We consider the control of a batch processing machine which is part of a la
rger manufacturing network of machines. Systems consisting of a batch proce
ssing machine and one or more unit-capacity machines in tandem are consider
ed. The objective is to minimize the average time that jobs spend in the en
tire system. We present algorithms to determine the optimal policies for ce
rtain finite horizon, deterministic problems. We then discuss the structure
of the optimal policies for infinite horizon, stochastic problems, and inv
estigate the benefit of utilizing information about upstream and downstream
unit-capacity machines in the control of the batch machine. We develop a s
imple heuristic scheduling policy to control the batch machine which takes
into account the state of other machines in the network. Computational resu
lts demonstrate the effectiveness of our heuristic over a wide range of pro
blem instances.