Data mining approach for knowledge-based process planning

Data mining approach for knowledge-based process planning

Kategorien Konferenz (reviewed)
Jahr 2014
Autoren Denkena, B., Schmidt, J., Krüger, M.:
Veröffentlicht in Thoben, K.-D.; Busse, M.; Denkena, B.; Gausemeier, J. (Eds.): Conference Proceedings of the 2nd International Conference on System-Integrated Intelligence: Challenges for Product and Production Engineering. July 2nd-4th 2014, Bremen, S. 407-416.

Concepts like gentelligent products, smart objects or cyber-physical systems have already proven a high potential especially for decentralized production planning and control. In this context, decentralized communication, new sensor technologies and the increased application of simulation and monitoring systems lead to an enormous increase of manufacturing data. Additionally, a new approach for the assessment of manufacturing quality based on process signals from the machine tool is proposed, which provides current tool state and surface roughness information for every manufacturing process. In order to reuse and evaluate thisdata for knowledge-based process planning, an approach to manufacturing data collection and evaluation using data mining methods was developed. The advantages of the proposed data mining approach for process planning is demonstrated by an exemplary testing case.