Diagnostic Lab Module Control for Automated State Switching
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Solution Overview
Problem
Large-scale diagnostic laboratories face inefficiencies and inaccuracies due to the need for continuous human monitoring and intervention across numerous laboratory analyzers and ancillary modules, which can be time-consuming and prone to errors.
Innovation Solution
A diagnostic laboratory system with a middleware that communicates with modules to change their operational states, enabling or disabling them as needed, and a master module that receives instructions to manage the operational states of submodules, reducing human intervention and optimizing module usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human operators continuously monitor and intervene in large-scale diagnostic laboratories, then operational control can be maintained, but time consumption increases and accuracy decreases
Solution Approach 1:
The system enables modules to automatically monitor their own operational states and perform self-diagnosis. The modular architecture allows each component to independently manage its operations, reducing the need for continuous human oversight while maintaining high accuracy through automated control mechanisms.
Solution Approach 2:
The control system implements continuous feedback loops where operational data from modules is automatically collected, analyzed, and used to adjust system operations. This automated feedback mechanism replaces human monitoring, providing real-time operational control without time-consuming manual intervention.
2Productivity
If multiple laboratory analyzers with similar capabilities are deployed, then processing capacity increases, but system complexity increases
Solution Approach 1:
The laboratory system is divided into independent, standardized modules that can be configured in different combinations. Each module performs a specific function and can be independently controlled, allowing the system to scale processing capacity without proportionally increasing coordination complexity through modular architecture.
Solution Approach 2:
Modules are designed with universal interfaces and standardized communication protocols that allow them to function in multiple roles within different system configurations. This multi-functionality enables the same module type to contribute to various processing workflows, increasing productivity without requiring unique complex control logic for each module.
3Productivity
If modules operate continuously without optimization, then processing throughput is maintained, but wear and tear and energy consumption increase
Solution Approach 1:
The system dynamically adjusts module operational states based on real-time workload demands and module conditions. Modules can transition between active, standby, and maintenance states, optimizing energy consumption and reducing wear by avoiding unnecessary continuous operation while maintaining required processing throughput through flexible resource allocation.
Solution Approach 2:
The system maintains continuous specimen processing throughput by intelligently coordinating module operations rather than allowing idle periods. Workload is continuously distributed across available modules, ensuring that processing capacity is fully utilized without any single module operating excessively, thereby balancing throughput maintenance with reduced overall wear and energy consumption.
Data Source
AI summary
Methods of controlling diagnostic laboratory systems include providing one or more modules, each of the one or more modules configured to process a specimen container and/or analyze a specimen; providing middleware configured to communicate with the one or more modules, wherein the middleware is configured to generate instructions to change an operational state of at least one of the one or more modules to enabled or disabled; generating, by the middleware, one or more instructions to change the operational state of at least one of the one or more modules; and changing the operational state of at least one of the one or more modules in response to one or more instructions generated by the middleware. Systems including a middleware server configured to carry out the methods are provided as are other aspects.