By David Schultz
Like it or not, digital transformation is real, and must be a part of your overall business strategy. While most messaging focuses on the undeniable benefits and opportunities, few articles focus on the reality of most companies: they have a lot of older equipment and legacy platforms that still work well, but aren’t currently able to support a digital transformation.
What do you do? Can you teach an old dog new tricks? In this article, I will highlight a few common scenarios that I have come across as companies attempt to tackle their digital transformation journey.
Depending on your industry, there may be a large installed base of older equipment, some of which—in certain cases—is more than 100 years old. The adage “If it ain’t broke, don’t fix it” applies to many companies who very rarely change the products they manufacture. If you have been making the same widget for decades, then it makes sense to run old equipment as long as possible, and make the most of your capital investment. The most common side effect of using legacy equipment is that it does not have any modern communication connectivity.
Of course, the goal of a digital transformation is to have more data available. To do this, you will need to figure out a way to connect and extract data from your older equipment.
One important note I want to highly stress: before you embark on machine connectivity, it is critical to first develop your digital transformation strategy. This strategy will help determine what kinds of activities you are going to perform with the data, which will guide you on what data will need to be available. Otherwise, you end up running the risk of capturing data for the sake of capturing data—and what benefit does that provide? The effort should be deliberate in the early phases, while providing ability for future needs.
Unconnected systems can be considered the stereotypical “old dog,” and therefore can be thought of as the most challenging. Often, they were built in an era where there was no need for external communication. Surprisingly, the easiest and best approach is to contact the vendor to see if they have developed any kind of connectivity solutions. Chances are, they may have some unique solutions of which you can take advantage.
Depending on the control system, one “new trick” can be adding a readily available bolt-on communication module. Many vendors specialize in this type of equipment. A common example of a “new trick” I see often implemented successfully is incorporating simple data collection for machine state and line speed. Again, your transformation strategy will dictate what data you need.
Connected with a Raw Format
Another “old dog” is obsolete or raw data formats that other systems cannot readily access. A common instance of this is capturing data from a weigh scale on a production line. In packaging, one of the metrics is weight control to reduce overweight and underweight products. Enabling a quality department to view scale data as a trend is one way to update processes for digital transformation.
While a scale may have Ethernet connectivity, the raw data stream contains only weight values. In order to trend the data, it needs to be historized, which will add time and quality to those values. The “new trick” in this case is to develop a collector to handle the velocity of scale data, and then store it in a time series database for future retrieval. This will require the purchase of a process historian that supports the development of a collector. In one case, this solution became the foundation of a system that eventually included OEE (operational equipment effectiveness) and SPC (statistical process control).
Connected with Limited Storage
Stand-alone systems that come with the equipment can be considered a third “old dog.” Stand-alone systems are used to operate equipment and provide basic performance metrics. These commonly include items like current process status, trending data, and perhaps cycle data. The challenge is that these systems were not designed to work with other systems in the plant. They were designed for short-term visualization and use. The good news is they often include a small database that can be leveraged.
In this case, the “new trick” is to develop a method to query data from the equipment database and ingest it into another system. This is very similar to the weigh scale above. You should confirm you have received all of the data from the machine before it is deleted. (The data will need to be removed from the equipment in order to prevent the database from filling up.) From there, it can be used to generate daily, weekly, and monthly reports. The same trick can be applied to other equipment to start analyzing how systems work together.
When it comes to purchasing new equipment, you might be the “old dog” that needs to learn a “new trick.” Start by developing your Industry 4.0 strategy. This will guide the features and capabilities you will need. Items such as process variables, counters, throughput, and asset health are a few topics that should be considered.
Work with machine providers in the early phases to ensure they can support this strategy. The last thing you want to do is purchase equipment that cannot do what you need it to do. Most importantly, include these capabilities in your equipment specification.
As mentioned earlier, there is a lot of equipment that performs its intended function quite well; it just needs to be updated. Machine connectivity will become less of an issue as equipment suppliers provide this capability in their standard designs. But instead of replacing equipment purely for this purpose, I hope you consider salvaging your existing investment—and attempt to “teach an old dog new tricks.”
This article is a product of the International Society of Automation (ISA) Smart Manufacturing & IIoT Division. If you are an ISA member who is interested in joining this division, please log in to your account and visit this page.
About the Author
David Schultz has 25 years of automation and process control experience across many market verticals, with a focus on continuous and batch processing. He currently works with manufacturers to help them develop and execute strategies for their industrial transformation and asset management efforts. He is the current Vice President for the Milwaukee Chapter of ISA. He is actively involved in ISA’s Digital Twin and AI/ML technical committees. He is also a member of the Society of Maintenance and Reliability Professionals (SMRP) and Project Management Institute (PMI).