Transforming Valve Data into Dollars

Summary

We live in a digitally connected world, surrounded by mountains of potentially valuable process data. The underlying premise is that more data equals more value, so any device or software application that gathers more data must be worth the purchase price.
 
Unfortunately, the reality is that data only has value if one does something with it, as data serves little purpose if it remains stored away on a hidden database, never to be seen again. Historically, the focus has been on data gathering, but new applications are entering the market that analyze that data and convert it to economic value. This article will look at one such solution for valves—a new software application that converts data into actionable information.
 

The migration of analytics

Data used to be difficult and expensive to obtain. Sensors were bulky and costly, and once data was obtained from them, it was difficult to transport or analyze. Not that long ago, a strip chart recorder was considered state of the art. An expensive transmitter was hooked up to a high-speed paper recorder, and the resulting miles of pen traces were then studied for insights.
 
Around the 1980s and into the 1990s, the price and power of electronic chips began to fall, and sensors began to shrink, stimulating a revolution of data gathering. Suddenly, diagnostic data was available that had never been present before, allowing technicians to review it and determine why something failed (Figure 1).
 
As information became more widely available, it enabled the technical staff to quickly identify why something failed, a technique often referred to as diagnostic analytics. That level of analysis was certainly useful because it allowed technicians to quickly troubleshoot and resolve problems. However, the data was typically captured and stored at the device level, so it could only be obtained by going into the field and downloading it locally. This was usually done after the equipment had failed and impacted production.

 
The next generation of data analysis

Advances in predictive analytic software, such as Emerson’s Plantweb Insight Valve Health App, have enabled a new, more cost-effective solution. Rather than depending on local or remote valve experts to monitor the data stream, specialized software running predictive analytics is used to evaluate and monitor the incoming field device data stream (Figure 3). The software is always on, looking for immediate issues but also using the historical data to spot trends, highlight developing problems, and even predict impending failures well in advance.

A range of analytical options

Similar predictive and prescriptive analytic software applications have been developed for a wide range of plant equipment (Figure 7). Utilizing the same types of data networks and process instrumentation, these software applications continuously monitor process conditions to detect degraded performance.
 

 
Data into dollars

These advanced analytic software applications convert the overwhelming wave of data into specific recommended actions to resolve problems and avoid unexpected failures, increase safety, and significantly improve process reliability. This is especially important for valves because they are often critical to plant operation, and they can degrade in performance over time due to a multitude of reasons. To learn more about this new Plantweb Insight Valve Health App, please contact your local Emerson office or Emerson Impact Partner.
 
_{All figures courtesy of Emerson}