Architecture-based change impact analysis in cross-disciplinary automated production systems

Maintaining an automated production system is a challenging task as it comprises artifacts from multiple disciplines - namely mechanical, electrical, and software engineering. As the artifacts mutually affect each other, even small modifications may cause extensive side effects. Consequently, estimating the maintenance effort for modifications in an automated production system precisely is time consuming and often nearly as complicated as implementing the modifications. In this paper, we present the KAMP4aPS approach for architecture-based change impact analysis in production automation. We propose metamodels to specify the various artifacts of the system and modifications to them, as well as algorithms and rules for change propagation analysis based on the models. We evaluate KAMP4aPS for three different change scenarios based on the established xPPU community case study on production automation. In the case study, we investigate different configurations of metamodels and change propagation rules. Evaluation results indicate the accuracy of change propagation for applying KAMP4aPS to the specific metamodel and rules.