Cloud-based predictive maintenance and anomaly detection in textile production

A cloud-based predictive maintenance solution for textile manufacturing, designed to reduce downtime and increase operational efficiency.

Machine data from the factory was continuously collected in near real-time, enabling the early detection of anomalies in complex mechanical systems.

By analyzing deviations in performance, the system was able to quickly and precisely locate emerging defects.

The platform also supported the dynamic adaptation of data collection to new shift patterns, thus enabling more accurate financial reporting.

Furthermore, it facilitated the quantification of daily yarn production, thereby supporting a production-based pricing model.