Digitalization brings valuable new functions that make use of the data that probably already existed on the production line but was stranded in disparate systems.
There is certainly a buzz around the idea of digitalization—for its ability to deliver the benefits offered by greater visualization and analysis of data and to gain a greater understanding of the root causes of unexpected downtime and production bottlenecks. But what are the options, and how can they best be employed?
One benefit of digitalization—in addition to offering greater connectivity of devices at plant level—is its potential to escalate data to other systems and to make it possible to monitor plants remotely, in more depth, and over wider distances and longer periods than has been possible in the past.
Manufacturing traceability, for example, would traditionally have been achieved via paper-based batch recording, while product-level traceability would not have been achievable without digital technology. Predictive maintenance could be achieved but only via periodic monitoring of devices.
So digitalization brings with it a host of valuable new functions that make use of the data that probably already existed on the production line but was stranded in disparate systems.
At its most simplistic, digitalization is about integrating devices to gain information about them that helps rectify problems. However, the potential goes much further, and the benefits of digitizing will be widespread, right across an enterprise. Visualization, for example, can give greater insight into how productive and efficient the entire manufacturing plant is.
The biggest barrier to adopting digital technology revolves around the fact that operational technology (OT) was traditionally designed around the need for machine optimization, employing architectures and networks that provide optimal performance for machines. However, because any digitalization project’s success relies on the IT and OT worlds merging, OT technology has had to evolve to be better able to integrate with the wider world. Today’s modern machine-control solutions incorporate IT functionality, including direct SQL database connectivity, and can also be provided with OPC-UA, as well as MQTT, all providing solutions to achieve a simple and seamless method of escalating operational information from machine level to the IT environment and vice versa.
Middleware solutions are also now available, which can act as gateways to connect legacy devices to the IT world where necessary.
On-premises servers can offer a good data-handling solution for applications that need fast access to data. When it comes to connecting the OT environment to the rest of the world, security is often a concern. However, if the intention is to analyze and store data in an on-premises IT server, security should already be provided by the factory firewall or existing security infrastructure.
Nevertheless, because any connection point may be a potential security threat, there are always some security measures that should be taken. One way to address this issue is by using “trusted certificates,” a recognized IT security measure. The trusted certification is unique to the OT device on which it resides and can be easily identified by the IT server.
The downside of on-premises servers is that they cannot store infinite amounts of data, so if an application requires huge amounts of data to be processed, a better solution would be to use a cloud-based server. However, this would require more stringent security considerations. The cloud can provide a scalable data storage solution that is not limited by capacity and requires no architecture changes if storage needs change.
The downside of cloud-based servers is that they cannot provide a real-time connection. There will always be some latency when it comes to processing and reacting to data.
When it comes to data storage platforms, different solutions offer benefits in different applications. Tasks such as production visualization lend themselves well to the use of on-premises servers because less data needs to be stored and less data processing is required.
Predictive maintenance requires huge amounts of data and processing power, so it lends itself to the cloud to churn the data to get meaningful outcomes.
Manufacturing traceability probably also lends itself best to the cloud, as it requires vast amounts of information to be stored. Likewise, product-quality–improvement projects are suited to the cloud, as real-time access is not required.
Moving to the edge
Today, more operators are also seeing the benefit of processing data at the edge — close to the device itself — making it possible to gain real-time operational benefits. Using an integral artificial-intelligence controller allows data to be analyzed in real time, allowing for fast reactions to the information at the point of its creation, which enables real-time predictive analysis. However, the limitation of edge technology is that it cannot handle large amounts of data.
The best data-management approach — which allows OT and IT environments to maximize the use of data created — is often a hybrid solution that sees data processed at the edge and then escalated for storage and further analysis in on-premises or cloud-based servers to gain the most benefit from data.
It is useful to know that you can work with the same data in more than one place — for example, using it at the edge first for real-time processing requirements and then escalating the same data for post-processing purposes. This is possible because data is time-stamped, so it can be referenced and synchronized in different applications.
For added data security, it is also helpful to employ controllers that can spool data, so in the event of a connection or data- corruption issue, there will always be a backup — a particularly important consideration in FMCG sectors, which place a high priority on compliance and product traceability.
For most manufacturers, the on-premises server solution will offer the best first step on the digitalization ladder, as it is usually the easiest function to achieve. Indeed, many manufacturers will already have some degree of IT infrastructure installed on the factory floor, so placing data on-premises gives easy access to data. It is also possible to achieve such a solution more cost-effectively if you already have a controller that has the capability to escalate data. Once there, it can be analyzed using a range of low-cost software solutions.
Data is opening many manufacturers’ eyes as they start to understand what it can achieve and what traditional processing issues can now be solved. When it comes to storage and processing options, there is a variety of platforms available — edge, on-premises, or cloud-based servers — to suit the needs of all applications. However, bear in mind that storing data for the sake of it is a costly exercise, so make sure that you use the data and don’t let the data use you.
For engineers, it is reassuring to know that digitalization does not require a fundamental change in the method of manufacturing; its purpose is just to gather and handle data. Engineers should consider digitalization to be just another tool that can give them greater insight into their processes to help improve efficiencies.
This article was originally published on EE Times Europe.