Asset-Based Distributed Control for Zero-Engineering Commissioning
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Solution Overview
Problem
Current industrial process automation systems face challenges in efficiently designing, commissioning, and maintaining distributed control systems, requiring significant engineering efforts and lacking in flexible application design and auto-creation capabilities.
Innovation Solution
The implementation of a method and system that utilizes the IEC 61499 standard to define and model assets with built-in facets, allowing for the creation of an asset library and auto-generation of control applications through machine learning or an asset configurator tool, enabling distributed control and reduced engineering efforts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional industrial process automation systems are used for designing and commissioning distributed control systems, then system functionality is achieved, but significant engineering efforts and time are required
Solution Approach 1:
The patent applies preliminary action by pre-defining function blocks with standardized interfaces, behaviors, and configurations before actual system deployment. These pre-configured function blocks can be directly instantiated and connected to model control applications, eliminating the need for time-consuming on-site programming and commissioning activities. The system stores multiple versions of function blocks that can be selected and deployed immediately, significantly reducing engineering time while maintaining system functionality.
2Adaptability or versatility
If distributed control systems are designed with customizable function blocks, then application flexibility is improved, but system complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the control system into discrete, independent function blocks that each perform specific control functions. Each function block is a self-contained unit with defined inputs, outputs, and behaviors, allowing them to be independently configured, tested, and deployed. This modular segmentation enables flexible application design through composition of simple blocks while avoiding the complexity of monolithic control systems, as each block can be developed and maintained separately.
Solution Approach 2:
The patent implements universality by designing function blocks with standardized interfaces and configurable parameters that allow the same block type to serve multiple purposes across different applications. A single function block definition can be instantiated multiple times with different configurations to fulfill various control requirements, reducing the need for custom-designed blocks and simplifying the overall system architecture while maintaining high adaptability.
3Manufacturing precision
If manual configuration and programming of control applications is performed, then precise control logic is achieved, but engineering efforts and costs increase
Solution Approach 1:
The patent applies copying by enabling the replication of pre-defined function block templates across multiple instances and applications. Once a function block is properly configured and validated, it can be copied and instantiated repeatedly with minimal additional effort. The system supports version control and template management, allowing precise control logic developed once to be accurately replicated across the entire distributed control system, maintaining precision while dramatically reducing repetitive engineering work.
Data Source
AI summary
Configuring distributed control in an industrial system comprises building an asset model representative of a process control installation of the industrial system and creating an asset library of distributed control assets according to a distributed control programming standard. The asset model includes modeled assets defined according to levels of a physical model standard and representing physical devices of the industrial system. The distributed control assets each have one or more predefined, built-in facets. One of the distributed control assets in the asset library is mapped to each of the modeled assets to configure the process control installation of the industrial system and generate an asset-based control application for providing distributed control of the industrial system. Additional aspects relate to auto-creation of control applications based on an information model, either through the use of machine learning or an asset configurator tool.