| Title |
Funkcinio testavimo efektyvumas elektronikos pramonėje |
| Translation of Title |
Efficiency of functional testing in electronics industry. |
| Authors |
Mendelis, Dominykas |
| Full Text |
|
| Pages |
64 |
| Keywords [eng] |
functional testing ; machine learning ; anomaly detection ; electronics manufacturing ; test efficiency. |
| Abstract [eng] |
Functional testing is essential for ensuring the quality and reliability of electronic devices before they are released to consumers. As electronic components become more complex, making functional testing more efficient is becoming an increasingly important challenge for Electronics Manufacturing Services. This research peers to achieve higher efficiency by using modern technologies like big data analytics, machine learning and neural networks. It examines different testing approaches, analyses key factors such as first pass yield and test cycle time and explores how predictive analytics can help spot and fix testing inefficiencies. Final work also proposes a starting framework for incorporating modern algorithms into testing process to reduce execution time, minimize false failures and boost overall production quality. Findings show that using AI-driven techniques can possibly greatly improve testing accuracy and efficiency, which would lead to lower costs and higher yields in electronics manufacturing industry. |
| Dissertation Institution |
Kauno technologijos universitetas. |
| Type |
Master thesis |
| Language |
Lithuanian |
| Publication date |
2025 |
