Are you a good driver? You rely on your experience to drive safely. But you also take in data that enables you to respond to what’s happening in the moment: traffic lights, headlights, distance from the center line, distance to the side of the road, distance between cars, pressure on the brakes, acceleration, sunlight peeking over the visor, wipers, dashboard lights, the song on the radio, what’s in your rearview mirror, signs, buildings, pedestrians, signals—and so on.

Now, imagine putting on a blindfold and getting behind the wheel.

Manufacturers who operate without real-time quality and process data are asking their production teams to run their lines blindfolded. And that’s a scenario that can lead to disaster.

Modern-day manufacturers strive for optimal efficiency—running production lines at the best speed with minimal downtime while ensuring high quality and low scrap and waste. Achieving that balance is a mix of art and science.

Experienced operators understand what we mean by art. Over time, operators get to know the unique sounds and vibrations—even smells—of the machines they operate. And they understand how small changes affect the products they are making.

When these experienced operators combine real-time data and metrics with their knowledge and experience, they can supercharge product quality and machine efficiency.

On the plant floor, data is plentiful—from process-specific temperatures, speeds, and pressures to product quality measurements, machine verifications, and safety checks.

When data is collected and analyzed in real time, you get instant insight into how a machine is running and what is necessary to prevent quality issues. It’s the science that complements the operators’ art. And it can mean the difference between profit and a shift’s worth of products that gets tossed in the dumpster.

InfinityQS once worked with a company that manufactured newsprint—literally giant rolls of paper. The senior operator told us that one of the most important quality metrics for this product is moisture content. It has to be “just right.”

To demonstrate, he walked under the massive machine, where a span of freshly pressed newsprint was flying overhead and re-rolling at the end of the line. The operator placed his forearm over his head, just barely touching the paper that was zipping by. When he reached the other side of the machine, he turned and reported the newsprint moisture content to within a tenth of a percent.

How do you know that? 

He smiled and calmly said, “I’ve been doing this for 30 years. I know this machine, and I know the moisture content just from the feel of the paper.”

He continued, “But I also know that the moisture content needs to be a couple tenths of a percentage higher. So I turn this knob here, which increases pressure and generates a bit more moisture. Then, I make sure that it’s applied consistently across the entire web,” he said, referring to the width of the giant roll of paper.

“Once I’ve increased the pressure, I measure the moisture at several places across the web using a moisture meter. Then, I record those measurements so I can see how each value changes over time.”

That’s the essential combination: This veteran operator used data analysis together with his artistic expertise to keep his machine running perfectly.

Real-time data becomes even more valuable when you apply it across multiple lines—or multiple plants. Like humans, no two machines are exactly alike. So experienced operators running the same processes on the same machines can get very different results.

A company we worked with bought five “identical” milling machines. The only difference between the machines was the serial numbers. The mills were installed on the same shop floor at one of their facilities. Before being approved for production, the company ran identical tests on each machine for several different material types. What we found was extraordinary.

Under the same test conditions, and for the same material types, each machine produced slightly different quality from the others. Some machines generated inherently more (or less) product variation than others. One of the mills created dimensions that were just a little larger than the other machines. Each mill indeed had its own personality.

Thus, it’s critical for even the best operators to have access to real-time data and analyses to further improve quality. Real-time SPC data provides insights they never would have if they relied solely on instinct. The best operators know that the data they collect expands their knowledge of the machinery and validates their artistry.

You can’t clone your experienced operators, but you can clone their best practices. What they do correctly can be communicated to other operators with standard operating procedures (SOPs).

SOPs help communicate the nuances of successfully running a production line. You don’t want to do away with artistry entirely. But when less experienced operators use SOPs—along with insights from real-time data—it’s easier for them to make machines run right and ensure high-quality products.

Regardless of an operator’s experience, data is essential. And, just like a good driver, your operators need to have that input in real time so they can expedite process control information and minimize quality issues—before they become more serious problems. No blindfolds allowed.

It’s time to give your plant floor production teams access to the information they need. Visit InfinityQS to learn about our best-of-breed quality management platform, Enact—and discover how to access the information you need from the heart of your manufacturing processes.

Copyright ©2022. All Rights Reserved BNP Media.

Design, CMS, Hosting & Web Development :: ePublishing