Fewer Metrics Leads to Better Results

Big Data and IIoT have captured the automation industry’s imagination. A key take-away from all that’s been written is that plant data holds the key to making many production processes safer, more efficient, and more profitable. While there’s growing evidence that Big Data and IIoT are delivering meaningful value, some scientists have begun to wonder if there is a limit to the amount of information that is actually helpful. They’ve posed the question: At what point does information become detrimental to the people who rely on it?

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What to Learn from a Plant’s Frequency Data

If you’re old enough to remember the Internet browser called Netscape, then you may remember the company’s CEO – Jim Barksdale – who once quipped: “If we have data, let’s look at data. If all we have is opinions, let’s go with mine.” Fortunately for those that come to this blog there’s typically sufficient amounts of data. That said, a question often raised relative to a plant’s process data is: What gems are hidden in it?

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How Does Loop Monitoring Help with Root-Cause Analysis?

For most individuals, a house is the most expensive asset that they’ll ever purchase. And while living there a homeowner can expect a significant problem or two to arise whether that problem involves a leaky roof, termite damage, or some other costly issue. A downside of such problems is that the damage is typically and irrevocably done before the homeowner encounters the first visible signs that the issue even existed.

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