A parallel algorithm for robust fault detection in semiconductor manufacturing processes

The semiconductor manufacturing consists of a number of processes, and even a small fault occurring at any point can damage the product quality. The fast and accurate detection of such faults is essential to maintain high manufacturing yields. In this paper, we propose a parallel algorithm for fault detection in semiconductor manufacturing processes. The algorithm is a modification of the discord detection algorithm called HOT SAX, which adopted the SAX representation of time-series for efficient storage and computation. We first propose a sequential algorithm and then extend it to a parallel version. We evaluate our algorithm through experiments using the data obtained from a real-world semiconductor plasma etching process. As a result, our fault detection algorithm achieved 100 % accuracy without any false positive or false negative.

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