Abstract
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
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(2016, 02). Data Mining Approach For Knowledge-based Process Planning.. ProjectStoc.com. Retrieved 02, 2016, from https://projectstoc.com/read/7172/data-mining-approach-for-knowledge-based-process-planning-8913
"Data Mining Approach For Knowledge-based Process Planning." ProjectStoc.com. 02 2016. 2016. 02 2016 <https://projectstoc.com/read/7172/data-mining-approach-for-knowledge-based-process-planning-8913>.
"Data Mining Approach For Knowledge-based Process Planning.." ProjectStoc.com. ProjectStoc.com, 02 2016. Web. 02 2016. <https://projectstoc.com/read/7172/data-mining-approach-for-knowledge-based-process-planning-8913>.
"Data Mining Approach For Knowledge-based Process Planning.." ProjectStoc.com. 02, 2016. Accessed 02, 2016. https://projectstoc.com/read/7172/data-mining-approach-for-knowledge-based-process-planning-8913.
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