AVEVA™ PI System™ Feedback Portal

Welcome to our new feedback site!


We created this site to hear your enhancement ideas, suggestions and feedback about AVEVA products and services. All of the feedback you share here is monitored and reviewed by the AVEVA product managers.

To start, take a look at the ideas in the list below and VOTE for your favorite ideas submitted by other users. POST your own idea if it hasn’t been suggested yet. Include COMMENTS and share relevant business case details that will help our product team get more information on the suggestion. Please note that your ideas and comments are visible to all other users.


This page is for feedback specifically for AVEVA PI System. For links to our other feedback portals, please see the tab RESOURCES below.

Add a new idea Subscribe
Status No Status
Product AVEVA™ PI DataLink™
Categories Functions
Created by Matt Voll
Created on Aug 16, 2022

RELATED IDEAS

Interpolate Step=On Tags

There are tags that should be kept as Step=On but there is certain cases in which someone should be able to easily bypass the typical interpolating rules (interpolation that follows the step parameter) and allow for a true interpolation between values The cumbersome workaround is to utilize performance equation functions within the expression field . . . but that's pretty advanced usage
  • Attach files
  • Kenneth Barber
    Reply
    |     Aug 16, 2022
    What do you mean by "true interpolation"? Do you mean linear interpolation (i.e. treat the Step = on tag as if it were Step = off)?
  • Matt Voll
    Reply
    |     Aug 16, 2022
    yes, so that a user can force the tag's interpolation to behave as if it was Step=off, instead of is true behavior of step=on
  • Kenneth Barber
    Reply
    |     Aug 16, 2022
    In what cases would you want to keep Step = on but use linear interpolation?
  • Matt Voll
    Reply
    |     Aug 16, 2022
    For us lab data is common numerical data point that we use Step=ON for. A process sample analyzed by a lab represents a single moment in time, when the sample was taken, and due to the infrequent nature of the sample (ranging from once per hour to once a day), it would not be accurate to represent this data, visually, using linear interpolation. The process could be following any variety of behavior between the data points; roller coaster ups and downs, steady average with occasional dips, erratic with occasional spikes, etc, etc. So lacking this context the most reasonable assumption is to have step=on and have the data merely represent the state in which the process was last analyzed. Higher frequency process data, like from instruments, is sampled/scanned/advise at a higher frequency, that is reasonable to assume a linear interpolation trend between data points since they are likely less than a minute apart (ignoring any compression factors in that statement). This step behavior also helps user realize that lab data should be event-weighted summarizations and not time-weighted. a once per shift lab sample is meant to represent 8 hours of time, if the process is down or a shift sample is missed, using time-weighted summarization results in the last sample before the gap to be over represented compared to other data point That explains why lab data would be Step=ON as a default. . . now when we get to subsequent data analysis . . . well different users want to treat the data differently based on their own judgement, and possibly make different assumptions . . . even lacking the context mentioned above. Taking a big data set for a modeling effort results in numerous decisions and assumptions in an effort to clean, filter, align data . . . I don't see any reason why they shouldn't be able to actively make the decision to use linear interpolation on a step=on tag if they so choose and makes sense for their analysis