The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Outlier screening is a popular approach employed for automotive product lines. There have been many outlier methods proposed. In practice, it is desirable to choose the “best” outlier method. This work develops a notion of applicability associated with an outlier method on a given set of wafers. A measure for applicability is proposed and experiment results are presented to illustrate its effects...
An analytics process is subjective to the perspective of the analyst. This paper presents a learning approach that models the process of how an analyst conducts analytics. The approach is applied in the context of correlation analysis for production yield optimization. The benefit is demonstrated by showing that learning from resolving a yield issue for one automotive product line can help resolve...
Feature selection is essential to rule learning in the context of functional verification. In practice today, features are selected manually and the selection requires domain knowledge. In contrast, this work proposes using automatic feature extraction from design documents as a viable approach to support rule learning. To demonstrate its effectiveness, document-extracted features are employed to...
Outlier screening is a popular approach for testing automotive products. In practice, developing an outlier model can be subjective, making justification of the model challenging. In this paper we propose a new concept called Consistency which provides a data-driven objective way to assess an outlier model. We study the development of outlier models in view of this new model consistency concept and...
In this work, we study the generalization of an outlier model from two perspectives, temporal and spatial. We show that model generalization with existing distribution-based outlier analysis methods can vary significantly. We then propose a “big data” outlier analysis approach together with a probability-based outlier evaluation for improving model generalization. Experiments are conducted based on...
This work presents a novel yield optimization methodology based on establishing a strong correlation between a group of fails and an adjustable process parameter. The core of the methodology comprises three advanced statistical correlation methods. The first method performs multivariate correlation analysis to uncover linear correlation relationships between groups of fails and measurements of a process...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.