Annals of DAAAM and Proceedings of the International DAAAM Symposium
The 31st DAAAM International Symposium on Intelligent Manufacturing and Automation was organised as virtual online conference hosted by the University of Mostar, Mostar, Bosnia and Herzegovina, between the 21st and 24th October 2020, during the DAAAM International Week. The Symposium was organized by DAAAM International Vienna in cooperation with ÖIAV 1848, Vienna University of Technology, International Academy of Engineering, University of Mostar and University of Applied Sciences – Technikum Wien and Under the Auspices of the Danube Rectors’ Conference & Rectors’ and Presidents’ Honor Committee of DAAAM International for 2020. This year’s symposium aimed at continuing the success of the previous years, focusing on the five-fold traditional objectives of the symposium: the presentation of the most recent high-quality results, support of development of young scientists and researchers, organization of international (summer) doctoral school, inauguration of new members of Central European Branch of International Academy of Engineering and the provision of the necessary setting for stimulating discussions, brainstorming and networking among European and international researchers coming both from the academia government agencies and industry.
The papers discuss many aspects of modern manufacturing and automation such as: Algorithms, Artificial Intelligence, CAX, Computer Integration, Control, Cutting Tools, Design, FEM, Invited Lectures, Knowledge, Management, Manufacturing System, Mechatronics, Methodology, Methods, Modelling, Optimization, Robotics, Simulation, Technical Solutions, Technology and Trends.
In our application research, we propose a Digital Ecosystem approach to overcome data integration, orchestration and quality challenges in railway reporting system using Big Data technologies. We are building a Digital Ecosystem Framework consisting of different Agents, where each Agent is an essential part of the Railway Reporting Management System. In this work, we address different problems in building digital ecosystem including integration problems, orchestration problems and data quality problems. We present a proprietary solution called the Digital Ecosystem Reporting Framework (DERF) for building robust, reliable, fault-tolerant, scalable and high-loaded data pipelines of the Railway Reporting Management System based on Big Data technologies. DERF integrates different Digital Agents such as main ETL-pipeline Agents, technical data quality Agents, business data quality Agents, BI-services integration Agents and high-level data orchestration Agent. A test implementation of DERF has been performed for Railway Reporting Management System using KPI reporting data of the real Railway company.