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on
1
Intro
2
Motivation
3
Overview of Example Industrial Process
4
Resources from plant
5
Simplified Process Diagram (DCS)
6
Industrial Database
7
Understanding the Data
8
Data Collection Points (Control Loops)
9
Temporal Alignment Problem
10
Variability Challenges in Establishing Ground Truth
11
Machine Learning
12
Supervised learning for tracing sources of variability
13
Further Correlation Analysis
14
Behavior Based Event Detection System for Industrial Facilities
15
Advantage over Current State of the Art
16
Overview of Toolkit Flow
17
Feature Selection
18
The Cluster Tuning Algorithm
19
The K-Means Algorithm
20
Threshold Optimization
21
GUI FOR Cluster Tuning
22
Operator in the Loop
23
State of Health Assessment
24
Conclusion
Description:
Explore the concept of ground truth in industrial processes through this 38-minute BSidesLV conference talk. Delve into the challenges of establishing accurate baselines in complex industrial environments, including temporal alignment issues and variability factors. Learn about machine learning techniques for tracing sources of variability and implementing behavior-based event detection systems. Discover the advantages of these advanced methods over traditional approaches. Gain insights into toolkit flow, feature selection, cluster tuning algorithms, and state of health assessments. Understand how to optimize thresholds and incorporate operator expertise into the process. Enhance your knowledge of industrial data analysis and process optimization techniques.

Know Thy Operator

BSidesLV
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