Distributive Deployment of Function Block Applications
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Solution Overview
Problem
Existing process automation systems face challenges in efficiently deploying function block application programs (FBAPs) across distributed control nodes while considering underlying node details, relationships, and constraints.
Innovation Solution
The implementation of automatic and distributive deployment techniques for FBAPs across process automation nodes, which involves analyzing constraints and selecting suitable subsets of nodes for deployment, taking into account operational parameters, performance capabilities, and environmental factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If FBAPs are manually deployed across process automation nodes, then deployment control and constraint compliance are improved, but deployment time and operational complexity increase
Solution Approach 1:
The deployment system performs self-service by automatically analyzing FBAP constraints, evaluating node suitability, and executing deployment decisions without manual intervention. The system services itself by maintaining deployment metadata, automatically resolving constraints, and adapting to system changes, eliminating the need for continuous human oversight while ensuring constraint compliance.
Solution Approach 2:
The system performs preliminary actions by pre-analyzing FBAP constraints, pre-evaluating node capabilities and relationships, and pre-determining optimal deployment configurations before actual deployment occurs. This advance preparation ensures that when deployment is executed, it proceeds rapidly while already satisfying all constraints.
2Productivity
If FBAPs are deployed without considering underlying node details, then deployment simplicity and speed are improved, but deployment optimality and system performance deteriorate
Solution Approach 1:
The deployment system acts as an intermediary layer between the high-level FBAP deployment request and the underlying complex node details. It automatically queries and processes node capabilities, relationships, and constraints, then translates this information into optimal deployment decisions. This intermediary approach maintains deployment simplicity while ensuring optimality by systematically considering all relevant node characteristics.
Solution Approach 2:
The system dynamically changes deployment parameters based on analyzed node characteristics, relationships, and constraints. Instead of using fixed deployment rules, it adjusts deployment decisions according to the specific parameters of available nodes, their interrelationships, and FBAP requirements, thereby achieving both speed and optimality.
3Reliability
If the system analyzes all node relationships and constraints before deployment, then deployment optimality is improved, but analysis time and computational complexity increase
Solution Approach 1:
The system segments the complex deployment analysis into distinct modules: constraint analysis, node capability evaluation, relationship assessment, and optimization algorithms. Each segment handles a specific aspect of the deployment decision, processing information independently and systematically. This modular segmentation reduces overall system complexity while maintaining comprehensive analysis for optimal deployment.
4Device complexity
If FBAPs are deployed across fewer nodes, then system complexity and deployment overhead are reduced, but system scalability and fault tolerance deteriorate
Solution Approach 1:
The deployment system is dynamic and adaptive, automatically adjusting the number and configuration of nodes used for FBAP deployment based on current system conditions, constraints, and requirements. It can scale deployment across more or fewer nodes as needed, optimizing the balance between complexity and scalability for each specific deployment scenario rather than following a fixed rule.
Data Source
AI summary
Implementations are described herein for automatic deployment of function block application programs (FBAPs) across process automation nodes of a process automation system. In various implementations, one or more constraints associated with execution of a FBAP may be identified. Based on the one or more constraints, a process automation system that includes a plurality of process automation nodes may be analyzed. Based on the analysis, a subset of two or more process automation nodes on which to distributively deploy the FBAP may be selected from the plurality of processing node. In response to selecting the subset, the FBAP may be distributively deployed across the two or more process automation nodes of the subset.