Scheduling for Dedicated Machine Constraint

Abstract

We have proposed the heuristic Load Balancing (LB) scheduling (Shr et al., 2006a) (Shr et al., 2006b) (Shr et al., 2006c) and Multiagent Scheduling System (MSS) (Shr, et al. 2006d) approaches to provide solutions to the issue of dedicated photolithography machine constraint. The dedicated photolithography machine constraint, which is caused by the natural bias of the photolithography machine, is a new challenge in the semiconductor manufacturing systems. Natural bias will impact the alignment of patterns between different layers. This is especially true for smaller dimension IC for high technology products. A study considered different production control policies for semiconductor manufacturing, including a “machine dedication policy” in their simulation, has reported that the scheduling policy with machine dedication had the worst performance of photolithography process (Akcalt et al., 2001). The machine dedication policy reflects the constraint we are discussing here. In our previous work, along with providing the LB scheduling or MSS approaches to the dedicated machine constraint, we have also presented a novel model––the Resource Schedule and Execution Matrix (RSEM) framework. This knowledge representation and manipulation method can be used to tackle the dedicated machine constraint. A simulation system has also been implemented in these researches and we have applied our proposed scheduling approaches to compare with the Least Slack (LS) time approach in the simulation system (Kumar & Kumar, 2001). The reason for choosing the LS scheduling approach was that this approach was the most suitable method for solving the types of problems caused by natural bias at the time of our survey. The LS scheduling approach has been developed in the research of Fluctuation Smoothing Policy for Mean Cycle Time (FSMCT) (Kumar & Kumar, 2001), in which the FSMCT scheduling policy is for the re-entrant production lines. The entire class of the LS scheduling policies has been proven stable in a deterministic setting (Kumar, 1994) (Lu & Kumar, 1991). The LS approach sets the highest priority to a wafer lot whose slack time is the smallest in the queue buffer of one machine. When the machine becomes idle, it selects the highest priority wafer lot in the queue buffer to service next. However, the simulation result has shown that the performances of both our proposed LB and MSS approaches were better than the LS method. Although the simulations were simplified, they have reflected the real situation we have met in the factory. O pe n A cc es s D at ab as e w w w .ite ch on lin e. co m