@inproceedings{evers2019roadmap, author = {Evers, Kathrin and Seyler, Jan R and Aravantinos, Vincent and L{\'{u}}cio, Levi and Mehdi, Anees}, title = {Roadmap to Skill Based Systems Engineering}, booktitle = {24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)}, publisher = {IEEE}, pages = {1093--1100}, year = {2019}, abstract = {Finding the right solution for a given automation problem is one of the biggest challenges for customers of industrial control and automation companies. This search needs to address customers’ demands and preferences such as cost-effectiveness, energy-consumption, durability, working space, etc. Consequently, solutions may comprise different products of different providers. This leads to an enormous search space of diverse potential solutions. As of today, the search process involves human effort. Thus, a good understanding of system engineering is required not only on the manufacturer side but on the customer side as well. Furthermore, integration and configuration of the products into a functional system needs extra effort.In this paper, we present our first ideas on reducing the complexity of this search task. Our approach is laid out in three layers: (i) a customer only needs to describe their desired automation application on an abstract level. (ii) manufacturers need to categorize their products as per functionality and characteristics. (iii) the linking between the requirements as per customer’s description to relevant products is done automatically.This paper provides a roadmap for the research necessary to implement these three layers in practice. We lay out the essential research questions and provide a conceptual division of the work, thus pointing out the challenges that need to be solved to allow for further automation in this area.}, doi = {10.1109/ETFA.2019.8869534}, keywords = {Model-based Systems Engineering, MbSE}, }