Batch Process Control Using Similar Successful Trajectories
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Industrial processes for producing chemical, pharmaceutical, or biotechnological products face challenges in controlling and monitoring due to multivariate behavior, especially in batch processes where multiple variables interact, leading to complexity in measurement and control, particularly when scaling up or using expensive ingredients.
Innovation Solution
A computer-implemented method using a cloud-based database to store and retrieve process parameters, allowing for the identification of similar successful trajectories for controlling and monitoring processes, employing multivariate analysis to adjust parameters in real-time based on recorded measurements and comparing them to stored successful processes to ensure product quality attributes are met.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple batches are produced on the same equipment with different scales and operating conditions, then productivity increases, but process control complexity increases
Solution Approach 1:
The patent segments the complex multivariate process into multiple independent batches, each with its own parameter set. By treating each batch as a separate controllable unit with defined start and end points, the system can manage complexity through temporal segmentation rather than simultaneous control of all parameters across all batches.
Solution Approach 2:
The system performs preliminary actions by pre-defining parameter ranges and constraints for each batch before execution. The multivariate analysis framework is prepared in advance to evaluate parameter combinations, allowing the control system to anticipate and prevent control issues before they arise during actual batch processing.
2Manufacturing precision
If process parameters are adjusted in real-time to meet quality attributes, then product quality improves, but measurement and control challenges increase
Solution Approach 1:
The patent implements continuous feedback loops where process parameters are monitored in real-time, compared against target ranges derived from multivariate analysis, and adjusted accordingly. The system uses measured parameter values to update the multivariate model, which then provides feedback for optimizing subsequent measurements and control actions to maintain product quality.
Solution Approach 2:
The system dynamically changes parameter ranges and constraints based on the current batch context and multivariate analysis results. Rather than using fixed parameter specifications, the system adapts parameter targets and acceptable variations according to the specific operating conditions and interactions identified through multivariate modeling, enabling precise quality control in complex multivariate environments.
3Manufacturing precision
If expensive ingredients are used in batch processing, then product quality improves, but waste reduction becomes more critical
Solution Approach 1:
The patent applies dynamic parameter adjustment throughout the batch process based on real-time measurements and multivariate analysis. By continuously adapting parameter targets and constraints according to actual process behavior and ingredient consumption patterns, the system optimizes ingredient utilization to minimize waste while maintaining product quality attributes.
Solution Approach 2:
The multivariate analysis system automatically identifies and corrects parameter deviations that could lead to ingredient waste or quality failures. The system serves itself by using its own measurement data to update models and adjust control parameters, enabling autonomous optimization of ingredient usage without external intervention, thereby reducing waste of expensive materials.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A computer system and computer-implemented method are described for controlling and monitoring a process to produce a chemical, pharmaceutical or biotechnological product, the method comprising: providing a database, the database storing sets of process parameters to control and monitor respective ones of a plurality of processes performed in order to produce products, wherein each of the stored sets of process parameters is associated with a successful trajectory of a respective one of the processes performed according to the respective set process parameters, wherein each successful trajectory is a time-based profile of measurements recorded during performance of the respective process; receiving a set of characterizing process parameters that characterize the process; identifying a first set process parameters from the stored sets of process parameters, the first set of process parameters having a specified degree of similarity to the set of characterizing process parameters, wherein the first set of process parameters is associated with a first successful trajectory, controlling and monitoring the process using the first successful trajectory, comprising: recording measurements of the process; estimating a trajectory of the process based on the recorded measurements.