but also saves water and energy, and reduces waste. It supports energy efficiency and carbon reduction goals, fostering sustainable, green production practices.