This contribution introduces an educational Product Lifecycle Management (PLM) curriculum suitable for undergraduate and young professionals, which enables a graduation as Master of Science. The main goal is to increase the accessibility of valuable PLM content for educational purposes and to introduce students to the productive “hands on” features of PLM by developing an international, interdisciplinary and online-based program. This program focusses on a fundamental PLM understanding, the usability of available software systems and an industrial PLM integration and application. A highly professional cooperation between five technical universities from Turkey, Spain, Germany and Austria, international experts designed interactive online classes, which are suitable for distance learning. Sharing technology for international educational platform enables students, professors and partners from industry to share their PLM expertise with students and improve the common and different understandings. This new PLM program shows the usability of the applications, which were implemented and tested in a pilot training course. The results are very promising and further suggestions and feedback for improvement will be taken in to account. Student feedback and the exceptional motivation of the whole project team shows that interdisciplinary online education has a promising future in international academic PLM education integrating practical use cases.

Collaborative design is a key element in Product/System development. However, delivering true collaboration in multidisciplinary teams is challenging. Feedback systems are one of the solutions to improve collaboration; although teams normally receive feedback on outcomes, the collaboration process itself is neglected. During a PBL course, 40 engineers from 22 disciplines and 12 countries were distributed in six teams. In addition to receiving outcome feedback, we used Motivational Interviewing (MI) techniques to provide process feedback for half of the design teams whereas the other half only received outcome feedback. At the same time, we employed a pre-trained Machine Learning (ML) technique to compare the teams’ progress through teams’ communication and sentiment analysis. Our results show that; (i) adding process feedback in the early stages of the design process enhances the collaborative design. (ii) ML algorithms can predict the progress. We suggest further research using Natural Language Processing (NLP) and supervised ML techniques for designing a new AI team-mate and mentoring assistant, as well as fostering Human-AI interaction styles via MI methods.

This publication aims to explore the concept of human-centric manufactur-ing systems and the skills necessary for its implementation and promotion. Through a series of workshops, the objective of this research is to gain a deeper understanding of what constitutes a human-centric manufacturing system and the human elements that play a crucial role in its successful re-alization. The results of the workshops will provide insights into the skills and knowledge required for the design, development, and implementation of human-centric manufacturing systems, including an understanding of the different functional units inside an organization, as well as the importance of collaboration and communication among all stakeholders involved. Ad-ditionally, through a design thinking approach, the workshops will also explore the challenges and opportunities of the human-centric manufactur-ing system with a focus on the role of human factors in driving innovation and competitiveness. The findings of this study will contribute to the de-velopment of strategies for promoting the transition from an Industry 4.0 to an Industry 5.0 manufacturing system.