Hierarchical Smart Asset Control for Large-Scale Industrial Optimization
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Solution Overview
Problem
Traditional process-centric control systems face challenges in managing complex industrial operations across large domains due to exponential complexity, limiting the scope of coordinated control strategies and failing to address reliability and integrity issues, especially in large-scale industrial settings.
Innovation Solution
The development of a Hierarchical Asset Control Application and Integrated Smart Asset Control System, which employs a hierarchical view of industrial operations as a collection of assets rather than a single process, using intelligent agents and cyber-physical systems to facilitate granular control and optimization across smart asset groupings, addressing operational constraints and objectives in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If process-centric control systems are used to manage large operational domains, then coordinated control strategy scope is limited, but system complexity increases exponentially
Solution Approach 1:
The patent segments the industrial operation into discrete assets organized in a hierarchical structure (asset, asset set, unit, area, plant, enterprise levels). Each asset is controlled by independent intelligent agents that can be configured and managed separately, avoiding the exponential complexity of process-centric systems while enabling coordinated control across the entire operational domain through the hierarchical framework.
2Adaptability or versatility
If process-centric design is used for control systems, then control scope can be expanded to larger domains, but engineering and maintenance complexity increases
Solution Approach 1:
The intelligent agents embedded in each asset provide self-service capabilities including autonomous decision-making for control actions, self-diagnosis for maintenance needs, and automatic configuration. This reduces engineering and maintenance complexity by eliminating the need for complex manual programming and coordination that characterizes process-centric systems, while still enabling broad control scope through the hierarchical asset structure.
3Ease of manufacture
If traditional control systems are used, then implementation is straightforward, but reliability and integrity issues are not addressed
Solution Approach 1:
The intelligent agents continuously monitor asset performance, operational constraints, and objectives, using real-time feedback to adjust control actions and maintain optimal operation. This feedback mechanism enables the system to proactively address reliability and integrity issues by detecting deviations from acceptable operating conditions and automatically implementing corrective actions, while maintaining implementation ease through the standardized agent framework.
4Ease of manufacture
If digital control systems are programmed to replicate analog functionality, then transition is smooth, but potential scope of automatic coordinated control is not realized
Solution Approach 1:
Instead of programming digital systems to replicate analog functionality, the patent inverts the approach by creating a fundamentally new asset-centric control paradigm with intelligent agents that natively provide autonomous coordinated control. This inversion enables the full scope of automatic coordinated control across hierarchical levels while maintaining transition smoothness through the modular, configurable nature of the agent-based system that can work with existing assets and processes.
Data Source
AI summary
Systems and methods of a Hierarchical Smart Asset Control Application development and Integrated Smart Asset Control System optimization are disclosed. In various embodiments, the system may develop a Hierarchical Asset Control Application and corresponding control hardware requirements. This can be used to create an Integrated Smart Asset Control System in order execute various processes for a set of equipment elements. The smart assets associated with the system may utilize intelligent agents to balance operational constraints and operational objects in order to determine real-time optimized operational parameters for a process and implement the appropriate controls to facilitate achieving the improved operational objectives.