Task

The task was to develop a reliable, automated system that monitors the condition of production machinery in real-time, aiming to identify potential issues or malfunctions early. The goal was to drastically reduce unplanned downtime, enhance production efficiency, and enable predictive maintenance.

Challenge

A medium-sized company specializing in metal production regularly faced unplanned downtime and costly production interruptions. Manual inspections proved to be time-consuming, error-prone, and inefficient. The challenge was to implement an innovative, automated solution capable of early detection of risks and enabling preventive actions.

Solution

SALTIR developed a specialized AI-based computer vision solution that continuously visually monitors the condition of production equipment. This intelligent system automatically detects changes in conditions and anomalies using specific models, immediately notifying maintenance personnel. Our holistic approach included not only the technical implementation but also close collaboration with users to ensure optimal integration and acceptance.

Results

The implementation of the system significantly reduced production downtime and unplanned maintenance interventions. This led not only to substantial cost savings but also sustainably improved production capacities and planning reliability. The company now benefits from stable and efficient production processes.