Digital Product Management

 

The digitization and networking of production increases the availability of data over the entire product life cycle and reveals new potential in the value creation of traditional industries. However, the new competencies and skills required for this are also accompanied by a cultural and structural change in the organization and type of collaboration.

The seminar therefore deals with the area of conflict between traditional mechanical and plant engineering with agile product development and new business models such as Software as a Service. It also addresses the rapidly changing role of domain experts and employees in relation to the systems, processes and products you use. With the shift in the focus of data analysis from reactive and corrective to proactive and predictive, the principles of operating machines and systems remain the same, but actors acting in the production environment need tools, e.g. from the domain of machine learning, to be able to deal with a changed complexity. In order to make informed decisions in human-centered production in the future, user-centered developed digital systems (Smart Quality Expert systems) are required.

Therefore, the basic concepts of Industry 4.0, Machine Learning, Artificial Intelligence and many more will be defined first. In a second step, the differences between classic waterfall-based development methods and the approaches of agile, user-centered development will be examined. From the user's point of view it is important to understand and evaluate the technical solution aspects. In addition to web technologies, these include tools from the fields of data science, data engineering and serverless architecture (cloud). Furthermore, the different sources and systems for data and information in manufacturing companies are addressed. In addition to their structural order (automation pyramid), this also includes the technical and organizational changes currently taking place here. Using consistent examples, the content will be completed and elaborated in small groups along several topic blocks in order to ensure a sustainable learning success based on the student "Do it yourself" work. Use cases from industry underline the theoretical contents at appropriate points.