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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Enhance the precision and sustainability of Advanced Process Control (APC) models by integrating both linear and nonlinear variables through deep learning techniques, thereby expanding their operational capabilities. Achieve better return on investment by facilitating swift controller implementation, ongoing model enhancements, and more streamlined workflows that simplify the process for engineers. Transform the model development landscape with artificial intelligence and refine controller tuning via intuitive wizards that guide users in defining both linear and nonlinear optimization goals. Boost controller availability by utilizing cloud technology to access, visualize, and analyze real-time Key Performance Indicators (KPIs). In the fast-paced global market, energy and chemical industries must adapt with agility to satisfy consumer demands and optimize profit margins. Aspen DMC3 represents cutting-edge digital technology that empowers companies to realize a 2-5% increase in throughput, a 3% enhancement in yield, and a 10% decrease in energy consumption. Explore the innovative advancements in next-generation advanced process control technology and discover the transformative impact it can have on operations. This technology not only boosts efficiency but also supports sustainable practices within the industry.

Description

Cybernetica specializes in providing Nonlinear Model Predictive Control (NMPC) utilizing mechanistic models. Our innovative software solution, Cybernetica CENIT, features a versatile architecture capable of addressing diverse industrial challenges by delivering optimal strategies. This includes advanced multivariable optimal control, predictive control mechanisms, and intelligent feed-forward strategies, along with efficient handling of constraints. Furthermore, our adaptive control capabilities leverage state and parameter estimation, incorporating feedback from indirect measurements via the process model. The use of nonlinear models allows for effective operation across extensive ranges, enhancing the management of nonlinear processes. This leads to a diminished reliance on step-response experiments and bolstered accuracy in state and parameter estimations. Additionally, we offer control solutions for both batch and semi-batch operations, efficiently managing nonlinear processes that function under fluctuating conditions. Our technology also ensures optimal grade transitions in continuous operations, safe supervision of exothermic processes, and control of unmeasured variables, including conversion rates and product quality. As a result, we contribute to reduced energy consumption and a lower carbon footprint, while also enhancing overall process efficiency. In summary, Cybernetica is committed to advancing industrial control solutions that optimize performance and sustainability.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

COLUMBO

Integrations

COLUMBO

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Aspen Technology

Country

United States

Website

www.aspentech.com/en/products/msc/aspen-dmc3

Vendor Details

Company Name

Cybernetica

Country

Norway

Website

cybernetica.no/technology/model-predictive-control/

Product Features

Oil and Gas

Compliance Management
Equipment Management
Inventory Management
Job Costing
Logistics Management
Maintenance Management
Material Management
Project Management
Resource Management
Scheduling
Work Order Management

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