Keeping Industrial Networks Healthy.
Case Study: PROCENTEC
At a Glance:
Industry:
Industrial Automation / Industrial Networking
Use Case:
Al-powered diagnostics and continuous monitoring for PROFIBUS and PROFINET industrial networks to reduce downtime and enable proactive maintenance.
Technologies Used:
- Machine Learning
- Neural Network Analysis
- Feature Extraction
Impact:
2-Minute Diagnostics, speeding up problem detection from hours to minutes
24/7 health checks at a fraction of technicians’ cost
Monitoring 176 PROFIBUS and 33 PROFINET networks across 42 locations
worldwideRevolutionized network monitoring with Al technology
- Prevented costly network downtime
The Challenge
Manufacturers running PROFIBUS and PROFINET systems face mounting pressure to maintain high uptime. Yet, diagnosing network issues often depends on a few skilled technicians manually interpreting complex oscilloscope data-limiting insights to their availability and increasing operational costs. PROCENTEC saw an opportunity to shift this paradigm by rethinking how industrial networks could be monitored, diagnosed, and maintained.
Our Approach
To modernize industrial network maintenance, Procentec partnered with Spur Insights to develop SNAP (Synthetic Neurologic Analytic Processor)-an Al-powered solution that reimagines how faults in PROFIBUS and PROFINET systems are identified and addressed. Instead of relying on manual diagnostics, SNAP continuously analyzes low-level electrical signals, traffic patterns, and error logs to detect emerging issues. These insights are presented in intuitive visual formats, empowering operators to take fast, informed action.
What we uncovered
Simplifying Complex Signal Analysis
PROFIBUS Systems
Traditionally, troubleshooting PROFIBUS networks required deep expertise to interpret oscilloscope traces captured by Procentec’s ComBricks hardware. With SNAP, this data is analyzed by Spur’s Al algorithms, which detect, locate, and classify errors automatically. The result: network diagnostics that once depended on expert technicians are now accessible through clear visuals and step-by-step guidance.
Uncovering Hidden Faults in Real Time
PROFINET Systems
For PROFINET environments, the ATLAS device captures traffic and error messages across the network. SNAP processes this raw data through the same intelligent framework, uncovering issues like intermittent faults and hardware degradation that often go unnoticed until failure. These real-time diagnostics allow teams to intervene early-before problems disrupt production.
The Results
Accelerated Diagnostics: Diagnostic time reduced to under 2 minutes, compared to hours with traditional methods.
Continuous Monitoring: 24/7 network health monitoring at a fraction of the cost of a full-time technician.
Cost-Efficient Solution: Prevents costly network outages, contributing to Procentec’s digitization and automation initiative.
Rapid Market Adoption: Six months post-launch, SNAP is used by major clients, including a global e-commerce platform, across 42 global locations, managing 176 PROFIBUS and 33 PROFINET networks worldwide.
“Working with a flexible, highly educated and motivated team allowed us to create a completely new business model from a scratch.”
— Matthew Dulcey, Chief Technology Officer at PROCENTEC
What’s Next?
Procentec plans to continue expanding SNAP’s deployment, further integrating it into diverse industrial environments to cover even more networks globally, ensuring that real-time diagnostics become the standard.