How AI reduces unplanned downtime in manufacturing
June 28, 2026 · 6 min read · KobiKan team · Touch4IT
In automotive, the cost of an unplanned outage is measured in thousands of euros per minute. Most of those outages were solved before — nobody on the night shift just knows about it.
Where most time is lost
ARC and Plant Engineering studies repeatedly show that 30–50% of unplanned-outage time is spent searching — for a manual, a schematic, a contact person, a previous repair record.
An AI assistant doesn't cut that time by a few minutes. It cuts it by orders of magnitude — from tens of minutes to seconds — because the answer comes to the technician right at the machine, with the source attached.
Recurring failures: the biggest hidden cost
Up to 70% of failures stem from human error during a previous repair or from missing context. AI links machine data with repair records and flags when a scenario is about to repeat.
Example: if a specific sensor failed three times in the past six months, always preceded by a pressure drop in the loop, the system predicts the next failure before it happens.
What to measure during the pilot
MTTR for the top 10 most common failures. Track the trend for the first three months.
Number of recurring failures on the same machine — it should drop because technicians have access to previous solutions.
After-hours escalations. If they fall, your night shift effectively has a "24/7 senior" in hand.