At its core, Digital Transformation simply means adding digital technologies to our manufacturing and industrial processes. A big by-product of this work is easy access to reams and reams of data. A Process Engineer, can see a wider variety of information about his process and in higher fidelity. A Production Manager, can have immediate access to production counts, reject rates, customer order statuses. Maintenance managers can monitor, proactively check and in some cases, predict when an important piece of equipment is going to fail. With all these scenarios you need to be able to make sense out of all this data to make prudent decisions. Colorful charts and graphs and 360-degree dashboards impress tour groups, but someone or something has to do the hard work of putting this data in context, if real productivity gains are to be realized.
I’ve recently learned about 2 new ways to add context to process data:
- Trend Annotation. We now have the ability to add notes that are directly tied to a process parameter at a specific point in time. All team members will see these notes anytime they go to review process charts and graphs. This is not only a way to provide context and commentary, but also a great collaboration tool to make sure everyone is in tune with the most current information. In a past blog, I referenced work I had done for an aluminum manufacturer a while back. In those days, the process engineer spent a lot of time studying aluminum Hot Mill vibration signals and conferring with maintenance on what to do and when to do it. Today, he could add notes to the vibration trend, in real time, indicating that it may be time to do roll change due to the vibration patterns. The maintenance engineer would see the notes in the trend and could easily confirm that it was time to make the roll change.
- Alarm Information Annotation. Similarly, we ALSO now have the ability to overlay alarm information on top of the process data charts. This can be used to easily identify process conditions that warrant deeper analysis. Most older systems have process data and they have alarm data, but those two data sources are not always correlated or put in context to help with decision making. When I was doing plant startups in the process industry, we were constantly monitoring the plant’s key variables, such as the kiln temperatures and gas concentrations, to bring systems online. We also had to simultaneously monitor the process alarms to verify that we were not in a running in an out of tolerance condition. I would have loved to have the ability to see the kiln temperatures and the alarms conditions overlaid on the same graph as we now can. This would have made it much easier for me to optimize these control systems. I am sure this will be a valuable tool for you when analyzing your processes.
I’ve prepared a video to share how you might take advantage of these new capabilities and quickly put your data in better context.