OEE monitoring
Unite availability, performance and quality.
OEE monitoring shows in real time how effectively manufacturing lines are used, making disruptions, slow running and quality losses immediately visible.
- Higher efficiency
- More transparency
- Faster processes
OEE
downtime
payback
response speed
Calculated from additional output through higher OEE and lower downtime costs.
- 01
Data integration
Consolidate data from ERP, MES and further sources for OEE monitoring.
- 02
Data quality
Clean, harmonise and validate data for plausibility.
- 03
Model development
Train and validate the OEE monitoring model on historical data.
- 04
Pilot
Pilot OEE monitoring in one area and collect feedback.
- 05
Rollout
Scale the solution and integrate it into operational processes.
Steps
Data sources
Stakeholders
From first data access to production – every step delivers a tangible interim result.
MES data
Production orders, feedback and machine data.
Machine data
Condition, parameters and production counters.
Quality data
Inspection results, lab values and complaints.
Order data
Customer orders, line items and dates.
HR data
Shift plans, qualifications and absences.
Maintenance data
Faults, maintenance and spare-parts consumption.
Production manager
Uses insights directly in daily operations.
Maintenance
Plans maintenance and spare parts precisely.
Quality management
Secures compliance with standards and regulations.
Controlling
Quantifies effects and supports budgeting.
Higher efficiency
More transparency
Faster processes
Better planning
Higher availability
With a solid data foundation this use case gets faster, cheaper and far more stable.
Central data platform
Real-time data integration
Scalable analytics pipelines
Reusable data products
OEE monitoring
Availability data complements process metrics.
Predictive maintenance
Sensor data provides wear indicators.
Predictive quality
Same data reveals quality deviations.