Asset Capability Limits for Model Predictive Process Control
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Solution Overview
Problem
Industrial processes often operate inefficiently due to fixed limits that are inaccurately configured, leading to disruptions and undesirable operations in industrial facilities, where concatenated processes can negatively impact other processes, resulting in inefficient and suboptimal performance.
Innovation Solution
A system and method that utilize asset modeling data from performance management systems to adjust real-time operating limits and transmit control signals for industrial processes, enabling dynamic optimization and minimizing disruptions through model predictive control and industrial process optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If fixed limits of operation are used for industrial assets, then operational simplicity is maintained, but process efficiency and adaptability deteriorate
Solution Approach 1:
The patent transforms static fixed operating limits into dynamic real-time operating limits that adapt to changing process conditions. The system continuously updates operating limits based on asset performance data, process variables, and predictive models, enabling the control system to respond dynamically to variations in asset capability and process requirements while maintaining operational simplicity through automated adjustments.
2Ease of operation
If fixed operating limits are inaccurately configured, then operational simplicity is maintained, but process performance and efficiency deteriorate
Solution Approach 1:
The patent implements a feedback mechanism where asset performance management systems continuously monitor actual asset capability and process outcomes. This feedback loop enables the system to detect deviations from optimal performance and automatically adjust operating limits to maintain or improve process performance, eliminating the need for manual reconfiguration while ensuring accurate, data-driven limit settings.
Solution Approach 2:
The system performs preliminary analysis of asset performance data and process requirements to proactively determine optimal operating limits before process disruptions occur. By predicting future asset capability and process needs, the system pre-adjusts operating limits to prevent performance degradation rather than reacting to problems after they arise.
3Productivity
If concatenated industrial processes are implemented, then production capacity is increased, but process stability and coordination deteriorate
Solution Approach 1:
The patent creates a universal real-time operating limit adjustment system that can be applied across multiple concatenated industrial processes. The system integrates asset performance data and process control for different units (e.g., distillation, cracking, reforming processes), enabling coordinated optimization that maintains stability across the entire process train while maximizing overall production capacity through shared data and control mechanisms.
Data Source
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AI summary
Various embodiments described herein relate to calculating asset capability using model predictive control and/or industrial process optimization. In this regard, an optimization request to optimize an industrial process that produces an industrial process product is received. In response to the optimization request, asset modeling data is obtained from one or more asset performance management systems for an asset associated with the industrial process. Also in response to the optimization request, one or more real-time operating limits for the industrial process are adjusted based at least in part on the asset modeling data obtained from the one or more asset performance management systems. Furthermore, a control signal configured based at least in part on the one or more real-time operating limits is transmitted to a controller configured for optimization associated with the industrial process that produces the industrial process product.