Towards Test-Driven Model Development in Production Systems Engineering

The correct representation of discipline-specific and cross-specific knowledge in manufacturing contexts is becoming more important due to inter-disciplinary dependencies and overall higher system complexity. However, domain experts do seldom have sufficient technical and theoretical knowledge or adequate tool support required for productive and effective model engineering and validation. Furthermore, increasing competition and faster product lifecycle require the need for parallel collaborative engineering efforts from different workgroups. Thus, test-driven modeling, similar to test-driven software engineering can support the model engineering process to produce high-quality meta and instance models by incorporating consistency and semantic checks during the model engineering. We present a conceptual framework for model transformation with testing and debugging capabilities for production system engineering use cases supporting the modeling of discipline-specific AutomationML instance models. An exemplary workflow is presented and discussed. Debug output for the models is generated to support non-technical engineers in the error detection of discipline-specific models. For future work user-friendly test definition is in planning.