Discovery Service Context Inference for Software-Defined Process Control
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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
1Reliability
If hardware-centric control systems are used, then system reliability is improved, but device complexity and cost increase
Solution Approach 1:
The system segments control functions into virtualized software components (virtual machines, containers) that run on standardized hardware platforms. This separates control logic from hardware dependencies, reducing overall system complexity while maintaining reliability through software-based fault isolation and redundancy.
Solution Approach 2:
The patent implements universal hardware platforms that can run multiple different control system software instances. This multi-functionality allows a single hardware infrastructure to support various control applications, reducing hardware complexity and cost while maintaining system reliability through software configuration rather than hardware specialization.
2Stability of the object's composition
If hardware-centric control systems are used, then system stability is improved, but adaptability decreases
Solution Approach 1:
The system employs dynamic software-defined control modules that can be instantiated, configured, and deployed on standardized hardware platforms. This dynamic approach allows the control system to adapt to changing process requirements while maintaining stability through virtualized isolation and controlled deployment processes.
Solution Approach 2:
The patent utilizes parameter-based configuration of virtualized control components, allowing system behavior to be modified through software parameter changes rather than hardware reconfiguration. This enables rapid adaptation to different process conditions while maintaining system stability through consistent hardware platforms and controlled parameter management.
3Ease of operation
If traditional control systems are used, then ease of operation is maintained, but productivity decreases
Solution Approach 1:
The system implements self-service capabilities through automated deployment, configuration, and management of virtualized control components. This reduces manual engineering effort and accelerates system implementation while maintaining ease of operation through standardized interfaces and automated operational procedures.
Solution Approach 2:
The patent employs preliminary configuration and pre-deployment validation of virtualized control modules, allowing systems to be prepared and tested before actual deployment. This preliminary action reduces on-site commissioning time and accelerates productivity while maintaining operational simplicity through pre-validated configurations.
4Manufacturing precision
If hardware-centric systems are used, then manufacturing precision is maintained, but loss of time increases
Solution Approach 1:
The system creates virtual copies of control functionality through virtual machines and containers that replicate control logic on standardized hardware. This copying approach maintains manufacturing precision through software-based control accuracy while reducing deployment time and hardware customization requirements.
Solution Approach 2:
The patent implements preliminary validation and testing of virtualized control modules in simulated environments before production deployment. This preliminary action ensures manufacturing precision is maintained while significantly reducing field commissioning time and accelerating system implementation.
Data Source
AI summary
A software defined (SD) process control system (SDCS) includes a method executed by a discovery service for inferring information regarding a physical or logical asset of a process plant. The method includes obtaining an announcement indicative of a presence of a physical or logical asset of the process plant. The method also includes obtaining, from a context dictionary, one or more parameters retrievable from the physical or logical asset or one or more services associated with the physical or logical asset that were not indicated in the announcement. Furthermore, the method includes storing a record of the discovered physical or logical asset in a discovered item data store. The record includes an indication of the identity of the physical or logical asset and the one or more parameters or one or more services associated with the physical or logical asset that were not indicated in the announcement.