Getting Started with OEE and Production Data Collection
A production data collection project should help teams make faster decisions from shared data. Adding more charts is not enough. A successful start establishes business questions, data ownership and validation methods before connecting machines.
Key takeaways
- ✓Start with the decision: where is the loss, what causes it, and who needs to act?
- ✓Combine automatic machine signals with operator, work order, product and quality context.
- ✓Read OEE through its availability, performance and quality components rather than treating the total as a standalone target.
- ✓Prove data accuracy on a pilot machine before expanding to a line or factory.
Which data should you collect?
Collecting every signal increases cost and complexity. Select a minimum dataset based on the business problem being addressed. A running or stopped signal alone is insufficient for downtime analysis: you also need to distinguish planned from unplanned stops and record reason codes.
- Machine status, cycle times and production counts
- Work order, product, operation and shift
- Downtime start and finish times and reason codes
- Good units, scrap and rework records
- Context such as operator, tooling or fixture, and recipe information where required
What does OEE tell you, and what does it leave out?
OEE is a manufacturing measure combining availability, performance and quality. The total is only a starting point. Its components show whether losses come from downtime, slower cycles or quality problems.
Comparing different machines, products or sites using one number can be misleading. Make sure planned time, ideal cycle time and quality are defined and calculated consistently.
Machine connectivity options
Production network security matters alongside protocol selection. The data collection component should access only the signals it needs, and traffic between office and production networks should be controlled.
- Direct reading through a PLC or controller protocol
- OPC UA, Modbus TCP, MQTT or a vendor API
- Additional data collection through digital signals, sensors or counters
- Operator terminals and barcode entry for processes without connectivity
Responsibilities across ERP, MES and the shop floor
ERP is generally the system for orders, inventory and financial records, while MES manages work order execution and manufacturing events on the shop floor. The data collection layer captures the machine event. Before integration begins, define which system is the authoritative record for each field.
- The source of work order and product information
- The destination for actual production counts, scrap and downtime
- Local buffering and retransmission when connectivity is lost
- Code mapping, time synchronisation and an error queue
Acceptance criteria for a pilot project
A pilot succeeds when more than the screen works. Data accuracy, user adoption, network security and the support process should be included in the acceptance record.
- The difference between automatic counts and verified physical or operational records
- Verification of downtime start and finish times against sample events
- The operator's ability to complete reason code entry
- The ability to continue through a connection outage without losing data
- Approval of shift and work order reports by the production supervisor
Related guides
Sources
This guide provides general information. Define implementation requirements around your business risks and infrastructure.