These results demonstrate that ML-based predictive analytics can significantly improve process efficiency, minimize unnecessary retesting, reduce tester load, and accelerate production throughput without compromising product quality. This study aimed to enhance the optical module manufacturing process using Machine Learning (ML) by enabling early defect detection. The traditional step-by-step testing workflow (OPA, LOPT, OTSM, and OSET) results in excessive retesting cycles, increasing production time, and reducing overall. delays in high-volume manufacturing settings. Identification of failure units rem ineffective. ML. Optical modules are key transmission components in communication networks, and their applications, technologies, types, and terminology are diverse. We at LSOLINK are a manufacturer dedicated to providing one-stop optical network solutions for high-performance computing, data. As optical modules are employed for high-speed data transmission and optoelectronic conversion, the manufacturing quality of their PCBs directly impacts the performance, stability, and reliability of the optical modules.
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