MPC MaintenanceMPC Maintenance and Improvement Consulting — Any Vendor, No Step Tests
Model predictive controller (MPC) maintenance and improvement is a remote consulting service that fixes poor MPC performance on any vendor software, DMC, RMPCT, Predict Pro, Connoisseur, or any other, using COLUMBO to refit the controller's dynamic models directly from MV, CV, and FF data you already export from your MPC, so prediction errors fall without step tests or downtime.
What an MPC Maintenance Engagement Includes
What an MPC Maintenance Engagement Includes
Model predictive controller performance degrades for identifiable reasons. A PiControl engagement reviews the MV, CV, and FF data you export and diagnoses which of the following are limiting your MPC, then fixes them using COLUMBO and direct process engineering review.
- Incorrect MPC dynamic models
- Poor selection of MV and CV variables inside the MPC
- Poor PID tuning on the slave PID loops feeding the MPC
- CVs and MVs that should be relocated to DCS-based advanced process control (APC)
- Judicious selection and deletion of dynamic MPC models
- Process engineering knowledge combined with the model fit to improve overall MPC performance
Because the review works from exported data rather than a live connection into your control system, it applies the same way regardless of which MPC package generated the data.
ROI and Documented Results
MPC control quality depends on the accuracy of its dynamic models, which drift as feed composition, catalyst activity, and operating conditions change. COLUMBO's optimizer refits the existing models and reduces prediction errors using a methodology not available in any other product, so the controller keeps making the multivariable moves it was installed to make instead of getting switched to manual.
Because COLUMBO reads MV, CV, and FF data directly from Excel files already exported from the MPC, an engagement does not require new instrumentation, a new host server, or new connections into the control system. The same historian data used to run the MPC is the same data used to refit it.
That vendor independence is what lets one methodology cover the whole installed base. COLUMBO has analyzed closed-loop data from active DMC, RMPCT, Predict Pro, and Connoisseur installations and refitted the dynamic models inside each without taking the controller offline for step tests.
The Software Our Engineers Use
Our engineers run every MPC maintenance engagement on COLUMBO, PiControl's closed loop universal multivariable optimizer, so the result is reproducible rather than personal to one engineer.
COLUMBO reads Excel data files containing MV, CV, and FF data exported from your model predictive controller, then its optimizer refits the existing models and improves their accuracy — a fast, novel methodology not available in any other product on the market.
- Independent of your MPC vendor — the engagement works whether your plant runs DMC, RMPCT, Predict Pro, Connoisseur, or another vendor's package.
- Our engineers do not replace your MPC; they refit and improve the models already running inside it.
Delivery and Engagement Scope
MPC maintenance and improvement consulting is delivered remotely. You export MV, CV, and FF data from your MPC into Excel files and send them to PiControl, so an engagement can start without a site visit, a new OPC connection, or any interruption to the running controller.
- Refitting the dynamic models with COLUMBO
- Reviewing MV and CV variable selection inside the MPC
- Tuning of the slave PID loops feeding the MPC
- Relocating certain CVs and MVs to DCS-based advanced process control (APC)
Scope is set by which of the six common root causes apply to your controller — PiControl scopes each engagement to your MPC rather than applying a fixed package to every project.
One Methodology, Four MPC Vendors: Models Refit Without Downtime
COLUMBO has analyzed closed-loop data from active DMC, RMPCT, Predict Pro, and Connoisseur installations and refitted the dynamic models inside each without taking any controller offline for step tests.
How an Engagement Delivers Results
A four-step protocol for every MPC maintenance engagement — from your Excel export to a validated, lower-error model, delivered entirely remotely.
Export MV, CV & FF Data
You export MV, CV, and FF data from your running MPC into Excel files, whatever vendor software it runs on, so the engagement starts from data your plant already collects rather than a new instrumentation project.
MPC Maintenance Consulting FAQ
Vendor compatibility, what COLUMBO fixes, what data to send, and how to get started.
Schedule an MPC Maintenance Engagement
Ready to fix your model predictive controller, whatever vendor software it runs on? Schedule a consultation and a PiControl engineer will review your MV, CV, and FF data, scope the engagement against the six common root causes, and outline the improvement you can expect before any work begins.