Manufacturers with automation and control systems rely on historians to retrieve and record instrumentation and control data from their production processes. Historians provide data compression for storing and retrieving large amounts of data efficiently. This enables applications and analytics to further utilize the data for system optimization, quality indication, product traceability, and specifications.
Historians also store metadata that describe the source sensors or measurements. Metadata may include measurement source, units, frequency, and datatype. In some cases, the expected limits or baselines are set from industry standards or expected norms. Actual data may not always trend to these standards. This variance can result in false-positive alerts, impacting production and quality metrics and even influencing how personnel approach monitoring and reacting to alerts.
So how does a manufacturer ensure the right data is being measured at the optimal frequency and within the correct limits? Performing an audit of all tags being recorded by the historian during a set time range using statistics and visualizations can provide initial insight into the quality of tag measurements.
Measurement Variations
How many distinct values is each tag recording? How many tags are recording thousands of different values verses only a few different values? Are there any tags only recording a single value? Understanding this piece of information can help determine if historians are set up correctly and collecting useful data.
Frequency of Collection
How many values were recorded for each individual tag? For example, if one week’s worth of data was selected are there any tags that recorded only 10 different values? You might find a tag collected only 1 distinct value a few different times, indicating the tag may not be mapped or recording properly. Like variation measurements, this is another way to verify the historian is set up correctly, as well as to confirm that the target does require a historian collecting from it.
Consistency of Collection
A quick analysis of collection rates will help determine if values are being recorded at the level of consistency intended. How much time is lapsing between when tag values are being collected and how often are these lapses occurring? This can shed light on devices that are down or unresponsive for extended periods of time.
Measurement Statistics
Examine the minimum value, maximum value, average, median, and standard deviation for each tag. Are these values in line with what is expected for each piece of equipment being monitored? The standard deviation gives insight into how volatile a tag is in the values it’s recording. Further, examine tags for like equipment together. Do any of the statistics reveal anomalies between tags?
These are just a few of the ways historian tag data can be audited. Taking a deep dive into the data being collected by historians can give manufactures confidence in their data quality, appropriate limits, and valuable alerts. It also ensures the historians you took time, energy, and money to install are set up correctly and collecting the values you expect.
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Jessica DeBoom, Interstates Business Analyst
