Author:
Schäffer Eike,Gönnheimer Philipp,Kupzik Daniel,Brossog Matthias,Coutandin Sven,Franke Jörg,Fleischer Jürgen
Abstract
AbstractAutomation solutions in production represent a sensible and long-term cost-effective alternative to manual work, especially for physically strenuous or dangerous activities. However, especially for small companies, automation solutions are associated with a considerable initial complexity and a high effort in planning and implementation. The ROBOTOP project, a consortium of industrial companies and research institutes has therefore developed a flexible web platform for the simplified, modular planning and configuration of robot-based automation solutions for frequent tasks. In this paper, an overview of the project’s scientific findings and the resulting platform is given. Therefore, challenges due to the scope of knowledge-based engineering configurators like the acquisition of necessary data, its description, and the graphical representation are outlined. Insights are given into the platform’s functions and its technical separation into different Microservices such as Best Practice selection, configuration, simulation, AML-data-exchange and spec-sheet generator with the focus on the configuration. Finally, the user experience and potentials are highlighted.
Publisher
Springer International Publishing
Reference30 articles.
1. Bartelt, M., Stecken, J., Kuhlenkötter, B.: Microservice zur Erzeugung von digitalen Zwillingen. Seamless Convergence of Automation & IT : Automation: Baden-Baden. 679–690 (2018)
2. Blažek, P., Kolb, M., Streichsbier, C., et al.: The evolutionary process of product configurators. In: Bellemare J, Carrier S, Nielsen K et al (eds) Managing complexity. In: Proceedings of the 8th World Conference on Mass Customization, Personalization, and Co-Creation. Springer International Publishing, pp. 161–172 (2017)
3. Dackweiler, M., Krause, M., Coutandin, S., et al.: Konfiguration Von Robotiklösungen. VDI-Z 8, 62–65 (2019)
4. Felfernig, A., Hotz, L., Bagley, C., et al.: Knowledge-based configuration: From research to business cases. Morgan Kaufmann, Waltham, MA (2014)
5. Fleischanderl, G., Friedrich, G.E., Haselböck, A., et al.: Configuring large systems using generative constraint satisfaction. IEEE Intell. Syst. 13, 59–68 (1998). https://doi.org/10.1109/5254.708434