Doctoral College Cyber-Physical Production Systems at TU Wien
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Cyber-Physical Production Systems (CPPS), such as industrial production plants, are typically the result of complex, multi-disciplinary engineering processes that require the seamlessly orchestrated collaboration of several engineering disciplines, such as mechanical, electrical, and software engineering. In these software and systems engineering environments, the work of (software) engineers depends on the inputs from other engineering disciplines, e.g., requirements incorporated in a range of engineering models. It is therefore critical to systematically support the multi-disciplinary engineering processes of CPPS and to ensure a high-quality output of these processes through the early detection and future prevention of defects that delay the development and increase the operational risks of CPPS. Major challenges for improving multi-disciplinary engineering processes are the heterogeneous representations, weak accumulation and integration of the dispersed, local engineering knowledge necessary for the development and validation of CPPS as well as its effective coordination and sharing between multi-disciplinary engineering teams in the organization.

Therefore, in the context of this PhD research, these challenges will be addressed by focusing on the empirically-grounded investigation of how to enhance (software) engineering methods and tools with collective intelligence (CI) to overcome aggregation, coordination and communication complexities of distributed knowledge in large, multi-disciplinary projects such as the engineering of CPPS and to provide awareness and efficient management of business-critical knowledge. To that end, basic concepts, principles, and models of software architectures for CI-enhanced information systems will be explored. Their application to build new systems with CI capabilities for industrial contexts will be evaluated within the Christian Doppler research laboratory on "Software Engineering Integration for Flexible Automation Systems" (CDL-Flex), with the goal to facilitate sustainable CPPS engineering process improvement on local and organization-wide levels. In order to effectively and efficiently tailor information systems with CI capabilities needed to support the business needs of a specific context or domain, this research especially aims to provide a comprehensive classification and a variability modeling method of CI systems that support software architects with design and trade-off analysis of CI system families and their evolution. The evaluation of the proposed models and methods is planned in the context of existing systems and several multi-disciplinary projects of industry partners as a basis for engineering future CPPS.

PhD-Student and Supervision

PhD-Student: Angelika Musil, B. Sc., DI / M. Sc. (Software Engineering)

Following her studies in Software Engineering at TU Vienna, Angelika Musil is a PhD student at the Christian Doppler research laboratory on "Software Engineering Integration for Flexible Automation Systems" (CDL-Flex) of the Institute of Software Technology and Interactive Systems. As part of the PhD, she will investigate basic concepts, principles and models of software architectures to enable and coordinate distributed collective work and knowledge sharing among users, and their application to build novel Collective Intelligence-enhanced tools for industries and high-impact application domains. Her major research interests include systematic software architecture design in general, and software architectures and analysis of collective intelligence systems in particular, their classification and measurement, its relation to human computation and crowdsourcing systems, as well as empirical software engineering.


Advisor: Prof. Dr. Stefan Biffl, CDL-Flex (E188)

Co-Supervisor: Dr. Marta Sabou, CDL-Flex (E188)