Hanyang University · Engineering
Professor Suk Joo Bae's research lab specializes in reliability engineering and statistical modeling, with a focus on degradation analysis in electronic and microelectronic systems. The lab develops advanced nonlinear and random-coefficient models—such as change-point, bi-exponential, and logistic mixture models—to capture complex degradation behaviors in devices like plasma display panels, IC wafers, and MOS transistors. A key emphasis is on improving reliability estimation and yield prediction by integrating spatial, temporal, and contamination-related factors into statistical frameworks. The lab also applies these models to public health data, as seen in meta-analytical studies on malaria prevalence.
Figures are computed from collected data and may differ slightly.
AbstractAs an alternative to traditional life testing, degradation tests can be effective in assessing product reliability when measurements of degradation leading to failure can be observed. This article presents a degradation model for highly reliable light displays, such as plasma display panels and vacuum fluorescent displays (VFDs). Standard degradation models fail to capture the burn-in characteristics of VFDs, when emitted light actually increases up to a certain point in time before it d
In testing display devices such as Plasma Display Panels (PDPs), the observed degradation in luminosity can exhibit an unstable period due to incomplete burn-in during the manufacturing process. We introduce a log-linear model with random coefficients and a change point to describe the nonlinear degradation path. The change point represents the time at which the burn-in period has finished and the degradation in the luminosity changes to a slower and more stable rate. The inference procedure for
Malaria is one of the major public health issues globally. Malaria infection spreads through mosquito bites from infected female Anopheles mosquitoes. This study aims to conduct a systematic review and meta-analysis on malaria prevalence in Pakistan from 2006 to 2021. We searched PubMed, Science Direct, EMBASE, EMCare, and Google Scholar to acquire data on the prevalence of malaria infections. We performed a meta-analysis with a random-effects model to obtain the pooled prevalence of malaria, Pl
As an alternative to traditional life testing, degradation tests can be effective in assessing product reliability when measurements of degradation leading to failure can be observed. This article proposes a new model to describe the nonlinear degradation paths caused by nano-contamination in plasma display panels (PDP): a bi-exponential model with random coefficients. A likelihood ratio test was sequentially executed to select random effects in the nonlinear model. Analysis results indicate tha
In this paper we propose spatial modeling approaches for clustered defects observed using an Integrated Circuit (IC) wafer map. We use the spatial location of each IC chip on the wafer as a covariate for the corresponding defect count listed in the wafer map. Our models are based on a Poisson regression, a negative binomial regression, and Zero-Inflated Poisson (ZIP) regression. Analysis results indicate that yield prediction can be greatly improved by capturing the spatial distribution of defec
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