Software-Defined Control Module Association for Flexible Process Plants
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Solution Overview
Problem
Current industrial process control systems are inflexible and hardware-centric, leading to increased costs for initial engineering and change management, as well as vulnerabilities to cost overruns and supply-chain delays in process plant installations and expansions.
Innovation Solution
A software-defined process control system (SDCS) that decouples software and hardware, implementing business logic as logical abstractions on top of computer resources and managing resources through a hyper-converged infrastructure. This system includes a software-defined networking layer, application layer, and storage layer, dynamically managing resources to support dynamic demands of process control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional hardware-centric control systems are used, then system stability and reliability are maintained, but flexibility and adaptability are reduced
Solution Approach 1:
The patent replaces traditional hardware-based control architectures with a software-defined control system. The controller executes software modules that can be dynamically loaded, unloaded, and modified without changing the physical hardware configuration. This substitution of mechanical/hardware control with software-based control enables flexible adaptation to different process requirements while maintaining system stability through the same physical infrastructure.
Solution Approach 2:
The control system implements dynamic module loading and execution capabilities, where software modules can be activated or deactivated based on real-time process needs. The system can dynamically allocate computational resources and adjust control strategies without requiring hardware reconfiguration, enabling the system to adapt to changing operational requirements while maintaining stability through controlled transitions.
2Adaptability or versatility
If software modules are dynamically loaded and executed, then system adaptability is improved, but system complexity increases
Solution Approach 1:
The patent introduces a module manager as an intermediary component that handles the complex tasks of loading, executing, and managing software modules. This intermediary abstracts the complexity of dynamic module management from the overall control system, providing a standardized interface for module operations while maintaining system stability through controlled module lifecycle management. The module manager coordinates module dependencies and ensures proper resource allocation.
Solution Approach 2:
The software modules are designed with self-descriptive capabilities, including metadata that automatically identifies their requirements, dependencies, and operational parameters. This self-service approach reduces the complexity of manual module management by enabling automatic module registration, dependency resolution, and resource allocation, allowing the system to dynamically adapt while maintaining manageable complexity through automated processes.
3Productivity
If hyper-converged infrastructure is used, then resource management efficiency is improved, but initial system complexity increases
Solution Approach 1:
The patent implements a hyper-converged infrastructure that merges computing, storage, and networking resources into an integrated system. By combining these previously separate infrastructure components into a unified platform, the system achieves improved resource management efficiency through centralized control and dynamic allocation. The initial complexity of integration is managed through standardized interfaces and automated configuration processes.
Solution Approach 2:
The hyper-converged infrastructure is designed with universal components that can perform multiple functions. The same physical hardware resources can dynamically serve different control tasks, data storage requirements, and communication needs based on real-time demands. This multi-functionality improves resource utilization efficiency while the standardized architecture helps manage the initial integration complexity through consistent design patterns.
Data Source
AI summary
A process control system includes a plurality of field devices operating to control a process in a process plant. A communication infrastructure couples the plurality of field devices to a software-defined control system (SDCS) that receives data from the field devices and transmits instructions to the field devices. A data cluster, executing the SDCS, includes a plurality of compute nodes, each of which includes a processor executing an operating system, a memory, and a communication resource coupled to one or more other compute nodes in the data cluster. A plurality of instantiated containers, each of which is an isolated execution environment within the operating system of the compute node on which the container is instantiated, cooperate to facilitate execution of a control strategy in the SDCS. At least one of the containers in the SDCS is pinned to a component in the SDCS.