Fault Diagnosis for Leakage and Blockage Defects in Flow-Based Microfluidic Biochips

Abstract

Advances in flow-based microfluidics now allow an efficient implementation of biochemistry on-a-chip for DNA sequencing, drug discovery, and point-of-care disease diagnosis. However, the adoption of flow-based biochips is hampered by defects that frequently occur in chips fabricated using soft lithography techniques. Recently published work has shown how we can automate the testing of flow-based biochips; diagnosis methods are now needed to identify the flaws in the fabrication process and to facilitate the use of partially defective chips. Since disposable biochips are being targeted for a highly competitive and low-cost market segment, such diagnosis methods need to be inexpensive, quick, and effective. In this paper, we present the first approach for the automated diagnosis of leakage and blockage defects in flow-based microfluidic biochips. The proposed method targets the identification of fault types and their locations based on test outcomes. It reduces the number of possible fault sites significantly while identifying their exact locations. We use a graph representation of flow paths and a formulation based on hitting sets for the analysis of observed error syndromes. The diagnosis technique is evaluated on three fabricated biochips, and the localization of faults and their classification are achieved correctly in all cases.