Exploring the Benefits of Hybrid Architectures with PLC IoT Sensors and ProSight
- tass peters
- Jan 13
- 4 min read
Industrial automation and smart manufacturing are evolving rapidly. Companies face increasing pressure to improve efficiency, reduce downtime, and gain real-time insights into their operations. One approach gaining traction is the use of hybrid architectures that combine Programmable Logic Controllers (PLCs), Internet of Things (IoT) sensors, and advanced monitoring platforms like ProSight. This blend of technologies offers a practical path to smarter, more connected industrial systems.
This post explores how hybrid architectures work, their advantages, and real-world examples of how they improve industrial processes.
PLC panel integrated with IoT sensors in an industrial environment
What Is a Hybrid Architecture in Industrial Automation?
A hybrid architecture combines traditional control systems with modern IoT devices and cloud-based or edge computing platforms. In this context:
PLCs act as the core controllers managing machinery and processes.
IoT sensors collect detailed data from equipment, environment, and operations.
ProSight is a monitoring and analytics platform that aggregates data, visualizes trends, and supports decision-making.
This setup allows companies to keep the reliability and real-time control of PLCs while gaining the flexibility and data richness of IoT devices and cloud analytics.
How PLCs and IoT Sensors Work Together
PLCs have been the backbone of industrial automation for decades. They execute control logic, handle safety interlocks, and communicate with machines in real time. However, PLCs typically work with limited data points and predefined logic.
IoT sensors complement PLCs by providing additional data streams such as temperature, vibration, humidity, and energy consumption. These sensors often connect wirelessly and can be deployed in hard-to-reach or hazardous areas without extensive wiring.
By integrating IoT sensors with PLCs, operators get a more detailed and holistic view of their systems. For example:
A vibration sensor on a motor can detect early signs of wear before the PLC triggers an alarm.
Temperature sensors can monitor ambient conditions affecting product quality.
Energy meters provide insights into power usage patterns.
This richer data enables predictive maintenance, quality control, and energy management beyond what PLCs alone can offer.
The Role of ProSight in Hybrid Architectures
ProSight acts as the central hub for data collected from PLCs and IoT sensors. It offers:
Real-time dashboards showing machine status and key performance indicators.
Historical data storage for trend analysis and reporting.
Alerts and notifications based on custom thresholds.
Remote access for operators and managers to monitor systems from anywhere.
By consolidating data in ProSight, companies can identify inefficiencies, predict failures, and make informed decisions quickly. ProSight also supports integration with other enterprise systems like ERP or maintenance management software.
Control room screen displaying ProSight analytics and sensor data
Benefits of Using Hybrid Architectures
1. Improved Operational Visibility
Combining PLCs with IoT sensors and ProSight provides a comprehensive picture of operations. Operators can see machine health, production rates, and environmental factors in one place. This visibility helps detect issues early and reduces unplanned downtime.
2. Enhanced Predictive Maintenance
IoT sensors capture subtle changes in equipment behavior that PLCs might miss. ProSight analyzes this data to predict when maintenance is needed, allowing repairs before breakdowns occur. This approach lowers maintenance costs and extends equipment life.
3. Greater Flexibility and Scalability
IoT sensors are easy to add or relocate without rewiring. This flexibility lets companies expand monitoring as needed. ProSight’s cloud or edge deployment options support scaling from small plants to large distributed operations.
4. Data-Driven Decision Making
With detailed data and analytics, managers can optimize production schedules, energy use, and quality control. ProSight’s reporting tools help identify bottlenecks and opportunities for improvement.
5. Cost Efficiency
Hybrid architectures reduce the need for expensive PLC upgrades by supplementing existing systems with IoT sensors. They also lower downtime and maintenance expenses through better monitoring.
Practical Examples of Hybrid Architectures in Action
Manufacturing Plant
A manufacturer integrated IoT vibration and temperature sensors with their existing PLC-controlled assembly line. ProSight collected and analyzed sensor data to detect early signs of motor wear. This allowed maintenance teams to schedule repairs during planned downtime, avoiding costly production halts.
Water Treatment Facility
The facility used PLCs to control pumps and valves, while IoT sensors monitored water quality parameters like pH and turbidity. ProSight provided real-time alerts when water quality deviated from standards, enabling quick corrective actions and regulatory compliance.
Food Processing
IoT humidity and temperature sensors were added to a PLC-controlled refrigeration system. ProSight’s dashboards helped operators maintain optimal storage conditions, reducing spoilage and ensuring food safety.
Steps to Implement a Hybrid Architecture
Assess existing systems to identify integration points for IoT sensors.
Select appropriate IoT sensors based on monitoring needs and environmental conditions.
Deploy ProSight or a similar platform for data aggregation and visualization.
Integrate data flows between PLCs, sensors, and ProSight using standard protocols like MQTT or OPC UA.
Train staff on using dashboards and interpreting data for maintenance and operations.
Continuously review and expand sensor coverage and analytics capabilities.
Challenges to Consider
Data security: Protecting sensitive operational data requires strong cybersecurity measures.
Integration complexity: Connecting legacy PLCs with modern IoT devices can require custom interfaces.
Data overload: Filtering and prioritizing data is essential to avoid overwhelming users.
Cost of deployment: Initial investment in sensors and software should be balanced against expected savings.
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