Automotive Intelligence Platform

Industry challenge

Automotive manufacturing operates on tight production schedules and just-in-time supply commitments that leave no buffer for undetected machine issues. A single machine failure on a critical line can halt downstream operations within minutes, delay component delivery to assembly, and generate quality escapes that only surface later in the build sequence. Supervisors often learn about stoppages by walking the line or receiving a phone call — not through a structured system that gives them immediate, actionable context. Downtime records are kept per-machine without aggregation across the line, making it impossible to see whether a pattern of brief stoppages on multiple assets is trending toward a systemic failure. Quality rejections are logged separately from production counts, and the connection between a specific machine event and a downstream quality issue is rarely traceable. For multi-shift and multi-line operations, consistent performance data across shifts is essential for credible production planning and supplier commitment — but without a structured monitoring system, that consistency is impossible to achieve.

How Factobrain applies

Factobrain delivers real-time visibility across every machine on every line — streaming live state data organized by production hierarchy so supervisors and plant managers can see exactly what is running, what has stopped, and what the current shift output looks like against the target. Role-aware alerts notify the right person the moment a machine transitions to STOP, with structured escalation logic that routes events to the appropriate level when the initial response does not resolve the issue within a defined window. Downtime events are captured automatically with full context — machine, line, shift, operator, job, and batch — and reason codes are assigned immediately, creating a structured record that supports both real-time response and post-shift analysis. Quality rejections are logged against the specific job and batch in progress, with rejection type codes that link quality outcomes to the machine events that preceded them. Cross-shift and cross-line dashboards give plant leadership a consolidated view of production performance without requiring manual report compilation from shift supervisors.