This paper discusses a scheduling technique, for cluster tools, that addres
ses postprocessing residency constraints and throughput requirements. The r
esidency constraints impose a limit on the postprocessing time that a mater
ial unit spends in a processing module. The technique searches in the time
and resource domains for a feasible schedule with a maximum throughput. It
operates in two main phases; the initial one of which (and the lower comple
xity one) computes a simple periodic schedule. For a large number of proble
m instances, the simple periodic schedule feasibly solves the problem. If a
feasible schedule cannot be found in the first phase, the scheduler enters
phase two (the higher complexity one) to compute a feasible schedule. Duri
ng this phase, the scheduler incrementally increases the period only if nec
essary, to keep the throughput at a maximum. Several heuristics are designe
d and added to reduce the complexity of the scheduling algorithm. The resul
ting schedules are deadlock free, since resources are scheduled according t
o the times that they are available. Analytical and experimental analyzes d
emonstrate the correctness and efficiency of our proposed technique.