Multi-Variable Process Control Using Inner Envelope Optimization
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Solution Overview
Problem
Existing methods for operating controllable multi-variable processes struggle to achieve improved performance by effectively utilizing historical data to adjust process variables within defined operational envelopes, leading to potential alarm conditions and suboptimal results.
Innovation Solution
A method and system that derive a multi-dimensional display representation using parallel coordinate axes, where historical data points are used to create both an outer and inner envelope, allowing for real-time adjustments of process variables to maintain operation within the inner envelope, thereby achieving target values and minimizing alarm conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If historical data is used to define operational envelopes for process control, then process reliability is improved, but device complexity increases due to the need for multi-dimensional display representations and envelope calculations
Solution Approach 1:
The operational envelope is segmented into multiple zones (outer envelope, inner envelope, and target zones) that represent different levels of process performance. This segmentation allows the system to provide graded guidance rather than a single complex control rule, improving reliability while managing complexity through hierarchical structure.
Solution Approach 2:
The patent uses multi-dimensional display representations where process variables are plotted across multiple axes simultaneously. This dimensional approach transforms complex multi-variable relationships into visual spatial representations, making the control system more intuitive and manageable despite the underlying complexity.
2Manufacturing precision
If the inner envelope is used to constrain process variables to achieve target values, then manufacturing precision is improved, but ease of operation deteriorates due to tighter constraints and more frequent adjustments
Solution Approach 1:
The system pre-calculates the inner envelope and target zones based on historical data before actual process operation. This preliminary action provides operators with pre-defined guidance boundaries, reducing the cognitive load during operation while maintaining precision requirements.
Solution Approach 2:
The system continuously monitors process variables against the inner envelope boundaries and provides feedback to operators. This real-time feedback mechanism guides operators back within acceptable limits, maintaining manufacturing precision while simplifying operation through automated monitoring and alerting.
3Productivity
If real-time monitoring and adjustment of process variables is implemented, then productivity is improved through optimized operation, but loss of time increases due to the time required for monitoring and making adjustments
Solution Approach 1:
The system automatically monitors process variables and calculates envelope violations without requiring continuous manual intervention. The automated monitoring reduces the time burden on operators while maintaining productivity benefits through continuous optimization guidance.
Solution Approach 2:
The system focuses monitoring and adjustment efforts on the most critical variables that violate the inner envelope, rather than requiring equal attention to all variables. This partial action approach optimizes productivity by concentrating resources on high-impact areas while reducing overall monitoring time.
Data Source
AI summary
Controlling a multi-variable process involves multi-dimensional representation of the values (Qa-Qh) of the process-variables (a-h) according to individual coordinate axes (Xa-Xh), and response based on historical values for the process-variables accumulated from multiple, earlier processes. An envelope (UL-LL) showing the best operating zone (‘BOZ’) for each process variable based on current values of the other variables is calculated from the accumulated historical values, and alarm conditions in which the current value of a variable lies outside the BOZ is rectified by changing the values (Qa-Qc) of manipulatable variables (a-c). Variable targets are achieved, alarms rectified and value optimisation realised using an inner envelope (UI-LI) derived from a subset of the BOZ-defining set of historical values. Where the alarm rate is low, operation is improved by narrowing the BOZ set to tighten the BOZ envelope (UL-LL) reducing an inner envelope where alarm rate remains acceptable, as a new BOZ.