Abstract
Furnaces are commonly seen in the front-end to the middle portion of the semiconductor process flow and their scheduling plays a key role in semiconductor manufacturing. Job scheduling of furnaces needs to meet the daily production targets while adhering to job due dates and process constraints. The furnace scheduling problem belongs to a special class of flexible job-shop scheduling with complicated constraints including but not limited to batch processing, reentrance, and time-windows. This problem is NP-hard. The extremely large solution space prevents any straightforward application of optimization techniques. In this paper, several properties are identified to reduce the solution space based on a dynamic programming formulation. With the help of these properties, an efficient algorithm has been developed to find a good solution to this problem. The developed method has been implemented in practical production lines. Compared with existing methods, the developed algorithm gives a higher throughput rate and improves the scheduling efficiency.
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