Intelligent Pattern Recognition of a SLM Machine Process and Sensor Data

Abstract Selective Laser Melting is an additive manufacturing process, in which the research has been increasing over the past few years to meet customer-specific requirements. Therefore, new manufacturing parameters have been monitored raising the number of sensors in the machines. Consequently, it leads to a bigger amount of data and difficulties to perform manual data analysis. In order to improve the analysis, this paper illustrates a possibility of pattern recognition using a different historical process and sensors data from a SLM machine. The results are evaluated using an intelligent tool for algorithms configuration and data analysis developed at Fraunhofer IPK.