[Zurück]

K. Meixner, R. Rabiser, S. Biffl:
"Feature Identification for Engineering Model Variants in Cyber-Physical Production Systems Engineering";
Vortrag: 14th International Working Conference on Variability Modelling of Software-Intensive Systems (VAMOS 2020), Magdeburg, Deutschland; 05.02.2020 - 07.02.2020; in: "Proceedings of the 14th International Working Conference on Variability Modelling of Software-Intensive Systems", ACM, (2020), ISBN: 978-1-4503-7501-6.

In Cyber-Physical Production System (CPPS) engineering, Assembly Sequence (AS) models of products are primary engineering
artifacts. Product variants are often designed as Product-ProcessResource (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

Feature Extraction, Product Lines, Cyber-Physical Production System (CPPS), Product-Process-Resource (PPR)

http://dx.doi.org/10.1145/3377024.3377043