Implementing IoT in an industrial plant is a project that requires coordination between the production team, the IT team, and maintenance managers. This guide provides the complete technical map: from sensor selection to predictive maintenance alert configuration and operational dashboard visualisation.
Phase 1: Identifying Assets to Instrument
Not all assets in a plant justify the investment in IoT monitoring. Priority candidates are equipment with the greatest production impact in case of failure (bottlenecks), those with high corrective maintenance costs, those operating in conditions difficult to access for manual inspection, and those with a history of frequent failures. A criticality analysis (simplified FMEA) helps prioritise instrumentation.
Vibration Sensors
Detect imbalances, worn bearings, and alignment problems in motors, pumps, and compressors. Price: €50–300/unit.
Temperature Sensors
Monitor temperature on surfaces, fluids, and ambient air. Detect overheating before it causes damage. Price: €20–150/unit.
Power Consumption Meters
Monitor the power consumption of each piece of equipment. An anomalous increase in consumption is an early sign of mechanical degradation.
Production Counters
Optical or magnetic sensors that count parts produced, machine cycles, and operating time vs. downtime.
Phase 2: Connectivity Architecture
The connectivity architecture defines how data travels from sensor to cloud. The most common options in industrial environments are: industrial WiFi (for areas with good coverage and fixed equipment), LoRaWAN (for assets distributed across large areas or outdoors, with long battery life), private 5G mesh networks (for low-latency, high-reliability applications), and Ethernet/RS-485 wired connection (for critical equipment where reliability takes priority over flexibility).
65% of industrial IoT projects that fail do so due to plant connectivity problems, not sensor technology. Designing the network layer correctly is the most important decision in the project.
Phase 3: IoT Platform — Where Data Lives and Is Processed
The IoT platform is the system that receives, stores, processes, and visualises sensor data. The three main options for SMEs are: Microsoft Azure IoT Hub (native integration with Power BI for visualisation, budget from €200/month for 100 devices), AWS IoT Core (the most flexible and scalable, with greater configuration complexity), and Siemens MindSphere or Bosch IoT Suite (platforms specialised for industrial environments with native OPC-UA connectors).
Phase 4: Alert Configuration and Predictive Maintenance
Establish Normal Operating Baselines
During the first 4–6 weeks, record normal values for each sensor under different operating conditions. This defines alert thresholds.
Configure Tiered Alerts
Informational alert (value outside normal range), attention alert (concerning trend), critical alert (immediate action required).
Connect Alerts to Work Orders
Integrate the IoT platform with your CMMS (computerised maintenance management system) to create automatic work orders when anomalies are detected.
Implement Predictive Models
With 3–6 months of historical data, it's possible to train models that predict equipment failure 3–7 days in advance.
Indicative Budget for the First Industrial IoT Project
A first IoT project for an industrial SME (10 monitoring points, connectivity gateway, cloud platform with basic dashboard and alerts) has an implementation cost of between €15,000 and €35,000, plus a monthly operational cost of €300–800 (cloud platform + maintenance). ROI, measured in reduced unplanned stoppages and corrective maintenance costs, is typically recovered within 12–18 months.
Want to design your first industrial IoT project with a robust architecture and a clear, measurable ROI? Request a free consultation .