Data Model-based Improvement of Transparency and Controllability of Product Complexity

The intelligent gathering, linkage and usage of data and their real-time availability is a central part of “Industrie 4.0”. Moreover, the analysis of data is currently being discussed in research and practice across a wide range of areas, but mainly with focus on production. Improved data availability is not only a relevant factor in production, but also in other areas such as the management of product complexity. A major challenge in this area is the tradeoff between standardization and customer-specific solutions. For this reason, transparency about product complexity is necessary in the first step. However, the available data is only used insufficiently and unstructured for complexity management in companies today. A data-based analysis of product complexity-relevant questions can thus guarantee realtime transparency and controllability of product complexity. There is no systematic and data-based method for improving transparency and controllability of product complexity. This paper deals with the development of a generic procedure for the analysis of product complexity by means of product complexity-relevant questions using a data model. Based on the current state of research, this paper presents a procedure for the data-based analysis of product complexity. Key elements of the procedure are product complexity-relevant questions, key figures, a derived data model and determined visualization requirements.