Test planning and test resource optimization For droplet-based microfluidic systems

Recent years have seen the emergence of droplet-based microfluidic systems for safety-critical biomedical applications. In order to ensure reliability, microsystems incorporating microfluidic components must be tested adequately. In this paper, we investigate test planning and test resource optimization for droplet-based microfluidic arrays. We first formulate the test planning problem and prove that it is NP-hard. We then describe an optimization method based on integer linear programming (ILP) that yields optimal solutions. Due to the NP-hard nature of the problem, we develop heuristic approaches for optimization. Experimental results indicate that for large array sizes, the heuristic methods yield solutions that are close to provable lower bounds. These heuristics ensure scalability and low computation cost.