Application of Bayes Theory Model to Determine the Optimal Variant of Technological Process for Production of MEMS Components

被引:0
作者
Nevliudov, Igor [1 ]
Khrustalova, Sofiia [1 ]
Chala, Olena [1 ]
Sliusar, Andrii [1 ]
机构
[1] Kharkiv Natl Univ Radio Elect, Dept Comp Integrated Technol Automat & Robot, Kharkiv, Ukraine
来源
2024 IEEE 19TH INTERNATIONAL CONFERENCE ON THE PERSPECTIVE TECHNOLOGIES AND METHODS IN MEMS DESIGN, MEMSTECH 2024 | 2024年
关键词
atomisation; MEMS; component; optimization; product innovation; engineering; manufacturing innovation; technological process;
D O I
10.1109/MEMSTECH63437.2024.10620011
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
a Bayesian model is proposed for determining the optimal variant of the MEMS component manufacturing technological process A software tool has been developed to automate this process Calculations are performed using the proposed models and software.
引用
收藏
页码:24 / 28
页数:5
相关论文
共 15 条
[1]  
Bortnikova V, 2019, INT CONF PERSP TECH, P83, DOI [10.1109/memstech.2019.8817394, 10.1109/MEMSTECH.2019.8817394]
[2]  
Daiki Koizumi, 2023, On the Prediction of a Nonstationary Exponential Distribution Based on Bayes Decision Theory, P193
[3]  
Falkowski MJ, Causality in Control Systems Based on Data-Driven Oscillation Identification
[4]  
Filipenko O, 2019, INT CONF ADV OPTOEL, P371, DOI [10.1109/CAOL46282.2019.9019570, 10.1109/caol46282.2019.9019570]
[5]  
Holovatyy A., 2023, CAD MACHINERY DESIGN, P31
[6]  
Holovatyy A., CAD MACHINERY DESIGN, P26
[7]   A New Hybrid Method for Predicting Recommendations for Collaborative Recommender Systems [J].
Lobur, Mykhaylo ;
Stekh, Yuriy ;
Holovatskyy, Ruslan ;
Kamiska, Maria .
2023 17TH INTERNATIONAL CONFERENCE ON THE EXPERIENCE OF DESIGNING AND APPLICATION OF CAD SYSTEMS, CADSM, 2023,
[8]  
Lyashenko V., 2023, Int. Res. J. Multidiscip. Technovation, V5, P09
[9]  
Nevliudov I., 2023, 2023 IEEE 5 INT C MO, P1, DOI [10.1109/MEES61502.2023.10402532, DOI 10.1109/MEES61502.2023.10402532]
[10]  
Nevliudov I, 2018, INT CONF PERSP TECH, P223, DOI 10.1109/MEMSTECH.2018.8365738