Diagnostic Device Credit Reallocation for Continuous Sample Analysis
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Solution Overview
Problem
Existing diagnostic systems face inefficiencies in resource allocation and operational readiness due to uneven usage of diagnostic devices, leading to potential downtime and suboptimal system performance.
Innovation Solution
A system architecture with device-specific internal values and central availability values enables dynamic redistribution of 'analysis credits' between diagnostic devices, allowing flexible control of operational readiness and resource allocation through bi-directional data exchange.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If analysis credits are allocated statically to each diagnostic device, then device-specific operational control is simplified, but system-wide operational readiness and flexibility deteriorate due to uneven usage patterns
Solution Approach 1:
The system segments analysis credits into two distinct components: device-specific internal values stored in local memory and a central availability value stored in external memory. This segmentation allows each diagnostic device to maintain its own operational state while the central system tracks overall resource availability, resolving the contradiction between local operational simplicity and global system flexibility.
Solution Approach 2:
The patent introduces a temporal dimension to credit allocation by implementing dynamic redistribution mechanisms. Analysis credits can be reallocated between devices based on actual usage patterns and system needs, transforming the static allocation model into a dynamic one that adapts to changing operational conditions, thereby improving system-wide readiness without complicating device-specific operation.
2Adaptability or versatility
If analysis credits are reallocated dynamically between diagnostic devices, then system flexibility and operational readiness improve, but system complexity increases due to additional control mechanisms
Solution Approach 1:
The patent introduces an intermediary software layer that manages the complex logic of credit redistribution. This software acts as a mediator between the diagnostic devices and the central control system, handling the calculations and decisions regarding credit reallocation. By isolating the complexity within this intermediary layer, the individual diagnostic devices remain relatively simple while the system as a whole gains flexibility.
Solution Approach 2:
The system implements self-service mechanisms where the software automatically monitors usage patterns and performs credit redistribution without requiring manual intervention. The system autonomously detects when reallocation is needed and executes the redistribution, reducing the operational complexity for users while maintaining high system flexibility.
3Reliability
If device-specific internal values are continuously synchronized with central availability values, then real-time operational control is improved, but data exchange overhead and processing time increase
Solution Approach 1:
Instead of continuous synchronization, the patent implements periodic data exchange between device-specific internal values and central availability values. The system performs synchronization at predetermined intervals or trigger events (such as when credits are allocated or consumed), reducing the frequency of data exchanges while maintaining sufficient real-time control for operational decision-making.
Solution Approach 2:
The system performs preliminary calculations and preparations for credit redistribution in advance, storing necessary data locally at diagnostic devices. This allows the actual synchronization and redistribution operations to be executed more efficiently with minimal data exchange, as the heavy computational work has already been prepared beforehand.
Data Source
AI summary
A method for performing analyses of biological samples using at least one diagnostic device, in particular in a diagnostic system, includes (i) checking whether an internal value stored in a software module in a control device of the diagnostic device corresponds to a zero value in analyses when a biological sample is or was fed to the diagnostic device by way of a consumable material specific to the diagnostic device, (ii) analyzing the biological sample by the diagnostic device if the internal value deviates from the zero value, and (iii) changing the internal value in the software module of the diagnostic device by an operation value of an analysis.