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Activity Number: 643 - Detection of Changes and Structural Breaks in Business and Industrial Data Streams
Type: Topic Contributed
Date/Time: Thursday, August 1, 2019 : 10:30 AM to 12:20 PM
Sponsor: Quality and Productivity Section
Abstract #304997
Title: Change Detection for Multi-Stage Multivariate Data
Author(s): Emmanuel Yashchin*
Companies: IBM Research
Keywords: Detection; Monitoring; Quality Control; Search Engine; Statistical Process Control
Abstract:

We consider early warning systems (EWS) for monitoring multi-stage data, in which downstream variables undergo changes associated with upstream process stages. In such applications, timeslides are typically useful for both monitoring and diagnostics. A timeslide is a set of observations that is ordered in accordance with product passage time through a given stage. In this paper, we discuss using timeslides in multivariate methodology for detecting unfavorable changes in downstream variables. We illustrate the methodology using examples from electronic industry.


Authors who are presenting talks have a * after their name.

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