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Computational and Monte-Carlo Aspects of Systems for Monitoring Reliability Data

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Proceedings of COMPSTAT'2010

Abstract

Monitoring plays a key role in today’s business environment, as large volumes of data are collected and processed on a regular basis. Ability to detect onset of new data regimes and patterns quickly is considered an important competitive advantage. Of special importance is the area of monitoring product reliability, where timely detection of unfavorable trends typically offers considerable opportunities of cost avoidance. We will discuss detection systems for reliability issues built by combining Monte-Carlo techniques with modern statistical methods rooted in the theory of Sequential Analysis, Change-point theory and Likelihood Ratio tests. We will illustrate applications of these methods in computer industry.

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Author information

Authors and Affiliations

  1. IBM, Thomas J. Watson Research Ctr., Box 218, Yorktown Heights, NY, 10598, USA

    Emmanuel Yashchin

Authors
  1. Emmanuel Yashchin
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Correspondence to Emmanuel Yashchin .

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Editors and Affiliations

  1. Centre de Recherche INRIA Paris-Rocquenc, Domaine de Voluceau, Le Chesnay cedex, 78153, France

    Yves Lechevallier

  2. , chaire de statistique appliquée, CNAM, rue Saint Martin 292, Paris, 75003, France

    Gilbert Saporta

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Yashchin, E. (2010). Computational and Monte-Carlo Aspects of Systems for Monitoring Reliability Data. In: Lechevallier, Y., Saporta, G. (eds) Proceedings of COMPSTAT'2010. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2604-3_23

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