Recently updated on October 25th, 2022 at 12:09 pm
Exploiting data to improve processes and predict outcomes is not something new, manufacturing plants and the oil and gas industry have been using them for a long time through industrial internet of things. In fact, it has been widely used in industries since the 1980s.
However, big data collection was limited to archiving and storing massive volumes of information. Interpreting them was still left to engineers or plant supervisors who then drew on their vast experience to make sense of the numbers.
As you can see, you needed a knowledge worker that operates the data historian system to come up with accurate results.
The setup was very limiting and quite dangerous frankly, especially if the specialist tasked to monitor and operate the system figures into an accident. What happens if the worker would be unavailable for a considerable period, and you cannot find a viable replacement?
So, you can put more value on these data historian solutions if they are accessible to as many people as possible.
For instance, if the system can be linked to the Excel Spreadsheet, then the numbers are presented in such a way that anybody can understand them. By looking at the figures, you can quickly make a diagnosis of the status of the equipment and terminals.
Fortunately, modern process historian tools already feature this capability, which only enhances their value to any organization. These data management solutions are no longer limited to specific industries as they cross over to retail, marketing, and other soft fields.
What about the Industrial Internet of Things?
Nowadays, people are talking about the Industrial Internet of Things (IIOT) and how it will severely handicap data historians. Both processes will give the user unparalleled insight into the internal processes of the organization. However, they have different ways of doing so.
Some analysts are predicting a digital disruption, and there is some grain of truth in that assumption. But only if you compare the IIOT with yesterday’s data historians.
Admittedly, old solutions depend heavily on the user to input the needed parameters and then analyze the data. Nowadays, the data is aggregated and classified at the onset of implementation. The system can also collect almost unlimited data and come up with a variety of analysis that offers a wide range of options. As a result, the user will have more flexibility to use the data repeatedly and for different purposes.
Data insight can also be accessed anywhere, including your mobile devices. It means you can bring your office anywhere. You can leave the plant and be on a business trip but remain updated of what is going on. Data historian systems are valuable tools to monitor manufacturing plants in different locations. All the operational information will be collected and classified in a central server.
Also, you need to factor in the cost. The Industrial Internet of Things is quite expensive to install compared to the data historian. Also, you might be overpaying for a tool if you could not maximize its features.
In standard operations, the data historian system is sufficient for you to monitor real-time and historical data, predict events (Sequence of Events), and produce a trend chart. As a result, you will be able to manage your assets better. So, in the end, the death of data historians is a gross exaggeration. It still has a place in industries and will remain so for a very long time.