Distributed Industrial Control Orchestration for Incremental Node Updates
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Solution Overview
Problem
Industrial systems face challenges in managing complexity and flexibility due to statically configured I/O and subsystems, which hinder incremental updates and adoption of IoT and software-defined technologies, leading to high operational and capital expenses and limited deployment of advanced technologies in harsh environments.
Innovation Solution
The implementation of a software-defined industrial system (SDIS) with dynamic data models, orchestration techniques, and self-descriptive modules enables flexible configuration, management, and integration of IoT devices, allowing for real-time updates and adaptation, while leveraging open architectures and security features to enhance reliability and scalability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If statically configured I/O and subsystems are used in industrial systems, then system reliability is maintained under harsh conditions, but system flexibility and adaptability deteriorate, preventing incremental updates and adoption of new technologies
Solution Approach 1:
The patent segments the industrial control system into multiple independent virtual machines that can be individually updated, configured, and managed. Each virtual machine represents a discrete functional unit (e.g., process control, safety systems, data acquisition) that can be modified without affecting the entire system, enabling incremental adoption of new technologies while maintaining overall system stability and reliability.
2Adaptability or versatility
If statically configured I/O and subsystems are used in industrial systems, then operational stability is maintained, but the ability to implement incremental changes and updates deteriorates
Solution Approach 1:
The patent implements dynamic configuration capabilities where virtual machines can be created, modified, migrated, and deleted while the industrial system remains operational. This dynamic approach allows incremental updates and technology adoption without requiring full system shutdowns, reducing downtime and enabling continuous production while evolving the control system architecture.
3Productivity
If traditional industrial control systems are used, then proven reliability is maintained, but operational and capital expenses increase due to lack of optimization capabilities
Solution Approach 1:
The patent implements comprehensive feedback mechanisms where virtual machines continuously monitor system performance, resource utilization, and operational parameters. This feedback enables real-time optimization of control strategies, predictive maintenance scheduling, and resource allocation, improving productivity while reducing operational costs through data-driven decision-making and automated adjustments.
4Adaptability or versatility
If heterogeneous IoT devices with heterogeneous software are integrated, then technological advancement and capability are improved, but device and software complexity increases making management difficult
Solution Approach 1:
The patent implements a universal virtualization layer that provides standardized interfaces and abstraction mechanisms for managing heterogeneous IoT devices and software. This universal approach allows diverse devices with different protocols, architectures, and software to be integrated and managed through common virtual machine containers, reducing management complexity while maintaining the ability to leverage advanced capabilities of each device type.
Data Source
AI summary
Various systems and methods for implementing a software defined industrial system are described herein. For example, an orchestrated system of distributed nodes may run an application, including modules implemented on the distributed nodes. In response to a node failing, a module may be redeployed to a replacement node. In an example, self-descriptive control applications and software modules are provided in the context of orchestratable distributed systems. The self-descriptive control applications may be executed by an orchestrator or like control device and use a module manifest to generate a control system application. For example, an edge control node of the industrial system may include a system on a chip including a microcontroller (MCU) to convert IO data. The system on a chip includes a central processing unit (CPU) in an initial inactive state, which may be changed to an activated state in response an activation signal.