Production Efficiency and Performance

Production output was below target, but supervisors could not identify where time was being lost. Relevant machine and MES data sat in separate systems and was difficult to correlate manually.

• Operational data was split across machine logs and MES records.
• Manual analysis across weeks of events was too time-consuming.
• Teams often acted on visible symptoms instead of root constraints.
• Improvement efforts lacked a shared view of the full production flow.

The plant was already collecting the data needed to investigate bottlenecks. Connecting machine, production, and shift information could reveal where the full sequence was constrained.

• Combine data from previously siloed operational systems.
• Correlate downtime and throughput across production stages.
• Distinguish root constraints from downstream symptoms.
• Give operations teams measurable changes to test.

We connected machine logs, MES throughput records, and downtime events in an analytics solution. It identified and ranked specific production constraints with recommendations the team could measure.

• Ingest operational data from across the production line.
• Detect bottlenecks and recurring short stoppages.
• Recommend concrete changes such as reducing changeover time.
• Track outcomes to assess each operational improvement.