MPCPy

DigitalClone® for Engineering is the world's only gearbox reliability prediction solution integrating multiple scales of analysis in a single software package. In addition to modeling and analysis capabilities at the gearbox and gear/bearing levels, DC-E is the only solution available that models fatigue life based on detailed, physics-based models of the material microstructure (US Patent 10474772B2). DC-E enables construction of a gearbox digital twin with high value across all stages of the lifecycle of the physical asset - from design and manufacturing optimization to component supplier selection to failure root cause analysis to condition-based maintenance and to prognostics. This computational environment drives down the time and cost to bring new designs to the market and to sustain them over time.

Closed-loop universal multivariable optimizer for Model Predictive Control (MPC) performance and Model Predictive Control (MPC) quality improvements. Use data in Excel files from DMC (Dynamic Matrix Control) from Aspen Tech, or from RMPCT (Robust Model Predictive Control Technology) from Honeywell, or Predict Pro from Emerson and use it to generate and improve correct models for the various MV-CV pairs. Amazing new optimization technology does not need step tests as required by Aspen tech, Honeywell, and others. It Works entirely in the time domain, is easy to use, compact, and practical. Model Predictive Controls (MPC) can have 10s or 100s of dynamic models. One or more could be wrong. Bad (wrong) Model Predictive Control (MPC) dynamic models produce a bias (model prediction error) between the predicted signal and the measured signal coming from the sensor. COLUMBO will help you to improve Model Predictive Control (MPC) models with either open-loop or completely closed-loop data.