Automated Sample Processing System Route Optimization
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Solution Overview
Problem
Existing laboratory systems face inefficiencies in sample processing due to suboptimal route planning for sample containers, leading to reduced overall efficiency and increased processing times.
Innovation Solution
The implementation of a workflow management layer (WML) and a process control layer (PCL) that generate and optimize process plans for samples, taking into account the availability and status of analyzers and processing devices, to maximize sample flow and processing speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a sample container follows a predetermined processing route in existing laboratory systems, then the system structure is simple and easy to operate, but the processing time is extended and overall efficiency is reduced
Solution Approach 1:
The system dynamically adjusts the processing route of sample containers based on real-time analyzer availability and status. The workflow management layer continuously monitors system state and modifies routing decisions, transforming static predetermined routes into dynamic adaptive paths that optimize processing efficiency while minimizing delays.
2Adaptability or versatility
If multiple potential routes are created for sample containers, then processing flexibility is improved, but system complexity increases
Solution Approach 1:
The system segments the workflow management into distinct layers: the workflow management layer handles high-level route planning and flexibility, while the process control layer manages specific device operations. This segmentation allows multiple potential routes to be planned without proportionally increasing overall system complexity, as each layer handles a specific aspect of the control hierarchy.
Solution Approach 2:
The workflow management layer acts as an intermediary between the user/interface layer and the process control layer. It processes multiple potential routes and translates them into optimized instructions for the process control layer, reducing the complexity burden on individual components while maintaining overall system flexibility.
3Speed
If the workflow management layer optimizes process plans in real-time, then sample flow is maximized and processing speed improves, but computational requirements and control complexity increase
Solution Approach 1:
The workflow management layer generates process plans in advance based on current system state, preparing optimized routes before samples arrive at processing stations. This preliminary action allows real-time optimization without adding significant computational burden during active processing, as the heavy planning work is performed proactively based on monitored system conditions.
Data Source
AI summary
One embodiment of the invention is directed to a method comprising receiving instruction data relating to a sample in a sample container. The method includes generating, by at least one processor using a workflow management layer, a process plan for the sample, and providing the process plan to a process control layer. The process plan comprises a plurality of possible routes. The method also comprises selecting, by the at least one processor using the process control layer, an optimized route within the plurality of possible routes in the process plan, and providing the optimized route to a middleware control layer. The at least one processor and middleware control layer are operable to cause a transport system to proceed along the selected route.