Department of Human-Cyber-Physical Systems (HCPS)
Welcome to the department of Human-Cyber-Physical Systems (HCPS).
The sustainable, human-centered industry of the future will be achieved by a complex combination of
- humans (Human, H),
- digital cyber-systems (Cyber, C), which are, for example, based on new digital technologies and artificial intelligence, and
- physical-technical machines and production facilities (Physical Systems, PS)
For the successful development of Human-Cyber-Physical Systems (HCPS), transdisciplinary research and work are essential so that the insights and strengths of the individual disciplines can be profitably combined in specific applications. In fundamental research, technical development, and for practical implementations within companies, the human being, their expertise, and their needs should be the center of focus. Human cognitive abilities and their formalization in a transparent manner represent a crucial foundation for the design of technical assistance and automation solutions that are meaningful, responsible, and hence sustainable.
The department brings together transdisciplinary expertise and operates at the intersection of psychology, computer science, and mechanical engineering. Its research, which spans both fundamental as well as applied approaches, focuses on fostering human-centered design of HCPS with a clear emphasis on enabling systematic, sustainable, and resource-efficient production for the future.
The department's research work provides theoretical and methodological insights that can be applied to various technical fields of applications and research questions.
This includes, for example, supporting multi-criteria decision-making in surface engineering, the cognition-based design of human-AI-technology systems, the exploration of new assistance and automation solutions such as human-machine teaming, and promoting resource-efficient and sustainable behavior through human-centered measures.
The department collaborates closely with other academic and non-academic research and industry partners to facilitate knowledge transfer.
The department’s key research areas currently encompass the following topics and guiding questions:
(1) Cognitive Engineering:
- Expert knowledge and humans’ cognitive abilities are essential for innovative research, technology development and industrial value creation.
- Examples of research questions: How can domain specific knowledge be captured, described, and sustainably digitized in a human-centered way? Which levels of knowledge need to be distinguished? Which strategies do experts use in their domain to solve problems and make decisions? How can expert strategies be implemented in adaptive systems and how can they be used to empower others?
(2) Knowledge-assisting visualizations:
- Complex technical processes and artificial intelligence algorithms must be task-specific and tailored to the human’s level of knowledge. True human-centeredness therefore requires a minimum level of comprehensibility and transparency, which can, among other things, be achieved through knowledge-assisting representations.
- Examples of research questions: How can data, information, and knowledge be presented in a cognition-based and human-appropriate manner? Which psychological principles are important for designing interfaces and interactions when visualizing complex process flows and multi-layered questions?
(3) Cognitive decision support und human-machine-teaming:
- Complex decision-making, problem-solving, or planning processes should be supported by powerful digital-technical solutions. To this end, viable concepts for new assistance and automation systems need to be developed.
- Examples of research questions: Can and should technology become a “team partner” of humans? Which characteristics of successful human-human teams can be transferred to human-cyber teams and which cannot? How can human teams be cognitively supported when interacting with cyber-physical systems?
(4) Sustainability through technology acceptance and user research:
- New technologies and human-centered measures, such as for sustainable and resource-efficient behavior in everyday production, are only successful if their functionality can be understood, accepted, and implemented by humans.
- Examples of research questions: Which prerequisites exist from users’ perspective for the acceptance of hydrogen-based technologies, such as H2 pedelecs, so that the technologies can be successfully and safely deployed? Which systematic approaches and human-centered measures empower stakeholders to realize sustainability goals in the form of concrete work actions?
Among other things, the following methods are used and developed further:
- observational methods, interviews, psychological experiments, and user studies
- cognitive task analyses, methods for determining (team) situation awareness and mental workload
- eye movement measurement and pupillometry using eye-tracking
- combined data- and knowledge-based modeling of technical processes (e.g., for multi-criteria decision-making and optimization problems) with methods of artificial intelligence
The research provides theoretical and methodological insights that can be applied to various technical fields of application. For example, for supporting multi-criteria decision-making in thermal coating. To this end, the department works closely with other academic and non-academic research and industry partners.
Projects
Project partners
Associated partners
- Fraunhofer IWU Chemnitz
- Continental AG
- secuvera GmbH, BSI-certified IT security service provider and test centre
- Aumann AG, special machines and production lines for electromobility
- SITEC Industrietechnologie GmbH
- IAOV, Institute for Work, Organisation and Transport Research GmbH
- Saxeed, founder network
- Vitesco Technologies GmbH
Sponsor
Federal Ministry of Education and Research (BMBF)
Project period
July 2019 to March 2023
Description
The aim of the project is to develop a technology-oriented range of services and software for the development and realisation of cognition-based interfaces for human-technology interaction (KoMTI). KoMTI will map cognitive-psychological findings (e.g. on understanding and decision-making processes) with machine learning algorithms that are as transparent and powerful as possible in order to enable a new quality of interaction between humans and (partially) autonomous technical/digital systems. The project follows the guiding principle of helpful technology that supports human self-determination and does not control or restrict it. KoMTI is aimed at product developers from the application areas of "intelligent mobility" and "digital society". It addresses new issues, such as the user-centred design of automated driving functions (e.g. in terms of driving comfort) or the optimisation of individual interaction with digital products such as apps (e.g. with regard to interaction errors, data and privacy security). The result of the project is a modular KoMTI method kit and a process strategy for the development and realisation of human-friendly interaction interfaces in complex human-technology systems.
Project demonstrator
Publications and conference papers
Heubeck, L., Hartwich, F., & Bocklisch, F. (2023). To Share or Not to Share-Expected Transportation Mode Changes Given Different Types of Fully Automated Vehicles . Sustainability , 15 (6), 5056.
Kreißig, I., & Bocklisch, F. (2022). Knowledge matters! - Exploring Drivers and Barriers in the Acceptance of FCEVs as a Sustainable Mobility Solution . Paper presented at the 2nd FC³ Fuel Cell Conference Chemnitz, Chemnitz, Germany
Assarzadeh, R., Hartwich, F., Vitay, J. & Bocklisch, F. (2020). Discomfort detection in autonomous driving using artificial neural networks . In C. Dobel, C. Giesen, L. A. Grigutsch, J. M. Kaufmann, G. Kovács, F. Meissner, K. Rothermund, & S. R. Schweinberger (Eds.), TeaP 2020 - Abstracts of the 62nd Conference of Experimental Psychologists (p. 18). Lengerich: Pabst Science Publishers.
Bocklisch, F., Drehmann, R., & Lampke, T. (2020). Kognitionsbasierte Mensch-Technik Interaktion in Cyber-Physischen Systemen am Applikationsbeispiel „Thermisches Spritzen“. MONARCH TU Chemnitz
Bocklisch, F., Kutschmann, P., Drehmann, R., & Lamke, T. (2020). A cognition-based human-machine interaction approach for thermal spraying . In C. Dobel, C. Giesen, L. A. Grigutsch, J. M. Kaufmann, G. Kovács, F. Meissner, K. Rothermund, & S. R. Schweinberger (Eds.), TeaP 2020 - Abstracts of the 62nd Conference of Experimental Psychologists. Lengerich: Pabst Science Publishers
Project partners
Sponsor
Federal Ministry of Education and Research (BMBF)
Project duration
July 2023 to June 2025
Description
The REDUCE project aims to significantly reduce resource consumption in industrial production. It thus addresses the significant share of this sector in the national consumption of resources such as energy (currently approx. 70%) and contributes to (inter)national efforts to make industry more resource-efficient, which is urgently needed in light of the current climate crisis. This goal is achieved through a transdisciplinary approach that combines technology-related digitalisation and efficient automation solutions with a consistently human-centred technology design that enables users to act in a resource-efficient manner in production. In line with this approach, the work plan envisages two complementary analytical approaches, which will be brought together in specific design solutions. On the one hand, modern sensor and measurement technology will be used to create a comprehensive database of all technical parameters relevant to resource consumption at various levels of production, on the basis of which specific potential savings will be identified. On the other hand, a comprehensive process analysis systematically describes the work and process sequences of human actors, from which options for action to reduce consumption are derived. Measures to reduce resource consumption are developed in a systemic view of both analyses and implemented in the form of a demonstrator. The project provides reliable findings on the potential for saving resources in the manufacturing industry through human-centred energy management and information systems. The results have high transfer potential and can be utilised in commercial applications close to industry in addition to scientific dissemination. The transdisciplinary approach of the project is made possible by a consortium with partners from technology and production, visualistics and psychology.
Project lead and contact person
Dr habil. Franziska Bocklisch
Addressing the societal challenges in the field of “Intelligent Industry” requires broad transdisciplinary cooperation among various disciplines, research institutions, and industry partners.
The lecture series “Transdisciplinary Dialogue: Human, Technology, and AI” explores the interaction of humans, technology, and artificial intelligence (AI) from the perspectives of different academic fields. In brief presentations, invited speakers address the human and social perspectives as well as the liberal arts- and STEM-oriented viewpoint, offering insights into specific topics for subsequent discussions.
events
Speakers
- Dr. Norbert Huchler (ISF, Munich): "Sozial nachhaltige Gestaltung der Arbeitsteilung zwischen Mensch und KI" [Socially sustainable design of the division of labour between humans and AI]
- Dr Marcel Todtermuschke (Fraunhofer IWU, Chemnitz): "Herausforderungen bei der Programmierung von Karosseriebauanlagen" [Challenges in programming car body manufacturing systems]
- Dr Mohamad Bdiwi (Fraunhofer IWU, Chemnitz): "From fear to trust in the context of human-heavy-duty robot interaction" [Of the fear to trust in the context of human-heavy-duty robot interaction]
Speakers
- Dr Rudolf Seising (Deutsches Museum, Munich): "Ich denke und vielleicht denkst Du, aber es denkt nicht! Die vergessenen Geschichten der KI" [I think, and maybe you think, but it doesn’t think! The forgotten stories of AI]
- Dr Uwe Haass (Roboconsult, Munich): "Roadmap KI: Perspektiven für Bildung und Forschung am Beispiel der Robotik" [Roadmap AI: Perspectives for Education and Research Using Robotics as an Example]
Contact person
