Challenge
A manufacturing facility operated with legacy systems and disconnected data sources. Quality control reports were slow, shift logs were inconsistent, and equipment readings were not centralized—leading to late issue detection and inefficient downstream processes.
Our Approach
We built an automation layer that unifies machines, QA workflows, and reporting in one place.
Discovery phase
Mapping the factory's quality checkpoints
- Mapped all quality inspection checkpoints end to end
- Designed central data flows connecting machinery, QA forms, and reporting tools
- Created structured alerting rules for anomalies and thresholds
Development & Stack
Connecting OT data to modern workflows
- Connected machines via MQTT and SAP using n8n middle-layer automation
- Built workflows that record equipment metrics, validate them, and send reports to supervisors
- Automated shift handover logs to standardize daily summaries
AI & Automation Intelligence
Surfacing early signals for QA teams
- Added anomaly detection for temperature and pressure spikes
- Implemented automated classification of QA failures using AI
- Set up predictive alerts for recurring equipment issues
Solution
A robust automation system now collects metrics, logs issues, notifies teams, and orchestrates reporting—all powered by n8n. Supervisors see live equipment health, QA results, and shift updates without manual aggregation.
Key capabilities delivered:
- Equipment monitoring and alerts with consistent thresholds
- Automated QA workflows that capture, validate, and route findings
- Real-time supervisor dashboards for production visibility
- Predictive issue detection to prevent downtime
Why It Matters
This project shows how n8n can connect industrial systems, modernizing manufacturing operations without expensive custom solutions. It reflects Excality’s ability to merge automation, IoT, and AI-driven insights into practical, enterprise-ready workflows.