Avoid drowning in data with data analytics software

If you’re drowning in data, machine learning software may be an anchor, with data analytics software often a better solution.

By Dan Hebert, PE, contributing editor

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“To install Seeq, the machine or skid builder could put it on the same PC housing the historian data or on another PC, in either case using the software’s data connector to automatically link to the historian. Once the data connection is made, an engineer can use the intuitive, Web-based interface to investigate performance attributes or create reports,” explains Risse.

Data analytics software is always used in a directed fashion by the engineer or expert.

Without a tool like Seeq, the alternative is usually a spreadsheet. Data is exported from the historian to the spreadsheet software, a task which must be performed for each data set of interest. Once the data is in the spreadsheet, it takes someone very well-versed in spreadsheet manipulation and programming to analyze the data and generate reports. This difficult set of tasks causes many to give up because the effort required isn’t worth the potential return.

But, with data analytics software, improvements can be realized in a few hours rather than days or weeks, as the tool is specifically designed for the particular task of analyzing time-series data, as opposed to a general purpose tool like a spreadsheet. The software is also designed for use by engineers, with no programming or IT specialists required.

“In the past 24 months, we have seen two trends in the media,” relates Hans De Leenheer, the vice-president of marketing at TrendMiner. “First, we need to hire more data scientists, and, second, we need them to talk to the process engineer. Only the second part is true, as our software doesn’t require a data scientist. The only reason why data analytics in industry has not evolved as in some other sectors is because the data only makes sense when it is combined with the experience of the engineer or expert; otherwise, they are just numbers.”

Also read: Cognitive computing in the cloud is smarter than you think

The most critical attribute of any machine or process skid is usually availability or uptime, so insights into health and future operating state are paramount. Data analytics software has advanced trending, search and batch analysis tools, so comparisons among product or process runs—or checking variability in performance over time, batches or production runs—becomes a matter of minutes rather than hours.

Optimization is another priority, such as tweaking processes to gain a percent or two on margin, yield or quality attributes. “Our customers say they know what they want to do, but it’s just too hard or takes too long using the same approaches they have used for 20 years: Excel, programming scripts and elbow grease. Seeq changes the investigation paradigm by bringing analytics and insight into an advanced trend viewing application, so visualization, data manipulation, data cleansing and search capabilities are an integral and intuitive part of the user experience,” continues Risse.

The activities described by Risse can improve the operation of individual machines and process skids, but what about the much more complex and often more important task of optimizing an entire plant?

“Our software has the ability to aggregate data from one asset in the context of other data sets or other data sources to investigate issues across a plant. So, the process the asset is a part of can be improved as a whole by integrating machine, process skid and other data sets to enable analytics across the entire production line,” concludes Risse.


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