Component Lifecycle Tracking for Secure Reuse and Remanufacture
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Solution Overview
Problem
The challenge of efficiently tracking the remaining life and predicting future failures of information handling system components, automating their separation for reuse, and managing their lifecycle to minimize environmental impact and security risks is not adequately addressed by existing methods.
Innovation Solution
A system and method that tracks component health through geographically distributed micro manufacturing centers, using robotic tools and secure data management to optimize carbon footprint, cost, and reuse efficiency by predicting failures and scheduling repairs and remanufacture based on lifecycle information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If components are manually harvested, tested, and reassembled from failed information handling systems, then component reuse is achieved, but the expense and complexity of breakdown, testing, and rebuilding becomes prohibitive
Solution Approach 1:
The patent applies preliminary action by embedding health sensors and tracking mechanisms in components during original manufacturing, continuously monitoring and recording operational data before failure occurs. This pre-collected data eliminates the need for post-failure testing and diagnosis, directly resolving the contradiction by making component assessment trivial while maintaining reuse validity.
Solution Approach 2:
Components perform self-service by autonomously tracking and reporting their own health status, usage patterns, and remaining life through embedded sensors and communication modules. This self-monitored information enables automated reuse decisions without manual testing, reducing remanufacturing complexity while ensuring reliable component selection.
2Ease of operation
If information handling systems are repaired by replacing failed components, then system functionality is restored, but commitment of functional components to landfills increases and environmental impact worsens
Solution Approach 1:
The patent implements discarding and recovering by systematically capturing still-functional components from failed systems through automated disassembly, using health data to identify viable reuse candidates. These recovered components are systematically tracked and deployed to new systems, reducing landfill commitment while maintaining repair efficiency through component availability.
Solution Approach 2:
The system applies parameter changes by transforming component status from 'failed' to 'reusable' through data-driven assessment. Health metrics, usage patterns, and remaining life predictions change the perceived value and suitability of components, enabling extended service life and reducing environmental impact while preserving repairability.
3Measurement precision
If component health tracking data is collected and stored, then remaining life prediction and failure prediction improve, but data security risks and system complexity increase
Solution Approach 1:
The patent applies segmentation by distributing health data storage and processing across multiple hierarchical levels: component-level sensors, system-level controllers, and centralized databases. This segmented architecture improves measurement precision through localized data collection while mitigating security risks by limiting exposure at each level and enabling selective data sharing.
4Productivity
If geographically distributed micro manufacturing centers are established for component remanufacture, then carbon footprint is optimized and reuse efficiency improves, but system complexity and infrastructure requirements increase
Solution Approach 1:
The patent implements segmentation by dividing the centralized remanufacturing operation into geographically distributed micro manufacturing centers. Each center independently handles local component recovery, testing, and refurbishment, improving productivity through localized operations while the modular structure manages network complexity through standardized interfaces and centralized coordination.
Solution Approach 2:
The system applies another dimension by adding geographical distribution as a new spatial dimension to the remanufacturing process. This transforms a single centralized facility into a network of distributed centers, optimizing carbon footprint through local operations while managing complexity through hierarchical coordination and standardized protocols.
Data Source
AI summary
A life cycle agent stored in non-transitory memory and executing on an information handling system processor detects lifecycle information associated with a component of the information handling system to communicate to a network location so that the lifecycle information is available at breakdown of the information handling system for reuse. A scannable code on the component includes an identifier stored with the lifecycle information so that component health is evaluated at information handling system breakdown. Lifecycle information of one component is stored on other components when relevant to the lifecycle of the other components, such as detection of liquid at a keyboard membrane, which is stored locally in a motherboard lifecycle non-transitory memory.