Shadow Workflow Engines for Automated Analyzer Reliability
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Solution Overview
Problem
The increasing complexity of automated analyzers in laboratories leads to higher network traffic, latency, and a single point of failure, reducing sample turnaround times and productivity.
Innovation Solution
Implementing a computer-implemented method with a main workflow engine and shadow workflow engines, where the shadow engines receive data snapshots to process orders independently, reducing network traffic and providing redundancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single centralized control node is used to control workflows of automated analyzers, then centralized control and coordination is achieved, but network traffic increases, latency increases, and the system has a single point of failure
Solution Approach 1:
The patent divides the centralized control system into multiple distributed workflow engines (main workflow engine and shadow workflow engines), each responsible for specific subsets of automated analyzers. This segmentation eliminates the single point of failure by distributing control functions across multiple nodes, while reducing network traffic by localizing control decisions at each distributed engine.
2Productivity
If a single centralized control node processes all orders for multiple automated analyzers, then centralized coordination is maintained, but network traffic and computing resources at the central node increase considerably
Solution Approach 1:
The patent extracts control functions from the centralized main workflow engine and distributes them to shadow workflow engines. Each shadow workflow engine receives and processes a subset of orders locally, extracting the burden of processing from the central node. This reduces network traffic and computing resource consumption at the central node while maintaining overall system productivity.
3Productivity
If increased computing resources are allocated at the centralized control node, then more orders can be processed, but the complexity and cost of the system increases
Solution Approach 1:
The patent merges the control functions of the main workflow engine with multiple shadow workflow engines into a distributed architecture. Instead of concentrating all computing resources at a single centralized node, the system combines resources across multiple distributed engines, achieving the same or greater processing capacity with reduced complexity at any single node.
4Reliability
If a centralized workflow engine controls all modules, then centralized coordination is achieved, but the system has a single point of failure causing downtime
Solution Approach 1:
The patent implements shadow workflow engines as backup systems that are prepared in advance to take over control functions. When the main workflow engine fails, the shadow engines can immediately assume control, providing beforehand cushioning against failure. This eliminates the single point of failure and minimizes system downtime by having pre-configured backup control capacity.
Data Source
AI summary
A computer-implemented method for processing biological samples in an environment including multiple automated analyzers having multiple modules is presented. The method includes receiving data related to a plurality of orders for processing biological samples at a main workflow engine. The main workflow engine receives and processes data for each of the multiple automated analyzers having multiple modules. The method further includes providing a data snapshot to at least one shadow workflow engine associated with a subset of one or more modules of the multiple modules. The data snapshot comprises only a portion of the data related to the plurality of orders that is necessary to determine actions of the module of the multiple modules. The method further includes determining, by the shadow workflow engine, a plurality of actions for the subset of modules to process the plurality of orders based on the data snapshot.