Reducing unplanned downtime in an auto-components MSME

Problem

A machining line was losing production hours because stoppages were tracked informally and root causes were not visible across shifts.

Context

The MSME needed a low-cost way to structure downtime evidence before selecting sensors, automation, or process changes.

Solution approach

NumSum would structure the problem, capture onboarding questions, run a challenge for practical diagnostics, and evaluate a simple downtime classification workflow before recommending tools.

Impact

Expected impact includes fewer repeat stoppages, better shift handover, and a measurable downtime-reduction baseline for future pilots.

Lessons learned

• Start with problem evidence before buying tools.
• Shift-level categories make root-cause discussion easier.
• Impact metrics should be approved before public publication.