Plant-Wide MPC Coordination for Continuous and Batch Operations
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Industrial process control and automation systems face challenges in optimizing both continuous and batch operations, particularly in integrating intermediate components produced under different time frames, leading to manual adjustments and loss of manufacturing profit due to the difficulty in honoring lower-level operating constraints.
Innovation Solution
A cascaded model predictive control (MPC) approach is implemented, where a master MPC controller uses a planning model to perform plant-wide optimization, receiving constraints and proxy limit values from slave MPC controllers to ensure continuous conversion of raw ingredients into intermediate components and non-continuous production of final products while honoring process variable constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a master MPC controller performs plant-wide optimization including both continuous and batch operations, then manufacturing efficiency and profit margins are improved, but the device complexity and difficulty of detecting and measuring increase
Solution Approach 1:
The control system is segmented into a master MPC controller that performs plant-wide optimization and multiple slave MPC controllers that handle specific process units. This segmentation allows the complex optimization problem to be divided into manageable parts while maintaining overall system coordination through the master controller.
Solution Approach 2:
The master MPC controller acts as an intermediary between the planning layer and slave controllers, translating high-level production targets into coordinated control actions across multiple process units. It mediates between continuous and batch operations to achieve plant-wide optimization while respecting individual unit constraints.
2Reliability
If the master MPC controller integrates constraints from multiple slave MPC controllers, then the ability to honor lower-level operating constraints is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The master MPC controller receives feedback from slave MPC controllers in the form of proxy limits that indicate the extent to which process variables can be adjusted without violating constraints. This feedback mechanism enables the master controller to integrate constraints from multiple sources and make informed optimization decisions.
Solution Approach 2:
The system transforms complex constraint information from slave controllers into simplified proxy limit parameters that the master controller can easily process. This parameter transformation maintains constraint satisfaction while reducing the complexity of constraint integration.
3Loss of time
If continuous conversion of raw ingredients into intermediate components is optimized alongside non-continuous production of final products, then loss of time is reduced, but the device complexity increases
Solution Approach 1:
The master MPC controller merges the optimization of continuous conversion processes and non-continuous batch production into a unified plant-wide optimization framework. This integration allows simultaneous optimization of both operation types, reducing production time by coordinating material flows and scheduling across different process modes.
Data Source
Figure 1
Figure 2A
Figure 2B
AI summary
Constraints are received on initial components and intermediate components. Information is received on the products to be produced including a quantity of each of the products to be produced and a specification that specifies how the intermediate components are to be combined to form each of the products. An optimization is performed that includes the continuous conversion of initial components into the intermediate components as well as subsequent production of the products, subject to the constraints on each of the initial components, the constraints on each of the intermediate components, and the quantity of each of the products to be produced.