Optimizing semiconductor processing open tube furnace performance: comparative analysis of PI and Mamdani fuzzy-PI controllers

Wesley Beccaro (), Carlos A. S. Ramos and Silvio X. Duarte
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Wesley Beccaro: University of São Paulo (USP)
Carlos A. S. Ramos: University of São Paulo (USP)
Silvio X. Duarte: Centro Universitário FEI

Journal of Intelligent Manufacturing, 2023, vol. 34, issue 7, No 9, 3015-3024

Abstract: Abstract High-temperature open tube furnaces are essential in semiconductor manufacturing process. This type of equipment requires periodic servicing for operational longevity and to comply with the requirements of microelectronics processes. This paper presents a comparative analysis of Proportional–Integral (PI) and Fuzzy-PI algorithms for controlling a three-zone open tube furnace. Initially, the furnace was identified using an AutoRegressive eXogenous (ARX) model. The model was tested using a cross-validation method with 10-steps-ahead prediction tests. The prediction showed results higher than 93.70% with Final Prediction Error (FPE) lower than 0.0007. The controllers were simulated and their parameters were tuned using the identified model. The tuned algorithms were implemented through a PC-based instrumentation in real-time. The Fuzzy-PI controller presented the best results regarding the steady-state error, controlling the temperature of the furnace with a variation less than $$\pm 1.06~^{\circ }\mathrm{C}$$ ± 1.06 ∘ C in the flat zone at the process temperature of $$900~^{\circ }\mathrm{C}$$ 900 ∘ C with fast settling time. This innovative result presents a major step toward the modernization of high-temperature furnaces to meet the growing demands in the electronics industry.

Keywords: Semiconductor manufacturing; Process control; Intelligent manufacturing; PID; Temperature control; Fuzzy logic controller (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10845-022-01993-2

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