Entwicklung einer Ontologie-basierten Entscheidungsunterstützung für die mechanische Fertigung im Werkzeugbau

Toolmaking is characterized by complex manufacturing processes and the absence of repetition effects. Due to its central position in the product life cycle, toolmaking acts both as a driver of innovation and as a source of productivity increases in series production. The use of heterogeneous manufacturing technologies requires a deep understanding of technology along the entire value chain. This results in activities that require the expertise of experienced employees. This applies in particular to know-how-intensive areas such as design, CAM programming and work preparation in mechanical production. There is currently no comprehensive system support in these areas and the knowledge required for planning activities is predominantly available in the form of implicit specialist knowledge and experience. A shortage of qualified workers is particularly problematic in the manufacture of highly complex tools. A comparison of the development of the age structure in recent decades illustrates the advancing demographic change. The age structures in toolmaking are following this trend. The average age of all employees in the German-speaking toolmaking industry is 42. This represents a major risk for companies in the form of a loss of expertise. An ontology-based decision support system was developed as part of this thesis. This enables companies to utilize existing expert and empirical knowledge in the context of technology selection in mechanical production. The developed methodology enables a holistic integration of implicitly existing technical and empirical knowledge in an early phase of modeling an ontology. The developed iterative approach takes into account the characteristics of toolmaking and focuses in particular on knowledge acquisition. For this purpose, a systematic procedure was developed that enables a requirements-oriented selection of suitable quantitative and qualitative methods. An integrated requirements analysis was used to determine which sources and which types of existing knowledge are relevant and necessary in companies in order to serve as a basis for ontology-based decision support. Based on the findings, a maturity model for knowledge carriers was developed and a detailed process model for the collection and evaluation of knowledge was derived. A detailed procedure was then designed to describe the toolmaking domain and the specific interrelationships in a holistic manner. Based on this, a detailed ontology was modeled that systematically maps the identified specialist and empirical knowledge. Finally, a framework was developed that creates the basis for the efficient use of the knowledge. A graphical user interface was developed to enable the prototypical decision support to be used in an industry-related environment.