Manufacturing · A multi-site industrial manufacturer, high-speed packaging lines

Self-Healing Data Operations

The line calls for help before it stops

“A line goes down and I hear about it from a phone call, four hours later.”

Context

Where it started

Unplanned stoppages ran 15 to 20 percent of scheduled time. Faults were diagnosed after the event, so parts arrived once the line had gone cold.

Action

What our team built

Our team wired vibration, temperature, pressure and current from 40 to 50 sensors per line into survival models that score every asset daily and call a likely failure 10 to 20 days ahead. The agent raises the work order, reserves the part and proposes a reroute. A planner releases it.

Results

What changed

80%+

failure prediction accuracy

Around 50%

less unplanned downtime

2 sites

running in production

The agent writes into the maintenance system. A prediction that only lights up a dashboard changes nothing.

Where does your AI programme actually stand?

Ten minutes, scored across the dimensions that decide whether pilots ship. You get the score and the gap map immediately.

Related work

More from the pipeline