Industrial-Grade Time-Dependent Counterfactual Root Cause Analysis through the Unanticipated Point of Incipient Failure: a Proof of Concept
Not on the map. Why?
Abstract (arXiv)
This paper describes the development of a counterfactual Root Cause Analysis diagnosis approach for an industrial multivariate time series environment. It drives the attention toward the Point of Incipient Failure, which is the moment in time when the anomalous behavior is first observed, and where the root cause is assumed to be found before the issue propagates. The paper presents the elementary but essential concepts of the solution and illustrates them experimentally on a simulated setting. Finally, it discusses avenues of improvement for the maturity of the causal technology to meet the robustness challenges of increasingly complex environments in the industry.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 40 references that are in the map. First posted on arXiv 10 Jul 2024.
Builds on
7 of 40 references.
References · 7
- 2017Detecting causal associations in large nonlinear time series datasetscited by 240
- 2019Causal structure based root cause analysis of outlierscited by 65
- 2020Potential, Challenges and Future Directions for Deep Learning in Prognostics and Health Management Applicationscited by 63
- 2022Causal Inference-Based Root Cause Analysis for Online Service Systems with Intervention Recognitioncited by 55
- 2023Root Cause Identification for Collective Anomalies in Time Series given an Acyclic Summary Causal Graph with Loopscited by 30
- 2022A Causal Approach to Detecting Multivariate Time-series Anomalies and Root Causescited by 8
- 2022On Root Cause Localization and Anomaly Mitigation through Causal Inferencecited by 6
Built on by
Not cited yet.