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Pareto optimization technique in actuation control for error minimization and reliability analysis in an operational pin-constrained digital microfluidic biochip

机译：致动控制中的Pareto优化技术，可在引脚受限的数字微流控生物芯片中实现误差最小化和可靠性分析

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摘要

Droplet routing in digital microfluidic biochip (DMFB) attempts to reduce overall droplet routing time. This phenomena increases repeated use of electrodes during electro-wetting on dielectrics (EWOD). Repeated use of same electrode requires frequent actuation. Often, this over utilization and frequent actuation of same electrodes affects the reliability of DMFB since these electrodes become fault prone under excessive use. Research on fault probability reduction, fault identification and fault management are key issues to achieve reliable output from DMFB. In this paper, a fault management process is focused with the objective to gain reliable performance of DMFB. This method reduces error probabilities of DMFB through a balanced utilization and actuation of electrodes. Initial phase of the proposed work captures the utilization of different electrodes resulting from a pin-constrained droplet routing schedule of DMFB. This initial routing schedule is then reviewed to ensure equitable utilization of electrodes. This will also increase the life-span of electrodes. Consequently, that will lessen fault probability and improve reliability. Finally a Pareto optimal analysis is performed upon the data acquired from previous two processes. These studies have been experimented upon different benchmark samples including in-vitro test suites and complex assay samples like Bradford protein assay, qPCR, sucrose gradient analysis to test its robustness and the results are really encouraging.
机译：数字微流控生物芯片（DMFB）中的液滴布线尝试减少总体液滴布线时间。这种现象会增加电介质上电润湿（EWOD）期间电极的重复使用。重复使用同一电极需要频繁启动。通常，相同电极的过度使用和频繁启动会影响DMFB的可靠性，因为这些电极在过度使用下容易发生故障。故障概率降低，故障识别和故障管理的研究是实现DMFB可靠输出的关键问题。本文以故障管理过程为重点，旨在获得DMFB的可靠性能。这种方法通过平衡利用和激励电极来降低DMFB的错误概率。拟议工作的初始阶段捕获了由于引脚受限的DMFB液滴布线时间表而产生的不同电极的利用率。然后检查此初始布线计划，以确保公平利用电极。这也将增加电极的寿命。因此，这将减少故障概率并提高可靠性。最后，对从前两个过程获取的数据进行帕累托最优分析。这些研究已经在不同的基准样品上进行了实验，包括体外测试套件和复杂的测定样品，例如Br​​adford蛋白测定，qPCR，蔗糖梯度分析，以测试其鲁棒性，结果令人鼓舞。

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