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Description
MPCPy is a Python library designed to support the testing and execution of occupant-integrated model predictive control (MPC) within building systems. This tool emphasizes the application of data-driven, simplified physical or statistical models to forecast building performance and enhance control strategies. It comprises four primary modules that provide object classes for data importation, interaction with real or simulated systems, data-driven model estimation and validation, and optimization of control inputs. Although MPCPy serves as a platform for integration, it depends on various free, open-source third-party software for model execution, simulation, parameter estimation techniques, and optimization solvers. This encompasses Python libraries for scripting and data manipulation, along with more specialized software solutions tailored for distinct tasks. Notably, the modeling and optimization tasks related to physical systems are currently grounded in the specifications of the Modelica language, which enhances the flexibility and capability of the package. In essence, MPCPy enables users to leverage advanced modeling techniques through a versatile and collaborative environment.
Description
Navigating the complexities of industrial processes presents a significant challenge for businesses striving to be both responsive to market demands and economically viable. To meet these challenges, manufacturers are required to refine their production techniques in order to offer an expanded range of higher-value items while also accommodating shorter production runs. It is essential for them to enhance output, optimize operational efficiency, and elevate product quality to the fullest extent permitted by their existing equipment. Achieving this necessitates maximizing equipment uptime and facilitating smoother transitions while minimizing waste. Furthermore, there is an increasing expectation from the public for manufacturers to lessen their environmental footprint and adhere to strict emissions regulations. Rockwell Automation Pavilion8® Model Predictive Control (MPC) technology serves as an advanced intelligence layer that integrates with automation systems, continuously steering the plant toward achieving a multitude of business goals—including cost savings, reduced emissions, consistent quality, and increased production—while operating in real time. This innovative approach not only enhances operational effectiveness but also aligns with sustainability initiatives, positioning manufacturers for success in an evolving marketplace.
API Access
Has API
API Access
Has API
Integrations
Python
Ubuntu
Pricing Details
Free
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
MPCPy
Country
United States
Website
github.com/lbl-srg/MPCPy
Vendor Details
Company Name
Rockwell Automation
Founded
1903
Country
United States
Website
www.rockwellautomation.com/en-us/products/software/factorytalk/operationsuite/pavilion8.html
Product Features
Product Features
Manufacturing
Accounting Integration
ERP
MES
MRP
Maintenance Management
Purchase Order Management
Quality Management
Quotes/Estimates
Reporting/Analytics
Safety Management
Shipping Management
Manufacturing Intelligence
Aggregation
Analysis
Contextualization
KPIs
Propagation
Visualization