Cloud Information Processing in Industry
Cloud information processing is becoming increasingly popular in the industry due to the need to improve and maintain high-performance processes. Industrial process engineers often prefer the principle "What happens in Vegas, stays in Vegas" for their systems, meaning that "what happens in the operational department does not leave that department." Technology engineers emphasize that automated systems, modules, controls, and measuring instruments should remain on-site, making their work more reliable and safe. However, today we are witnessing changes in this practice.
Industrial Internet of Things and Industry 4.0
With the drive to enhance efficiency due to the increasing market competitiveness, companies are increasingly using cloud data processing from monitoring and management systems. This allows for data collection from production, performing calculations, and providing all necessary information for those responsible for analysis, suppliers, vendors, and, in some cases, components that return to the factory. This approach can be referred to as the Industrial Internet of Things (IIoT) and Industry 4.0, which has been progressing for some time now.
Security Issues and Implementation Challenges
This new approach to organizing production raises many questions, particularly concerning security. Is it not paradoxical that what we have been doing for a long time is now being done under a different name? As companies go through the trial phase and begin the full-scale implementation of IIoT and Industry 4.0, questions arise regarding the number of languages, devices, and modules that can be controlled through existing tools in the cloud, as well as how much data needs to be processed there. What part of the processed control information should transition to the cloud?
Security and Speed Issues
Some proponents of cloud computing technology argue that the more data that is sent to the cloud, the better. However, this approach does not take into account the realities of industrial control systems (ICS). The security, speed, and reliability of the internet cannot compare to local factory networks, as communication at the object level is critically important. Moreover, the volume of data typically generated by industrial systems can consume a vast amount of cloud resources, which can negatively impact the entire operation.
Data Processing Organization
Among the new trends in cloud data processing, a crucial role is played by edge processing—data processing at the boundary of local networks and the global internet. The end modules of industrial systems are devices that organize data from multiple sources. The concept involves processing data on-site, which helps to save time and resources on filtering, transforming, and aggregating data before it is transmitted for further analysis.
Four Locations for Data Processing
Not everything should be done in the cloud. Most automation engineers believe that data processing should occur where it is most practical. In designing control systems and data processing, the following four locations should be considered for data processing:
- Device: Adding computing power at the device level allows for reducing the volume of data that needs to be sent to the cloud by filtering and transforming data on-site.
- Gateway: Processing data at the gateway is an efficient way to reduce the volume of transmitted data and transform it into a certain architecture that can save resources.
- Cloud: After limiting the data volume and enhancing management methods, cloud resources can be effectively used for data collection, storage, and analysis from various sources.
The latest generation of IIoT cloud services also provides secure bidirectional connectivity, allowing data and analytics to be sent back to authorized users. Cloud service providers can offer data storage at scales that were previously unattainable in local systems, which, in combination with extensive analytics capabilities, can improve operational processes.
Conclusion
The best utilization of the new generation of cloud services for industrial control will depend on how cloud data are managed and how they are obtained from the cloud. Unifying data for protocols will make the data accessible to a larger number of clients and their applications. This approach can positively influence all production processes.