  Modern semiconductor manufacturing involves intricate production processes
consisting of hundreds of operations, which can take several months from lot
release to completion. The high-tech machines used in these processes are
diverse, operate on individual wafers, lots, or batches in multiple stages, and
necessitate product-specific setups and specialized maintenance procedures.
This situation is different from traditional job-shop scheduling scenarios,
which have less complex production processes and machines, and mainly focus on
solving highly combinatorial but abstract scheduling problems. In this work, we
address the scheduling of realistic semiconductor manufacturing processes by
modeling their specific requirements using hybrid Answer Set Programming with
difference logic, incorporating flexible machine processing, setup, batching
and maintenance operations. Unlike existing methods that schedule semiconductor
manufacturing processes locally with greedy heuristics or by independently
optimizing specific machine group allocations, we examine the potentials of
large-scale scheduling subject to multiple optimization objectives.
