Mass Flow Controller Dual-Mode PID for Low-Latency Flow Stability
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Solution Overview
Problem
Traditional mass flow controllers (MFCs) face challenges with latency in achieving desired flow rates due to continuous PID control loop adjustments, leading to reduced throughput, efficiency, increased wear, and instability in industrial processes like ALD and ALE.
Innovation Solution
A dual-mode PID control loop system with a training mode to establish solenoid coil current setpoints and an inference mode for real-time flow rate monitoring, using a learning engine to optimize fluid flow regulation and stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous PID control loop adjustments are used to regulate fluid flow, then flow rate control is achieved, but latency in achieving desired flow rates increases
Solution Approach 1:
The system performs preliminary action by pre-calculating and storing optimal solenoid coil current setpoints for various operating states during a training mode before actual process execution. This allows the MFC to rapidly switch between pre-determined settings without requiring continuous real-time PID adjustments, thereby reducing latency while maintaining precise flow rate control.
2Measurement precision
If continuous PID control loop operation is used to regulate fluid flow, then flow rate accuracy is maintained, but wear and tear on system components increases
Solution Approach 1:
The invention extracts the continuous adjustment function from the PID control loop and replaces it with discrete pre-determined setpoints stored in memory. By taking out the continuous operation requirement and substituting it with rapid switching between stored values, the system maintains flow rate accuracy while significantly reducing continuous component wear and improving reliability.
3Ease of operation
If traditional MFC operation is used, then fluid flow control is achieved, but stability and drift monitoring capability is insufficient
Solution Approach 1:
The system implements feedback by continuously monitoring flow rates during inference mode and comparing actual performance against expected values. The Statistical Process Control mechanisms provide ongoing feedback to detect drift and instability, triggering retraining events when deviations are detected, thereby maintaining long-term flow rate stability and operational consistency.
4Productivity
If rapid flow rate adjustments are required for process efficiency, then throughput improves, but control precision may be compromised
Solution Approach 1:
The system resolves this contradiction by performing preliminary action during training mode to pre-determine optimal current setpoints for various operating states. During actual process execution, the MFC rapidly switches between these pre-calculated settings, achieving both high throughput through fast switching and high precision because each setpoint was optimized during training to deliver accurate flow rates.
Data Source
AI summary
This invention disclosure presents a mass flow controller (MFC) with a dual-mode proportional-integral-derivative (PID) control loop. In training mode, the PID loop determines solenoid coil current setpoints for various operating states stipulated by a process recipe, storing them for later retrieval. During the execution of a semiconductor manufacturing process, the stored setpoints enable rapid flow delivery without continuous PID control. Real-time flow rate monitoring and Statistical Process Control (SPC) ensure stability, triggering retraining if necessary, enhancing MFC speed, accuracy, and reliability.