Process Automation Network Configuration for Capacity Optimization
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Solution Overview
Problem
Optimizing process automation networks is challenging due to the difficulty in determining optimal network designs that balance resource allocation, quality, and future capacity, especially with complex traffic shaping mechanisms, leading to oversizing or undersizing issues and increased costs.
Innovation Solution
A method involving a network controller that analyzes network configurations based on topology and connectivity requirements, iteratively optimizing the network design to ensure it meets optimization criteria, including updating the topology and application design to avoid oversizing or undersizing, and generating a Bill of Material.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network resources are oversized to ensure quality targets are met, then reliability is improved, but cost increases
Solution Approach 1:
The patent performs preliminary network configuration verification before actual deployment by simulating traffic flows and checking resource allocation in advance. This allows identifying potential quality issues early and adjusting the configuration to achieve optimal resource utilization without oversizing the network infrastructure.
Solution Approach 2:
The system implements a feedback mechanism that analyzes network configuration responses and verification results to iteratively optimize resource allocation. By continuously evaluating actual resource utilization against quality targets, the system can adjust configurations to eliminate oversizing while maintaining required quality levels.
2Quantity of substance
If network resources are undersized to reduce cost, then cost decreases, but quality targets cannot be met
Solution Approach 1:
The patent performs preliminary verification of network configurations by simulating actual traffic patterns and measuring performance against quality targets before deployment. This early detection allows identifying insufficient resource allocation and adjusting the design to meet quality requirements while avoiding unnecessary oversizing.
Solution Approach 2:
The system dynamically adjusts network configuration parameters such as bandwidth allocation, priority levels, and traffic shaping settings based on verified performance data. By optimizing these parameters through iterative verification and analysis, the system achieves quality targets with minimal necessary resources.
3Productivity
If complex traffic shaping mechanisms are implemented to optimize resource allocation, then resource utilization improves, but device complexity increases
Solution Approach 1:
The patent implements automated verification and optimization systems that self-adjust network configurations based on measured performance. The system automatically analyzes configuration responses, identifies optimization opportunities, and adjusts traffic shaping parameters without requiring manual intervention, thereby managing complexity while maintaining high resource utilization.
Solution Approach 2:
The system optimizes resource utilization by dynamically adjusting traffic shaping parameters such as bandwidth limits, priority queues, and scheduling policies based on verified performance data. Through iterative parameter optimization guided by automated verification, the system achieves efficient resource allocation with reduced manual configuration complexity.
Data Source
AI summary
A computer implemented method for optimizing a process automation network includes providing topology data of the process automation network that includes network devices to a network controller and providing connectivity requirement data representing intended communication of a process application between communication endpoints of the process to the network controller according to a process application design for creating a network configuration; receiving a network configuration response from the network controller; analyzing the network configuration response for verifying whether the network configuration meets optimization criteria; in dependence on the analysis results, updating the network topology design and/or the process application design and the connectivity requirements, or stopping the optimization of the process automation network.