Estimation of lifetime distributions on 1550-nm DFB laser diodes using Monte-Carlo statistic computations

High performance and high reliability are two of the most important goals driving the penetration of optical transmission into telecommunication systems ranging from 880 nm to 1550 nm. Lifetime prediction defined as the time at which a parameter reaches its maximum acceptable shirt still stays the main result in terms of reliability estimation for a technology. For optoelectronic emissive components, selection tests and life testing are specifically used for reliability evaluation according to Telcordia GR-468 CORE requirements. This approach is based on extrapolation of degradation laws, based on physics of failure and electrical or optical parameters, allowing both strong test time reduction and long-term reliability prediction. Unfortunately, in the case of mature technology, there is a growing complexity to calculate average lifetime and failure rates (FITs) using ageing tests in particular due to extremely low failure rates. For present laser diode technologies, time to failure tend to be 10 6 hours aged under typical conditions (P opt =10 mW and T=80°C). These ageing tests must be performed on more than 100 components aged during 10000 hours mixing different temperatures and drive current conditions conducting to acceleration factors above 300-400. These conditions are high-cost, time consuming and cannot give a complete distribution of times to failure. A new approach consists in use statistic computations to extrapolate lifetime distribution and failure rates in operating conditions from physical parameters of experimental degradation laws. In this paper, Distributed Feedback single mode laser diodes (DFB-LD) used for 1550 nm telecommunication network working at 2.5 Gbit/s transfer rate are studied. Electrical and optical parameters have been measured before and after ageing tests, performed at constant current, according to Telcordia GR-468 requirements. Cumulative failure rates and lifetime distributions are computed using statistic calculations and equations of drift mechanisms versus time fitted from experimental measurements.