  Many complex activities of production cycles, such as quality control or
fault analysis, require highly experienced specialists to perform various
operations on (semi)finished products using different tools. In practical
scenarios, the selection of a next operation is complicated, since each expert
has only a local view on the total set of operations to be performed. As a
result, decisions made by the specialists are suboptimal and might cause
significant costs. In this paper, we consider a Multi-resource Partial-ordering
Flexible Job-shop Scheduling (MPF-JSS) problem where partially-ordered
sequences of operations must be scheduled on multiple required resources, such
as tools and specialists. The resources are flexible and can perform one or
more operations depending on their properties. The problem is modeled using
Answer Set Programming (ASP) in which the time assignments are efficiently done
using Difference Logic. Moreover, we suggest two multi-shot solving strategies
aiming at the identification of the time bounds allowing for a solution of the
schedule optimization problem. Experiments conducted on a set of instances
extracted from a medium-sized semiconductor fault analysis lab indicate that
our approach can find schedules for 87 out of 91 considered real-world
instances.
