SECS/GEM equipment integration
Our in-house SECS/GEM driver receives equipment status, events, alarms and process data in real time.
Industries
From equipment linksto full automation
Connect SECS/GEM equipment, process conditions, and LOT and material history with software we develop ourselves. Equipment data feeds directly into MES production records and quality analysis.
Process flow
Process flow
Material input
Material LOT verificationEquipment process
SECS/GEM data collectionProcess conditions
Recipe downloadInspection
Measurement and judgment recordsPackaging and shipping
LOT history done
Product lineup
Wavegram configuration
Process condition and recipe management
Manage process conditions centrally by item and download them to equipment, with change history retained.
LOT and material history
Combine input material LOTs, equipment, process conditions and inspection results into one traceable history.
Predictive maintenance
AI learns equipment vibration, current and temperature patterns to warn of early signs of failure.
Industry studies
Results from industry studies
Results achieved by companies adopting smart factories, MES and AI
Companies focused on predictive and preventive maintenance
- Unplanned downtime
- −52.7%
- Defects
- −78.5%
US National Institute of Standards and Technology (NIST), Manufacturing Equipment Maintenance Survey (2021)
MES adoption
- Data entry time
- −75%+
- Manufacturing cycle time
- −45%
- Paperwork between shifts
- −61%
- Lead time
- −27%
MESA International user survey (1997, averages)
FAQ
FAQ
Do you develop SECS/GEM integration in-house?
Yes. Wavegram connects equipment using its own SECS/GEM driver and adapts it together with you to each machine’s scenarios.
Can PLC-controlled equipment connect too?
Yes. Connect PLC, Modbus, OPC UA, MQTT and other LINKER-supported communications alongside SECS/GEM equipment in one system.
Can recipes be downloaded to equipment?
Manage process conditions centrally by item and download the relevant recipe to equipment when the item changes.
What data is used for predictive maintenance?
Learn normal patterns from vibration, current and temperature sensors, and alert maintenance staff to signs of deviation.