PI Parameter Optimization for Pressure-Based MFC Using Gaussian Mixture Model

A vast number of mass flow controllers (MFCs) are used in semiconductor industry. An efficient production method of MFC is required. The gain tuning of the proportional-integral (PI) control to realize a setting flow rate is essential for efficient mass production. The gains are tuned to meet the sp...

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Bibliographic Details
Published in2024 SICE Festival with Annual Conference (SICE FES) pp. 914 - 917
Main Authors Ueda, Takayuki, Higuchi, Seiji, Takijiri, Kotaro, Hayashi, Daisuke
Format Conference Proceeding
LanguageEnglish
Published The Society of Instrument and Control Engineers - SICE 27.08.2024
Subjects
Gaussian mixture mode
Gaussian mixture model
Iron
Manufacturing
Manufacturing processes
Mass flow controller
Mass production
Optimization
PI control
Production
Semiconductor
Statistical analysis
Time factors
Tuning
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Summary:A vast number of mass flow controllers (MFCs) are used in semiconductor industry. An efficient production method of MFC is required. The gain tuning of the proportional-integral (PI) control to realize a setting flow rate is essential for efficient mass production. The gains are tuned to meet the specifications required for evaluation indices of response time and overshoot amount in a step response waveform. In this paper, we propose a simple method for the PI gain tuning using the Gaussian Mixture Model (GMM) and the direct inverse analysis applicable to the pressure-based MFCs' production. The relationship between the gains and evaluation indices for a standard unit of the MFC is modeled as the GMM. The direct inverse analysis calculates the difference between the standard and a test unit. Under the assumption that the difference can be compensated by a simple shift, gains likely to meet the specifications for the test unit are searched. We applied the method to seven test units. The result showed that the gains of all the test units were tuned within only a few iterations.