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Study mode:
on
1
Intro
2
Bottom Line Up Front
3
Motivation
4
Overview of Example Industrial Process
5
Resources from plant
6
Simplified Process Diagram (DCS)
7
Industrial Database
8
Understanding the Data
9
Data Collection Points Control Loops
10
Temporal Alignment Problem: Establishing Truth is Difficult!
11
Variability Challenges in Establishing Ground Truth
12
Machine Learning
13
Supervised learning for tracing sources of variability
14
Further Correlation Analysis
15
Behavior Based Event Detection System for Industrial Facilities
16
Advantage over Current State of the Art
17
Overview of Toolkit Flow
18
Feature Selection
19
The Cluster Tuning Algorithm
20
The K-Means Algorithm
21
Threshold Optimization
22
GUI FOR Cluster Tuning
23
Operator in the Loop
24
State of Health Assessment
25
Characterizing Operator Response
26
Conclusion
Description:
Explore a comprehensive analysis of industrial process monitoring and optimization in this BSidesLV 2014 conference talk. Delve into the complexities of data collection, control loops, and temporal alignment challenges in industrial settings. Learn about machine learning applications for tracing variability sources and behavior-based event detection systems. Discover innovative approaches to feature selection, cluster tuning, and threshold optimization. Gain insights into operator response characterization and state of health assessment techniques. Understand how these advanced methodologies can enhance industrial facility operations and security.

Know Thy Operator: Behavior-Based Event Detection in Industrial Facilities

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