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What is Imubit?

Imubit’s AI-driven platform offers real-time, closed-loop optimization for processes within heavy industries by combining a dynamic process simulator, a reinforcement-learning neural controller, and performance tracking dashboards. The dynamic simulator harnesses a wealth of historical data alongside fundamental principles to construct a virtual model of actual processes, enabling what-if scenarios that explore the interactions among variables, shifts in constraints, and modifications in operational tactics. In parallel, the reinforcement-learning controller, which has been developed through extensive offline training with millions of trial-and-error scenarios, serves to continuously refine control variables, boosting profit margins while maintaining compliance with safety regulations. The real-time dashboards provide insights into model availability, user activity, and operational uptime, complemented by interactive visualizations that illustrate boundary conditions, operational thresholds, and trends in vital performance metrics. This advanced technology finds its applications in aligning economic strategies with real-time data and spotting instances of process decline, thereby promoting heightened efficiency and safety across operations. By adopting this holistic strategy, industries are better equipped to respond promptly and effectively to evolving conditions, ultimately leading to more resilient operations.

What is COLUMBO?

A universal multivariable optimizer, designed for closed-loop systems, aims to improve the performance and quality of Model Predictive Control (MPC) systems. This optimizer harnesses data from Excel files derived from Dynamic Matrix Control (DMC) by Aspen Tech, Robust Model Predictive Control Technology (RMPCT) from Honeywell, or Predict Pro from Emerson, facilitating the development and fine-tuning of precise models for various multivariable-controller variable (MV-CV) pairs. This cutting-edge optimization solution does away with the need for step tests that are usually required by Aspen Tech and Honeywell, functioning entirely in the time domain to maintain user-friendliness, compactness, and efficiency. As Model Predictive Controls (MPC) often involve numerous dynamic models—sometimes tens or even hundreds—there is a significant risk of utilizing incorrect models. Inaccurate dynamic models in MPCs can introduce bias, which appears as model prediction errors, leading to inconsistencies between expected signals and actual sensor measurements. COLUMBO emerges as a robust tool to bolster the precision of Model Predictive Control (MPC) models, effectively leveraging either open-loop or fully closed-loop data to guarantee peak performance. By tackling the risks associated with errors in dynamic models, COLUMBO not only enhances the reliability of the control system but also contributes to a more efficient operational framework. Ultimately, its implementation is expected to yield substantial advancements in control system effectiveness across various applications.

Media

Media

Integrations Supported

Integrations Supported

Aspen DMC3
Microsoft Excel

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Imubit

Date Founded

2016

Company Location

United States

Company Website

imubit.com

Company Facts

Organization Name

PiControl Solutions

Company Location

United States

Company Website

www.picontrolsolutions.com/products/columbo/

Categories and Features

Industrial AI

Not specified

Industrial Automation

Not specified

Categories and Features

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