In the realm of industrial supervision, SCADA (Supervisory Control and Data Acquisition) systems have proven their reliability since the 1960s. These systems collect real-time data and monitor operations. They also enable the analysis and automation of often critical industrial processes.
The IoT (Internet of Things), which emerged in the 2010s, connects devices and sensors to the internet for data collection and exchange. Initially focused on consumer applications like smart home technology, this innovation was quickly adopted by the industrial sector.
The Industrial Internet of Things (IIoT) evolved with the rise of new technologies, such as artificial intelligence and 5G.
This article explores the use cases of SCADA and IIoT systems in industrial supervision. It examines their respective advantages, the criteria for choosing between them, and potential future developments.
SCADA and IIoT: Characteristics
SCADA Systems
In a previous article, we explored in detail the role of SCADA systems in industrial supervision. To summarize, their main functions include data collection, remote control of operations through Human-Machine Interfaces (HMI), and managing alarms and notifications. The subsequent decision-making is usually handled manually by the operator in the control or supervision room.
This approach relies on two key principles:
- A centralized architecture with a control unit (SCADA server) and various programmable controllers (PLCs or RTUs)
- Specific industrial communication protocols (such as Modbus, Profibus, or OPC) on closed and local networks
The initial costs of SCADA systems are often high. It’s essential to plan for operational scalability over a 15 to 20-year period, which is the average lifespan of a SCADA system. Extending these systems can be quite challenging.
IIoT infrastructure
IIoT relies on a multitude of smart sensors and connected devices, allowing for the collection of a massive amount of data.
The functionalities of IIoT are similar in nature to those of SCADA systems. Along with data collection, IIoT also supports remote control, operational automation, and event management.
In addition to these features, IIoT enables predictive maintenance and supports more complex decision-making processes.
This system is based on two key principles:
- A more decentralized architecture, where devices typically communicate with each other through the cloud.
- Modern communication protocols (such as MQTT, AMQP, or CoAP) over more open network infrastructures (like Wi-Fi, Ethernet, or 5G).
The network infrastructure required to implement IIoT can be substantial and may involve high costs. However, the flexibility, scalability, and optimization that come with it offer significant advantages.
Cloud Computing and Edge Computing
Distinction between the two models
IIoT utilizes two data processing systems that differ in infrastructure, architecture, computing power, and reliability.
Cloud Computing enables large-scale data analysis through centralized management of IIoT devices in the cloud. It employs advanced AI models for predictive maintenance, complex decision-making, and process optimization. Additionally, it facilitates access to data from various locations and offers high connectivity.
Edge Computing, on the other hand, processes data locally, close to its source. This approach reduces latency and enhances reliability. By filtering data immediately, it optimizes bandwidth usage. Some critical decisions can be made on-site, ensuring more efficient operational continuity.
A hybrid architecture refers to the operation of IIoT using both models simultaneously, depending on the needs of each industrial supervision process. This hybrid approach allows for rapid responsiveness and high resilience through Edge Computing, while also providing robust analytical power via Cloud Computing.
SCADA systems, in comparison, function similarly to Edge Computing. Increasingly, there is a trend toward migrating SCADA information to the cloud for analytical purposes. However, challenges related to latency and reliability, as well as the complexities of integrating often proprietary systems with the cloud, quickly highlight the limitations of this model.
Edge Computing to address the weaknesses of IIoT
With Edge Computing and its ability to process data close to its sources, the latency of IIoT solutions can be significantly reduced through more localized operations. Additionally, the reliability of the solution is enhanced, and security risks are minimized.
However, the hybrid SCADA/IIoT model is still recommended for extremely sensitive operations for several reasons:
- Some operations require a certified supervision process regarding safety, reliability, or resilience—characteristics that IIoT cannot guarantee due to its operational nature and insufficient maturity level.
- SCADA systems are often deeply integrated into existing industrial processes, and implementing IIoT solutions could incur substantial costs associated with infrastructure changes.
Which solution for which need?
SCADA systems and IIoT can be effectively used together and often complement each other, depending on the industrial environment in which they are deployed.
IIoT, with its massive connectivity, offers excellent flexibility and scalability. Its integration and interoperability with other systems are extremely straightforward, as it typically adopts open standards and publicly accessible protocols. Its cloud-based operation also facilitates remote management for multi-site industries. Through large-scale data management and the use of artificial intelligence (AI) algorithms such as Machine Learning (ML) or expert systems, it ensures predictive maintenance and automated decision-making.
However, IIoT is heavily reliant on connectivity, which can lead to increased latency and makes it more vulnerable to connection interruptions. Additionally, data transmission over more open systems, while adhering to security protocols, still poses a higher cybersecurity risk.
On the other hand, SCADA systems, with their operation in closed local systems and built-in redundancy, exhibit strong robustness and reliability, along with significantly lower cybersecurity risks. They offer major advantages in process management due to their ergonomic Human-Machine Interface (HMI), real-time direct control, and advanced alarm management. SCADA systems also have features that may not be present in IIoT solutions, such as customizable control logic and compatibility with proprietary industrial protocols.
However, SCADA systems are much less flexible and often face greater integration complexity with other systems, particularly when it comes to managing large volumes of data in the cloud.
In practice, a hybrid infrastructure is advisable:
- SCADA systems manage critical tasks, while IIoT collects and analyzes data for predictive maintenance and complex decision-making.
- By combining Edge and Cloud Computing and integrating certain IIoT devices into SCADA systems, the efficiency of industrial supervision installations can be optimized.
Trust Motilde to guide you in optimizing and designing your supervision environments. Don’t hesitate to contact us to learn more. A specialized engineer will get back to you as soon as possible!
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