Lifetime Prediction of 1550 nm DFB Laser using Machine learning Techniques

TL;DR

This paper introduces an ANN-based method for predicting the lifetime of 1.55 μm InGaAsP MQW-DFB laser diodes, demonstrating superior accuracy over traditional accelerated aging tests.

Contribution

It presents a novel machine learning approach that improves the accuracy of laser diode lifetime prediction compared to conventional methods.

Findings

ANN method outperforms traditional lifetime projection techniques

Enhanced prediction accuracy for 1.55 μm DFB laser diodes

Potential for improved reliability assessment in laser manufacturing

Abstract

A novel approach based on an artificial neural network (ANN) for lifetime prediction of 1.55 um InGaAsP MQW-DFB laser diodes is presented. It outperforms the conventional lifetime projection using accelerated aging tests.