Let’s start with the PI ProcessBook question – you may use the XY-Trend and use your footage tage for the X axis and for the Y axis your process variables.
For the other question – I think the way is you have to use your footage tag and run the calculation on this. If you calculate the footage “live” – you may use the totalizer with results written upon expression change. This will eliminate all programming , but probably will reduce maintenance .
The problem though that I may run into is that I am adding the footage programically in history since I do not know the start and end of a coil until it has been produced so I need to back calculate.
This means that the process data I wish to aggregate has already been added to the PI archive and the footage is added after the fact. My understanding is that the totalizer works off of the snapshot?
In short, I need to perform this calculation on data that has already been written to the archive, after the fact. The start and end time for the calculation is also based on the start and end of each coil when it is in a unit batch.
One master EF for the batch and then a child event frame for each 5 foot increment. Then have Atrributes using the PI Point data reference to calculate your process data statistics using the containing EF's Start Time and End Time as parameters. Once you create some "coil" templates the only bit of programming you will need will be the EF generator part. The snag being the EF product is not in production just yet...
I do not mind that it is not in production as much that there are none of the major clients available to my customers such as process book, datalink, oledb.....
I am waiting on that one.
also, I would have never thought of using event frames in such a way. Will event frames handle the load of a coil produced every 4 minutes and each coil having about 400 children (2000 ft / 5 ft)?
If there is no other alternative, I guess maybe when I calculate the 5 foot increments I will also get the value for the process variable I need in 5 foot incrfements and write this to PI in a separate PI Point. I can then do statistics based off of events (by value and not time)
The disadvantage to this is that it is additional PI Points and gives me a rigid number of process variables to observe in this way. If I wish to add or detract from the process variable list, I will need to make a code change.
Any other thoughts or suggestions would be highly appreciated.