What technique did you use to derive the k=16.859, ti=5866.1?

Currently I'm using the Smith example, I've removed the SOPDT in the Smith predictor with FOPDT as you suggested.

In the top FOPDT I have:
Ko .093
del 720
tau 5400

In the bottom FOPDT I have:
Ko .028
del 420
tau 1500

In the process model I have:
Ko .059
del 540
tau 3600
tau2 4200

In the PIDMA I have:
picture attatched

I am constantly overshooting this simulation, any ideas?

Good morning Jaroslav,
My process ranges:
Gain .028 - .093
TimeConstant 25min - 90min
DeadTime 7min - 12min

See if I am understanding this correctly.
The 'smith predictor - process model' is my software process. I've updated the gain, Tc, and DeadTime with my known real world process. If I wanted to use this smith predictor example for real world applications I would remove the 'smith predictor - process model' with my real PV signal?

Nevermind about the PIDMA, looks like I need to upgrade if I want that.

I have a process that I am controlling using a PLC with a PI controller that is very very slow, process takes around two hours to get up to setpoint and most often over shoots excessively.
I am looking at using the Smith Predictor as a way to control my process (example project 0303-29). I see where I can insert my SP but dont understand where I would insert my PV, would it be the CNR_INP_DIST?
Can this Smith Predictor example be used in a real world application? Of course with some minor changes!
Also I have a license GY8G-H7MH-2U5A-8IFC-9X7U-9XT4-P8IK-LMXU and am trying to use the PIDMA but am getting a error that says I dont have the capability to use that FB.