Etxetar, leading company supplying high production machining systems, has participated with FORD in the deployment of ZDMP applications. This use case has been developed on the Block machining line at FORD Valencia Engine Plant. The line manufactures more than 3000 blocks per day at full capacity and it is producing 5 different block models.
The objective is to reduce the number of defective parts, improve the availability of the machines and reduce tool and machine consumption costs. For that purpose, four dedicated Etxetar machining centres have been selected for the deployment of the use case.
The health condition of certain critical machine components and the behaviour of the tools during machining have been monitored.
During production, certain variables associated with critical machine components have been acquired and pre-processed with an Edge Computing Node form the company Aingura IIoT, generating a set of monitoring variables for each part produced. These are sent to the ZDMP platform, where they are analysed by the anomaly prediction algorithms and presented to the user through the zAnomalyDetector application.
To assess the condition of the tools, each time a tool works on a part, a series of variables are recorded and pre-processed, generating a new set of variables associated with that tool which is sent to ZDMP for analysis and anomaly detection.
Shows to the user the anomalies detected during a period of time and gives the contribution of each of the variables considered in the AI Model to the anomaly, so that the user can have an idea of which can be the root cause of the issue.