Tracking of Production Data for Smart Process Data Analysis
In times of digitalization the acquisition of process data by production machines themselves is already standard in all industrial sectors. The aim of the Wafer 4.0 project is therefore to implement a major expansion of process measurement technology. A comprehensive sensor extension is the basis for an integrated process monitoring beyond the regular, machine-side process data acquisition. A big data pool will be created in an open source database. In this database each wafer created in the project is recorded with its digital footprint left in the course of the process. Using novel machine learning analysis methods, the data sets can be searched for interesting correlations. The objective is to find new correlations between manufacturing processes (crystallization, wafering, cleaning) and the resulting wafer specification or performance data of the manufactured solar cells. The figure shows an unsuccessful sawing test: Based on the enormous amount of data collected in the project, process artefacts can be clarified, but also quality predictions can be made.