About the Client
PrecisionMFG is a German industrial manufacturer operating 14 plants across Europe, producing precision components for automotive and aerospace industries.
The Challenge
Software deployments to factory floor systems took weeks, causing delays in rolling out critical updates. Unplanned downtime cost €200K per incident.
The Solution
We implemented a full DevOps pipeline for their factory systems — CI/CD for edge devices, infrastructure-as-code for factory servers, and a predictive maintenance AI that reduced downtime by 28%.
Key Features
Edge CI/CD
Automated deployments to 500+ factory floor devices
Deployments from weeks to hours
Predictive Maintenance
AI analyzing sensor data to predict equipment failures
28% less unplanned downtime
Infrastructure as Code
Terraform-managed factory server infrastructure
Consistent environments across 14 plants
Monitoring & Alerting
Real-time health dashboards for all plant systems
15-minute mean time to detection
The Results
28% less downtime. Deployments from weeks to hours. Saved €2.8M in first year.
28%
Less downtime
€2.8M
Annual savings
500+
Devices managed
15min
Mean time to detect
Our Process
Assessment
3 weeksCurrent state audit, deployment workflow analysis
Pipeline Design
3 weeksCI/CD architecture, edge deployment strategy
Implementation
10 weeksPipeline setup, IaC migration, monitoring deployment
Training
2 weeksTeam enablement, runbook creation, handoff
"CiroStack modernized our factory operations. The predictive maintenance AI alone saved us €2.8M in the first year."
Hans Müller
Head of Ops, PrecisionMFG
What the Client Loved
- Deployments that used to take 2 weeks now happen in 2 hours
- Predictive maintenance caught a critical pump failure before it happened
- The monitoring dashboards are used by management daily
Challenges We Overcame
- Deploying to air-gapped factory networks — built an offline artifact sync system
- Managing diverse device types across 14 plants — device abstraction layer
Technology Stack
DevOps
Monitoring
Edge
AI/ML
