Optimizing close-down processes of single-robot cluster tools via linear programing

In a cluster tool, periodical maintenance and lot switching operations require that the tool should be emptied from time to time. Thus, it is very important to optimize a normal close-down process from the steady state to the idle state. Besides, process modules (PMs) are prone to failure. When a PM at a step without any other parallel PMs fails, the tool cannot complete the entire process of any new wafer and some already in the tool. We need to close down the tool to empty it as well. Optimal scheduling of a close-down process is important yet challenging. Wafer residency time constraints make it even more challenging. By assuming no parallel PM at a step, this work focuses on time-constrained single-arm cluster tools in order to optimize their close-down process with and without PM failure. It first develops a linear program to optimize a normal close-down process. It then presents PM failure control rules to deal with the wafer in a failed PM and develops one more linear program to find an optimal schedule for the close-down process with PM failure. This work finally gives a real industrial case to show the new research results.