Has anyone taken a course that goes deep on mold level control and breakout detection, ideally AIST or OEM-led? I’m on a two-strand slab caster (180 cpm, 3.5 mm stroke) and want training with hands-on PID tuning and signal filtering using historian data to cut sticker alarms and tighten surface quality.
Are you on Primetals, SMS, or Danieli? Check AIST’s technology training and the OEM-led classes — Primetals Mold Expert and SMS Concast both offer solid MLCS tuning; start here: 404 - Page Not Found. While you’re waiting, pull a 30–60 min steady-state historian slice and do small valve bumps to ID the loop; at 180 cpm (about 3 Hz) add a notch or tight low-pass at the oscillation (earplugs for the sensor) and retune the PID in velocity form with casting-speed feedforward.
And good option: AIST’s Continuous Casting training usually includes a PID/IMC lab and real case work — check the calendar: 404 - Page Not Found. Ahead of that, export a shift of PV/CO and trial a narrow notch around 3 Hz (your 180 cpm) before retuning with IMC to put a leash on the wobble; OEM classes are solid but tool‑specific — @lucy_wilson02 which OEM are you on?
Big win for us: run a clean 10–15% speed bump, fit a FOPDT from the historian, set IMC-PI with lambda about 2*tau, then insert a tight notch at the oscillation frequency (about 3 Hz) before the PID — false stickers dropped about 30% and surface tightened. EMBr on or off, and what level sensor are you running, @lucy_wilson02?
One trick that helped us was moving to two‑DOF PI so setpoint steps don’t kick the meniscus; we kept our IMC gains but set ‘beta’ around 0.4 and added a 1–1.5 s low‑pass on the stopper feed‑forward, which cut nuisance stickers without dulling rejection. If you can, log a couple of small setpoint steps and compare error vs. control effort before/after to confirm you’re not starving the actuator. Does your controller expose setpoint weighting and feed‑forward filtering?
And quick win for us was adding speed feedforward so the stopper pre‑moves on ramps; we fit Kff from a about 6% speed step in the historian and clamp integral inside ±1.5 mm so noise at the meniscus doesn’t wind it up. With a short 3.5 mm stroke that cut sticker alarms a lot — does your controller let you add a basic feedforward term alongside the PI for that “signal filtering using historian data” push?
Closest fit I’ve seen for ‘hands‑on PID tuning’ is the pre‑AISTech continuous casting workshop on automation/control, and OEM‑wise Primetals (MoldExpert) and SMS group both run onsite mold‑monitoring sessions using your historian data. Ask them to deliver a two‑speed tuning matrix and an explicit deadtime ID so you’re not tuning by flashlight at 3 a.m. What level sensor are you on — EMLI or radiometric?
, at “180 cpm” (about 3 Hz) and 3.5 mm stroke, a synchronous notch tied to the oscillator encoder cleaned up our meniscus trace far better than smoothing alone, which let us push I a bit without spurious sticker alarms. For training, ISA’s Advanced Loop Tuning let us bring our own caster trends and work through filters on real data; not caster-specific, but it translated well: Training - ISA. Do you have an encoder signal you can sync to for the notch?
And building on @nathaniel_smith22, if you can swing an OEM onsite clinic, push for a two-DOF PID (setpoint weighting) plus an integral hold when meniscus velocity exceeds a small threshold; that kept our controller from ‘chasing ghosts’ and cut stickers about 25% for us. Do you log EMBr current and torch trims in the historian? Mapping those as a disturbance input during the lab moved the needle more than heavier smoothing, not a silver bullet but quick to try.
Before you pick a course, ask if they’ll run a short ‘replay’ lab with your historian data; we did this at 180 cpm by stepping stopper position about 0.5% during a speed hold, fit a quick FOPDT in PI/Seeq, and IMC‑tuned the PI so we walked in with gains that stuck. Caveat: we had to slow the filter a touch at higher casting speeds and recheck breakout thresholds afterward; would an OEM clinic let you do that with your data, @nathaniel_smith22?