Automation is a Rewarding Challenge
Thinking of automating your entire paint system?
Great choice.
Automation will transform your process and strategically position you for a future driven by data. You'll no longer be reliant on a shrinking pool of skilled and experienced workers. (And, as we observe daily, this trend shows no signs of reversing.)
However, automating your entire system will present its own set of challenges: many processes face communication issues, misaligned interests, and difficulty balancing various factors. Critical areas in your process could get overlooked.
Data Collection is Critical
The point is, we're moving away from decisions based on “gut feelings.”
If you can’t substantiate your position with data, it becomes increasingly irrelevant. We have to establish that a problem exists, understand why it exists, and demonstrate how the proposed solution can solve it.
At times, I encounter customers who are more likely to lean into their gut feelings over hard data. When a customer describes their coating process and the issues they’re facing, alarm bells go off because I have a strong sense of what might be contributing to their quality problems. While my instincts are often correct, sometimes they are not.
That’s why feelings alone aren’t sufficient to secure approval for a capital project. In the interest of achieving our goals, we propose collecting data to tell the story for us.
Is temperature impacting your viscosity? Absolutely.
How much? I don’t know.
Should addressing this in your automated system be a priority? Maybe – Let's find out.
But should you do so without data to justify it? Probably not.
There’s an inexpensive way to avoid fixing non-existent problems or engage in theoretical debates without a clear understanding of the actual situation: strategically installing sensors.
Installing sensors in your process to track and log data is essential because it aggregates and analyzes your data. The more data you have, the more likely you are to make precise improvements to your process.
And the sooner you start collecting that data, the better.
Read more: The Importance of Correlating Data Sets to Identify Root Causes
How Data Collection Can Benefit Automating an Industrial Finishing System
What do sensors look like in a painting system?
That depends.
Our approach typically involves using an in-line viscometer capable of real-time measurement of temperature and viscosity. You can install the viscometer – or multiple viscometers – at key points in the paint circulation line (wherever you decide that measurement is most critical). Throughout the shift, these viscometers send the data to your PLC for collection and analysis.
Imagine, for example, that you suspect temperature is affecting the viscosity of your paint as it travels from the mixing room to the paint booth.
Because you intend to automate your paint system with robots in the booth and convert your mix room into a “smart kitchen”, you contemplate whether it’s necessary to control paint temperature. But without having ever collected data, you have no evidentiary basis upon which to make this capital purchase decision.
One effective approach is to install a viscometer near the source as the paint begins to travel, and another near the dispense point. Continuously monitoring the paint temperature throughout the shift will allow you to analyze how it changes along its path. This is a widely-used method to substantiate whether temperature is indeed a critical factor (based on data analysis).
By collecting and analyzing data, you can substantiate hypotheses, like in the example above, to guide informed decision-making in automating and controlling your paint systems.
Proactive use of data not only avoids speculative fixes, but also ensures that investments in automation and smart technologies are justified by concrete evidence.
Automation can take years to complete. At these early stages, collecting data can prove invaluable, giving you a successful foundation to build upon.
Want to know how to effectively implement into your process?
