Software Agents Automate Part Replacement Configuration
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Solution Overview
Problem
Current asset management processes for part replacement in manufactured products are largely manual, lacking system intelligence to identify configuration changes, leading to inefficient sourcing and ordering decisions, and labor-intensive monitoring of life-limited parts.
Innovation Solution
The implementation of a Self-Aware Assets in a Highly Networked Environment (SAHNE) system, where part agents and ordering manager agents automate the identification of configuration changes and ordering of replacement parts based on up-to-date configuration data, using software agents to represent physical parts and negotiate with suppliers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual monitoring and inspection processes are used for part replacement, then labor flexibility is maintained, but productivity is reduced and errors increase
Solution Approach 1:
The system enables self-service through software agents that automatically monitor part status, detect configuration changes, and initiate ordering decisions without human intervention. Part agents represent individual parts and autonomously communicate with ordering manager agents to trigger replacements based on lifecycle status or configuration changes.
Solution Approach 2:
Manual mechanical monitoring processes are replaced with an electronic software-based system. The patent substitutes human inspection and paper-based tracking with automated software agents that continuously monitor part status, detect changes, and manage ordering through electronic communications with suppliers.
2Measurement precision
If manual configuration change tracking is used, then system simplicity is maintained, but measurement precision is reduced
Solution Approach 1:
The system implements continuous feedback loops where part agents monitor their own status and configuration data, compare against desired configurations, and automatically trigger notifications when changes are detected. This feedback mechanism ensures accurate detection of configuration changes while maintaining systematic control.
Solution Approach 2:
Software agents act as intermediaries between physical parts and the configuration management system. Part agents represent individual parts and mediate communication between the physical part status and the ordering manager, enabling precise tracking without direct human intervention.
3Productivity
If automated software agents are deployed, then productivity is improved, but device complexity increases
Solution Approach 1:
The system segments functionality into distinct software agents with specific roles: part agents represent individual parts and monitor their status, while ordering manager agents handle ordering decisions. This segmentation distributes complexity across multiple simple, specialized agents rather than one complex centralized system.
Solution Approach 2:
The software agent architecture provides universal functionality that can be applied to any part or product configuration. The same agent framework and communication protocols handle diverse part types, configuration changes, and ordering scenarios, reducing overall system complexity through standardized multi-functional components.
Data Source
AI summary
Methods and systems for use in managing part replacement associated with a manufactured product. A part agent, executed by a computing system and associated with a current part installed in the manufactured product, provides a replacement notification to an ordering manager agent executed by the computing system and associated with the current part. The replacement notification indicates that a replacement of the current part is desired. The ordering manager agent determines that the current part is associated with a configuration change that represents a substitution of a new part for the current part. The ordering manager agent provides the configuration change to the part agent. The part agent orders the new part via the ordering manager agent based on the configuration change.