Lab Automation Path Optimization for Transfer Time Reduction
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Solution Overview
Problem
Current liquid handling systems in genomic engineering face inefficiencies in reducing the travel cost (time) of multiple liquid transfers between source and destination points, particularly in high-throughput applications, where optimizing the order of transfers can significantly impact overall processing time.
Innovation Solution
The implementation of cost functions to determine a low-cost sequential ordering of liquid transfers using a Traveling Salesman Problem (TSP) solver, which considers the movement of two components, such as an acoustic transducer and a destination plate, to minimize the total transfer cost by aligning them at a liquid transfer position and computing the maximum travel cost for each transition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional transfer ordering is used, then the liquid handling system can complete transfers, but the total transfer time is excessive
Solution Approach 1:
The system pre-calculates the optimal transfer sequence using TSP algorithms before executing the liquid handling operations. By determining the most efficient path in advance, the system minimizes total travel time and maximizes throughput without compromising transfer accuracy
Solution Approach 2:
The patent implements dynamic path optimization by considering real-time positions of multiple moving components (acoustic transducer, source plate, destination plate) and adjusting the transfer sequence to coordinate their movements efficiently, reducing idle time and synchronization delays
2Adaptability or versatility
If multiple components move to align at transfer positions, then transfer flexibility is improved, but the complexity of coordinating movements increases
Solution Approach 1:
The patent makes multiple components (acoustic transducer, source plate, destination plate) capable of movement, allowing any component to serve as the reference frame for transfer operations. This multi-functionality enables flexible transfer sequences while the TSP algorithm coordinates their movements to manage complexity
Solution Approach 2:
The control system acts as an intermediary that receives transfer requests, calculates optimal sequences using TSP, and coordinates the movements of multiple components. This centralized mediation simplifies the complexity by providing a unified control strategy rather than managing each component independently
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces the total transfer time by determining the optimal order of liquid transfers, enhancing the efficiency of liquid handling systems in genomic engineering and enabling more precise control over the movement of components within the system.
Implementation Method 1
Acoustic drop ejection is a technology which uses highly focused sound energy to cause an ultra-small (e.g., 2.5 nL, 25 nL) droplet to dislocate from a source well and be deposited into a destination well
Data Source
AI summary
Systems, methods and computer-readable media are provided for determining a sequential ordering of predefined transfers for transferring an object from source points of a source array to destination points of a destination array in a laboratory automation system. For each transition to a next transfer, first and second component travel costs between current and next transfer positions are determined. A transition travel cost is determined from the first and second component travel costs. The cost of each sequential ordering of the predefined transfers is based upon an aggregate of the transition travel costs for each ordering of the transfers. The resolved sequential ordering may be based upon the sequential ordering that has the lowest cost.