An Intelligent Optimization System Using Neural Networks and Soft Computing for the FMM Etching Process

The rapid rise of flexible AMOLED displays has prompted manufacturers to advance technologies to meet growing global demand. However, high costs and quality inconsistencies hinder industry competitiveness and sustainability. This study addresses these challenges by developing an intelligent optimiza...

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Vydáno v:Mathematics (Basel) Ročník 13; číslo 13; s. 2050
Hlavní autoři: Chen, Wen-Chin, Ngo, An-Xuan, Zhong, Jun-Fu
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.07.2025
Témata:
Active matrix displays
Algorithms
AMOLED
Automation
Back propagation networks
BPNN
Design
Efficiency
Environmental sustainability
Etching
etching process
FMM
Genetic algorithms
Manufacturing
Mathematical optimization
Mutation
Neural networks
Optimization
Organic light emitting diodes
Parameter identification
Particle swarm optimization
Process controls
Process parameters
Product quality
Production costs
Production processes
Propagation
PSO-GA
Soft computing
Taguchi method
Taguchi methods
Variance analysis
ISSN:2227-7390, 2227-7390
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Shrnutí:The rapid rise of flexible AMOLED displays has prompted manufacturers to advance technologies to meet growing global demand. However, high costs and quality inconsistencies hinder industry competitiveness and sustainability. This study addresses these challenges by developing an intelligent optimization system for the fine metal mask (FMM) etching process, a critical step in producing high-resolution AMOLED panels. The system integrates advanced optimization techniques, including the Taguchi method, analysis of variance (ANOVA), back-propagation neural network (BPNN), and a hybrid particle swarm optimization–genetic algorithm (PSO-GA) approach to identify optimal process parameters. Experimental results demonstrate a marked improvement in product yield and process stability while reducing manufacturing costs. By ensuring consistent quality and efficiency, this system overcomes limitations of traditional process control; strengthens the AMOLED industry’s global competitiveness; and provides a scalable, sustainable solution for smart manufacturing in next-generation display technologies.
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ISSN:2227-7390
2227-7390
DOI:10.3390/math13132050