Challenge
Recurring line stoppages, changeover delays, dispatch misses, and late replenishment were making output continuity too dependent on manual judgment. Material timing and line-setting discipline were also drifting too often.
CETA role
CETA introduced AI-supported planning logic, clearer sequencing rules, live thresholds, escalation pathways, and dashboard visibility for supervisors and managers. The goal was to convert repeat manual decisions into a faster and more disciplined system layer.
Impact
The site improved efficiency by roughly 38%, reduced labor dependency, and gained cleaner coordination across lines with faster response to disruption.
Operating context
This site did not have an intelligence problem in the abstract. It had a coordination problem at the point where planning, materials, line readiness, and supervisor intervention met one another. Too many decisions still depended on individual judgment under pressure.
What changed
CETA focused on the repeatable parts of the work first: sequencing, replenishment timing, escalation thresholds, and visibility. By moving those decisions into a clearer operating layer, supervisors spent less time reacting line by line and more time managing the plant with cleaner context.
Why the result mattered
The gain was not only in efficiency percentage. The plant became more stable under pressure. A better decision layer reduced preventable interruption, tightened response timing, and made output continuity easier to defend across multiple active lines.
Proof basis
- Production and interruption observations from the active multi-line environment
- Pre- and post-intervention efficiency comparison
- Supervisor and operations review of replenishment and exception timing