Batch Control Using Bang-Bang Algorithms
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Solution Overview
Problem
Batch process control systems face challenges in maintaining product quality and efficiency due to difficulties in measuring product properties until the end of the batch, leading to high variability and inability to proactively compensate for disturbances, resulting in suboptimal final product specifications and process operability.
Innovation Solution
An advanced batch control method that uses empirical or semi-empirical models to predict final product quality attributes, applying control algorithms in real-time at decision points within the batch process, optimizing process variables to achieve desired set points and reduce variability, and incorporating feedback mechanisms for model adjustment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If basic automation systems use feedback control to adhere to recipe conditions, then the system can operate with simple measurement and control mechanisms, but the final product specifications exhibit great variability and the system cannot proactively compensate for disturbances
Solution Approach 1:
The patent applies preliminary action by using feedforward control to proactively compensate for disturbances before they affect the final product. The control system predicts the impact of disturbances on product quality and adjusts process conditions in advance, rather than reacting after deviations occur. This is achieved through a control algorithm that calculates compensation based on measured disturbances and their known relationship to product quality outcomes.
Solution Approach 2:
The patent combines feedback control with feedforward control in a hybrid approach. While maintaining basic feedback mechanisms to adhere to recipe conditions, the system adds a feedforward component that uses measurements of disturbances (such as material properties or environmental conditions) to proactively adjust process parameters. This dual approach reduces product variability without requiring completely complex control architecture.
2Ease of operation
If batch processes use repeated adherence to defined recipe conditions, then the control system remains simple and easy to operate, but the system cannot adapt to incoming disturbances and shows high variability between batches
Solution Approach 1:
The system performs preliminary compensation for disturbances by measuring key input variables and pre-calculating the necessary adjustments to maintain product quality. This allows the control system to adapt to disturbances while maintaining a relatively simple operational interface, as the complex calculations are performed automatically by the control algorithm without requiring operator intervention.
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting process parameters based on measured disturbances. The control algorithm modifies recipe conditions in real-time based on the relationship between disturbance parameters and product quality, allowing the system to adapt to varying batch conditions while maintaining ease of operation through automated parameter adjustment.
3Manufacturing precision
If advanced control algorithms are implemented to predict and control final product properties, then product variability decreases and desired specifications are achieved, but the control system complexity increases significantly
Solution Approach 1:
The patent uses an intermediary approach by introducing a control algorithm that acts as a mediator between simple measurements and complex control decisions. The algorithm uses a mathematical model to predict the relationship between process conditions and final product properties, allowing the system to achieve precise quality control without requiring direct complex control of all process variables. This intermediary model simplifies the control architecture while maintaining high manufacturing precision.
Data Source
AI summary
A method for batch control in a system. The system comprises at least two batch processing sets that share at least one shared equipment. A batch is initiated in each processing set. Process variables from each batch are monitored. At least one process variable from at least one batch are adjusted using bang-bang control to prevent conflicts.