Tekniker Fingerprint is a fast and automated procedure under controlled conditions for periodic monitoring of the status of machine tools. It consists of a monitoring and management test of machine tool use and condition data that allows knowing the health of critical components and detecting abnormal operating situations early. To collect signals from the controls and sensors, both internal and external, hardware capable of connecting in real time to different CNCs is used. The technological asset is part of Teknker's SmartFactoryHub and is connected to different machines and test benches of the Manufacturing Technologies and Components Laboratories in use. The objective of the analysis of the set of machines / equipment is to better understand the variability of the monitored signals and relate them to the degradation of the monitored components / products. The use of mathematical, statistical and computational models (automatic learning algorithms or ‘machine learning’) allows the generation of knowledge through the ‘data mining’ process in order to estimate / predict anomalous behaviors. These models can be transferred to other machines.
Digitalization and Conectivity
Fingerprint Box (hardware and software for connection and real time monitoring)
Fingerprint Box (hardware and software for connection and real time monitoring)
Fingerprint Test (machine test procedure and software for real-time acquisition)
Fingerprint Test (machine test procedure and software for real-time acquisition)
Smart Factory Hub: Acquisition, storage and exploitation software connected to machines and test benches from Tekniker laboratories
Smart Factory Hub: Acquisition, storage and exploitation software connected to machines and test benches from Tekniker laboratories
Demonstrator of fingerprint procedure and its connection / exploitation in the context of the SmartFactoryHub
Feasibility study of the applicability of the fingerprint to specific machines. Rapid tests of possible configurations and test cycles to assess the solution concept.
Training in concepts of predictive / proactive maintenance of machines and the life cycle of products.