Instance-Based APC Limits for Operating Mode Changes
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Solution Overview
Problem
Industrial process control systems often operate with fixed control limits, which can lead to inefficiencies as they fail to adapt to dynamic changes in operating modes, resulting in suboptimal performance and potential disruptions between processes in industrial facilities.
Innovation Solution
An IoT platform utilizing instance-based learning to compare current operating conditions with historical data, providing real-time insights and adjustments to optimize process control limits and settings, thereby enabling adaptive and efficient operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fixed control limits are used for industrial assets and processes, then the control system is simple and stable, but the industrial assets and processes are operated in an inefficient manner
Solution Approach 1:
The patent implements dynamic control limits that automatically adjust based on detected operating modes. The system transitions from static fixed limits to dynamic adaptive limits that change according to the current operating conditions, resolving the contradiction between simplicity and adaptability.
Solution Approach 2:
The system changes the parameter of control limits from fixed values to variable values that depend on operating mode. By detecting operating mode changes and adjusting control limits accordingly, the system achieves both efficiency improvement and adaptability.
2Adaptability or versatility
If fixed control limits are used, then the control system is easy to operate, but it fails to adapt to dynamic changes in operating modes
Solution Approach 1:
The system performs self-adjustment by automatically detecting operating mode changes and modifying control limits without human intervention. This self-service capability adds adaptability while keeping operation simple, as the system handles the complexity internally.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor operating conditions and use this information to adjust control limits. The feedback loop enables automatic adaptation to changing operating modes while maintaining ease of operation through automated decision-making.
3Productivity
If fixed control limits are used, then the control system requires minimal computational resources, but results in suboptimal performance and potential disruptions
Solution Approach 1:
The system dynamically adjusts control limits based on operating modes, improving throughput and performance. The computational energy is optimized by only performing adjustments when operating mode changes are detected, rather than continuous computation.
Data Source
AI summary
Various embodiments described herein relate to advanced process control for assets and/or processes using instance-based learning. In this regard, an event indicator related to a change event associated with operation of an asset is received. In response to the event indicator, one or more insights for one or more real-time settings for the asset are determined based at least in part on a comparison between a current operating condition digital signature for the asset and historical operating condition digital signature for the asset. Additionally, the one or more real-time settings for the asset are adjusted based on the one or more insights to provide one or more adjusted settings for the asset.