Industrial Process Controller Diagnostics for Lost Opportunity Analysis
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Solution Overview
Problem
Model-based industrial process controllers experience performance deterioration over time due to factors like equipment degradation, operator actions, and misconfiguration, leading to reduced benefits and difficulty in maintenance, especially with a shortage of skilled engineers.
Innovation Solution
An apparatus and method that estimate the impacts of operational problems on model-based industrial process controllers by analyzing data to identify issues such as constraint, model quality, inferential quality, optimizer configuration, and process variable noise, presenting these impacts in terms of lost opportunities to facilitate prioritization and resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If model-based controllers are used to control industrial processes, then productivity and control precision are improved, but performance deteriorates over time due to equipment degradation, operator actions, and misconfiguration
Solution Approach 1:
The system performs preliminary diagnostics by continuously monitoring controller performance and identifying operational problems before they cause significant performance deterioration. The impact estimation module proactively calculates potential performance losses and presents them to operators, enabling preventive maintenance actions to be taken before the controller performance degrades further.
2Measurement precision
If comprehensive monitoring of controller performance is implemented, then operational issues can be identified, but the complexity of the system increases
Solution Approach 1:
The system extracts and isolates specific operational problem categories (constraint issues, model quality issues, inferential quality issues, optimizer configuration issues, process variability issues) from the complex controller performance data. By separating these distinct problem types and estimating their individual impacts, the system simplifies the monitoring approach while maintaining comprehensive performance measurement capability.
3Ease of repair
If detailed analysis of operational problems is performed to identify specific issues, then maintenance can be targeted, but the time and resources required for analysis increase
Solution Approach 1:
The system implements continuous feedback by monitoring controller performance data and automatically analyzing it to identify operational problems and their impacts. The impact estimation module provides ongoing feedback to operators about performance losses and recommended actions, enabling targeted maintenance without requiring extensive manual analysis time. The system learns from historical data to improve its diagnostic accuracy over time.
Data Source
AI summary
A method includes obtaining data associated with operation of a model-based industrial process controller. The method also includes identifying at least one estimated impact of at least one operational problem of the industrial process controller, where each estimated impact is expressed in terms of a lost opportunity associated with operation of the industrial process controller. The method further includes presenting the at least one estimated impact to a user. The at least one estimated impact could include impacts associated with noise or variance in process variables used by the industrial process controller, misconfiguration of an optimizer in the industrial process controller, one or more limits on one or more process variables, a quality of at least one model used by the industrial process controller, a quality of one or more inferred properties used by the industrial process controller, or one or more process variables being dropped from use by the industrial process controller.