Description
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 this data 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.
