Fabrication Process Stochastic Model for Yield Estimation in Microwave Semiconductor Devices Production

• Published in: Journal of Engineering Vol. 2022; pp. 1 - 7
• Main Authors: Paszkiewicz, Bartlomiej K., Paszkiewicz, Bogdan, Dziedzic, Andrzej
• Format: Journal Article
• Language: English
• Published: Cairo Hindawi 29.04.2022; John Wiley & Sons, Inc; Wiley
• Subjects: Aluminum gallium nitrides; Big Data; Gallium nitrides; High electron mobility transistors; Manufacturing; Methodology; Modelling; Organic chemicals; Probability distribution; Process parameters; R&D; Random variables; Research & development; Semiconductor devices; Simulation; Stochastic models; Transistors
• ISSN: 2314-4904; 2314-4912; 2314-4912
• DOI: 10.1155/2022/5561059

This paper presents a new methodology for simulation of production processes in order to determine device parametric yield. The elaborated methodology is focused on capturing stochastic relations between every parameter of the subsequent processes that are impossible to determine directly. The current state-of-the-art together with the gaps in the knowledge regarding yield modelling is presented. A novel approach to the important issue of effective yield modelling that allows the overcoming of current challenges is presented. The methodology’s usefulness is validated with the example of the fabrication process of AlGaN/GaN HEMT (high electron mobility transistor) for application in high-frequency electronics. Fabrication of AlGaN/GaN HEMTs is a complex process due to the large number of technological stages required, most of which are still the subject of ongoing research. Most importantly, the approach presented in this paper could be easily applied to the modelling of any complex production process in every case where it is necessary to examine relations between the final product parameters distribution and the values of the involved process parameters.