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What is Oracle Real-Time Decisions?

Oracle Real-Time Decisions (RTD) merges rule-based methodologies with predictive analytics to deliver adaptive solutions for real-time enterprise decision management. This system allows for the seamless integration of immediate intelligence into business processes or customer interactions as they unfold. A powerful transactional server guarantees that decisions and recommendations are generated instantly. This server autonomously generates decisions within the business workflow, revealing insights and converting real-time data into actionable intelligence. Through closed-loop decision-making, organizations can implement comprehensive business logic with efficiency. Moreover, analytical decisions enable firms to leverage existing analytical resources for both rule-based and predictive selections. In addition, self-adjusting processes empower organizations to develop systems that automatically evolve in response to feedback, ensuring continuous optimization and flexibility. Notably, this blend of technology not only enhances responsiveness but also cultivates a smarter business landscape that is well-equipped to meet changing demands. The ongoing evolution of these systems positions companies for greater success in a fast-paced environment.

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

IBM WebSphere Application Server
Oracle Application Testing Suite

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
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Oracle

Company Location

United States

Company Website

www.oracle.com/middleware/technologies/real-time-decisions.html

Company Facts

Organization Name

PiControl Solutions

Company Location

United States

Company Website

www.picontrolsolutions.com/products/columbo/

Categories and Features

Decision Intelligence

Not specified

Decision Support

Not specified

Predictive Analytics

Not specified

Categories and Features

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