Implementing OPC UA for industrial IoT data unification
We explore how the OPC UA standard and ISA/IEC 62443 architecture help build a reliable bridge between OT and IT for predictive analytics without security risks.
INSIGHTS & PRACTICE
Circular economy and digital practice.
Circular economy, repair, reuse and traceability, supported by our archive of practical guides to digital processes, documents and monitoring.
149 publications
The future of industrial IoT: Driving autonomy with Physical AI
Integrating Physical AI into industrial environments requires moving from simple telemetry collection to resilient hybrid architectures, where data normalization and OT security are primary priorities.
Taking IIoT to scale: Transitioning from local pilots to full production
A practical guide to scaling the Industrial Internet of Things: edge vs. cloud architecture, secure legacy equipment integration, and OT network protection.
Securing legacy integration with digital twins for critical infrastructure
Architecture for integrating legacy equipment with digital twins in industrial sectors. How to extract telemetry while prioritizing OT system availability.
Building robust data pipelines for predictive maintenance in IIoT
Data architecture for Predictive Maintenance: how to standardize data flow via OPC UA and distribute computation between Edge and Cloud without replacing SCADA.
Striking the right balance between edge and cloud in IoT systems
Effective industrial IoT architecture requires load distribution: processing critical data on-site (Edge) or sending it to the cloud for deep analytics.
Balancing IT and OT convergence through SCADA and IoT integration
How to combine the flexibility of cloud-based IoT analytics with the strict availability requirements of SCADA systems without risking the shutdown of critical industrial processes.
Unifying industrial data securely: A hybrid IIoT protocol architecture
Integrating Modbus, MQTT, and OPC UA via edge gateways allows legacy equipment to be combined with modern analytical platforms, preserving data context and security.
Building an Industrial IoT architecture: From sensors to dashboards
How to integrate legacy equipment with the cloud, ensure OT network security, and build a robust architecture for industrial data collection and processing.
The future of BPM: Deploying AI agents for first-line workflow processing
How to combine the flexibility of AI with the rigid logic of BPMN 2.0 and DMN to automate first-line request processing without security risks or operational chaos.
Common automation pitfalls: Navigating chaos, RPA, and AI risks
How to avoid cementing inefficiencies, replace fragile RPA scenarios with reliable API integrations, and safely implement AI into operational workflows using BPMN and DMN standards.
From process discovery and pilots to continuous improvement: Managing automation projects
Why traditional process maps doom IT projects to failure and how to build effective automation based on real logs, BPMN 2.0, and DMN decision tables.