  Cyber-Physical Production Systems (CPPSs), such as automated car
manufacturing plants, execute a configurable sequence of production steps to
manufacture products from a product portfolio. In CPPS engineering, domain
experts start with manually determining feasible production step sequences and
resources based on implicit knowledge. This process is hard to reproduce and
highly inefficient. In this paper, we present the Extended Iterative Process
Sequence Exploration (eIPSE) approach to derive variability models for
products, processes, and resources from a domain-specific description. To
automate the integrated exploration and configuration process for a CPPS, we
provide a toolchain which automatically reduces the configuration space and
allows to generate CPPS artifacts, such as control code for resources. We
evaluate the approach with four real-world use cases, including the generation
of control code artifacts, and an observational user study to collect feedback
from engineers with different backgrounds. The results confirm the usefulness
of the eIPSE approach and accompanying prototype to straightforwardly configure
a desired CPPS.
