Automatic Control Loop Searching for Data Discovery
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Solution Overview
Problem
Current automation approaches are deterministic and lack the ability to autonomously discover additional data relevant for performance improvement and efficiency, relying on manual setup and limited scope, which is expensive and ineffective.
Innovation Solution
The Automatic Control Loop Searching (ACLS) system creates a search model to detect patterns in control loop data, collect and label additional data, and correlate results, enabling ongoing data-driven optimization without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual setup and analysis is performed for control loop data collection, then data relevance for machine learning can be achieved, but considerable additional effort and planning are required and the process is expensive
Solution Approach 1:
The system enables automated self-service through the ACLS system that autonomously searches for, collects, and labels additional data from control loop executions without requiring manual setup or analysis, thereby achieving data relevance while eliminating considerable manual effort and time
Solution Approach 2:
The system implements feedback mechanisms where the ACLS system continuously monitors control loop executions, detects search patterns in output data, and automatically adjusts data collection strategies based on identified patterns, creating a self-improving loop that reduces manual intervention over time
2Reliability
If manual performance measurements are conducted on an adhoc basis, then some performance evaluation can be achieved, but the process is expensive, difficult, and largely ineffective due to limited scope and duration
Solution Approach 1:
The system transforms adhoc manual measurements into continuous automated operations by executing the ACLS system continuously to monitor control loop executions, detect patterns in real-time, and collect data ongoing, thereby achieving reliable performance evaluation with unlimited scope and duration
Solution Approach 2:
The system replaces manual mechanical processes of setup and analysis with automated computational processes where the ACLS system electronically searches, collects, and labels data automatically, eliminating the difficulties and limitations of manual adhoc measurements
3Extent of automation
If current automation approaches are used, then control loops can execute actions with minimal human intervention, but they cannot learn or evaluate themselves to improve their operation
Solution Approach 1:
The system introduces feedback loops where control loop output data is analyzed by the ACLS system to detect patterns, and this information feeds back into improving future executions, enabling the automation to learn and evaluate itself while maintaining autonomous operation
Solution Approach 2:
The system enables self-service capabilities where the control loops automatically generate data that the ACLS system processes to identify improvement opportunities, allowing the automation to serve itself in learning and evaluating its performance without human intervention
4Adaptability or versatility
If repeated customization is performed to improve flexibility, then adaptability can be achieved, but the expense of repeated customization increases
Solution Approach 1:
The system creates a universal ACLS framework that can handle multiple different control loop types and data formats through a single standardized approach, detecting search patterns and collecting data across various contexts without requiring repeated customization, thereby achieving flexibility while eliminating additional expenses
Data Source
AI summary
Concepts and technologies disclosed herein are directed to automated control loop searching (“ACLS”). According to one aspect disclosed herein, an ACLS system can create a search model that provides high-level information regarding what the ACLS system should search for when a search pattern is detected within data that is output from execution of a control loop. The ACLS system can activate a control loop system that executes the control loop to yield the data as output. The ACLS system can detect the search pattern within data, and in response, the ACLS system can execute, based upon the search model, a search of the data. The ACLS system can collect search results of the search and select additional data from the search results.