CRISP-DM

Engineers are often uncertain about the application of machine learning (ML) due to the amount of different machine learning methods and the complexity of modeling. Thus, the use of ML applications in manufacturing companies remains behind the technical possibilities. This paper presents an intuitive ML guideline for engineers to reduce this uncertainty. The guideline comprises a process model with AI-based solutions to common problems of product development and production. An industrial example is used to demonstrate the functionality and the possibilities of the guide.

Internal and external communication is a key success factor for Industrial Data Science (IDS) projects. In particular, complex issues must be prepared and presented comprehensively. Visualization contributes to a uniform and deep understanding of data, processes, models, and results by all parties involved. This article shows the practical benefits of different visualisations for communication and documentation in the respective phases of IDS projects.