In selective laser melting, metal powder is melted layer by layer and fused with the already manufactured part. Within this process, defective layers are created, which can be avoided. Such defects can only be detected by various compression and tensile strength experiments after printing is complete. This procedure is costly and inefficient. Therefore, a demonstrator is presented that uses machine learning methods to identify defective layers during the manufacturing process. In addition, the machine operator is supported with decision recommendations.