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In automated production process control, the problematic situation is the lack of effective methods for data processing considering low quality of materials, improper connection of components and other process non-conformances, as well as equipment imperfection, its depreciation and incorrect settings, errors in the design of microcircuits and other components of microelectronics. In this work, the approaches to data processing in process control are considered that have regard to relationships between various local factors of production state, including those leading to defects in manufactured products. Particular attention is paid to the intelligent analysis of accumulated data on the state of the external production environment, actuators and mechanisms when a defect occurs and is detected. A mathematical model of a defect with an ordered set of its characteristics and their values is given. An ensemble of neural networks has been used to process the data of the output quality control of products, which allows building prognostic models of production state and determining critical factors that affect the global production technological processes. Criteria are given for determining the level of identified factor’s effect on production state. The resulting prognostic model allows determining the standards for measuring the state and forming a control action for its correction.

Key words: output quality control, process control, prognostic modeling, production state
Published in: INFORMATION-COMMUNICATION TECHNOLOGIES
Bibliography link: Shevnina Yu. S., Khvostik P. M., Zaitsev V. V., Vinokurov A. A., Portnov E. M.Predictive modeling of defects in microelectronics products based on neural network ensembles. Izv.vuzov. Elektronika = Proc. Univ. Electronics. 2025;30(4):487–496. (InRuss.).https://doi.org/10.24151/1561-5405-2025-30-4-487-496.
Financial source: the work has been supported by the Russian Science Foundation (project no. 24-29-00530).

Yulia S. Shevnina
National Research University of Electronic Technology (Russia, 124498, Moscow, Zelenograd, Shokin sq., 1)

Pavel M. Khvostik
National Research University of Electronic Technology (Russia, 124498, Moscow, Zelenograd, Shokin sq., 1)

Vladimir V. Zaitsev
National Research University of Electronic Technology (Russia, 124498, Moscow, Zelenograd, Shokin sq., 1)

Alexey A. Vinokurov
National Research University of Electronic Technology (Russia, 124498, Moscow, Zelenograd, Shokin sq., 1)

Evgeniy M. Portnov
National Research University of Electronic Technology (Russia, 124498, Moscow, Zelenograd, Shokin sq., 1)

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Information about the publication

UDK: 004.942.032.26
Publication type: Scientific article
Source lang: Russian
DOI: 10.24151/1561-5405-2025-30-4-487-496
RISC id: EFNACX

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