Feature Identification for Engineering Model Variants in Cyber-Physical Production Systems Engineering

In Cyber-Physical Production System (CPPS) engineering, Assembly Sequence (AS) models of products are primary engineering artifacts. Product variants are often designed as Product-Process-Resource (PPR) AS models that are initiated with clone-and-own approaches and by the manual derivation of shared features. This paper introduces the PPR Feature Candidate Identification (PPR-FCI) approach for identifying features from PPR AS models of product variants. From these features our approach derives a superimposed PPR that describes design options for engineers planning the CPPS. The approach is based on existing feature extraction research which we adapted to the scope of PPR models in CPPS engineering. Based on a real-world product line, we evaluate our PPR-FCI approach for feasibility and usefulness by comparing our automated approach to the traditional manual approach with domain experts. Initial findings show that the approach can identify relevant features from PPR AS models and domain experts found the results useful. However, further research is required to improve the PPR-FCI approach regarding the optimization of PPR Assembly Sequence models.