Analyzing Process Concept Drifts Based on Sensor Event Streams During Runtime

Analyzing Process Concept Drifts Based on Sensor Event Streams During Runtime

Abstract

Business processes have to adapt to constantly changing requirements at a large scale due to, e.g., new regulations, and at a smaller scale due to, e.g., deviations in sensor event streams such as warehouse temperature in manufacturing or blood pressure in health care. Deviations in the process behavior during runtime can be detected from process event streams as so called concept drifts. Existing work has focused on concept drift detection so far, but has neglected why the drift occurred. To close this gap, this paper provides online algorithms to analyze the root cause for a concept drift using sensor event streams. These streams are typically gathered externally, i.e., separated from the process exe-cution, and can be understood as time sequences. Supporting domain experts in assessing concept drifts through their root cause facilitates process optimization and evolution. The feasibility of the algorithms is shown based on a prototypical implementation. Moreover, the algorithms are evaluated based on a real-world data set from manufacturing.

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Authors
  • Stertz, Florian
  • Mangler, Jürgen
  • Rinderle-Ma, Stefanie
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Shortfacts
Category
Paper in Conference Proceedings or in Workshop Proceedings (Paper)
Event Title
18th Int. Conference on Business Process Management (BPM 2020)
Divisions
Workflow Systems and Technology
Event Location
Sevilla, Spain
Event Type
Conference
Event Dates
September
Series Name
International Conference on Business Process Management
ISSN/ISBN
LNCS 12168
Page Range
pp. 202-2019
Date
2020
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