Data Collection

Productivity losses often go unnoticed because they are not measured. We collect data from PLCs, robot controllers, cameras and sensors over PLC protocols, TCP/IP and UDP, store it in a database with timestamps, and make production counts, OK/NOK rates, downtime reasons and defect distributions visible on live screens.

This foundation is already part of the stations we build: quality inspection screens keep OK/NOK counts and reports per shift, measurement stations keep trend charts, and palletizing lines keep production counts per robot and product type.

The data is used for decisions, not only for reports: quality data feeds deep learning models, and downtime data shapes the maintenance plan.