Sample Container Storage Selection for Laboratory Congestion Control
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Solution Overview
Problem
Automated laboratory systems (ALS) experience congestion due to varying processing times of sample containers, leading to inefficiencies and reduced throughput, as longer paths and occupancy imbalances in storage units increase the risk of system overload.
Innovation Solution
A method for selecting storage units based on distance and occupancy data to optimize path selection, prioritizing shorter paths and dynamically distributing sample containers to reduce congestion and improve system capacity prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sample containers are processed simultaneously in the ALS, then processing capacity increases, but congestion risk increases due to varying processing times and storage unit occupancy imbalances
Solution Approach 1:
The system dynamically adjusts storage unit selection based on real-time occupancy data and path length considerations. The computing device continuously monitors storage unit states and modifies routing decisions for each sample container to balance load across storage units, preventing congestion while maintaining high processing capacity
Solution Approach 2:
The system implements feedback loops where occupancy data from storage units is continuously collected and used to inform subsequent storage selection decisions. This feedback mechanism allows the system to adapt to changing conditions and redistribute sample containers to prevent overcrowding in any single storage unit
2Adaptability or versatility
If longer paths are used for moving sample containers, then more storage units can be accessed, but processing time increases leading to reduced throughput
Solution Approach 1:
The system changes the parameter of path selection by considering both path length and storage unit occupancy together. Instead of always selecting the shortest path or the path to the nearest storage unit, the system optimizes the combined metric to balance accessibility with processing time efficiency
Solution Approach 2:
The system performs preliminary evaluation of multiple possible paths and storage unit combinations before finalizing the routing decision. By pre-calculating optimal paths based on current system state, the system avoids unnecessary detours and minimizes processing time while still accessing the necessary storage units
Data Source
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AI summary
The invention relates to a method comprising: selecting, by a computing device, based on distance data and occupancy data, a storage unit among a plurality of storage units for storing a sample container processed by an automated laboratory system. The distance data specify a distance along a path for moving the sample container in the automated laboratory system, such that a biological sample included in the sample container is processed by the automated laboratory system according to a test order associated with the biological sample. The path comprises the storage unit. The occupancy data comprise information indicative of an occupancy of the storage unit.