Correlation analysis methods in multi-stage production systems for reaching zero-defect manufacturing

Abstract Based on the amount of production steps and the related complexity, multi-stage production systems are very error-prone. In order to compensate for this disadvantage and to achieve zero-defect manufacturing, a data-driven approach is needed. The increasing availability of sensor and machine data provides a high informational content of the individual processes, which can be evaluated with appropriate methods. Literature shows various methods of data analysis for examining the correlations of data sets. These methods and strategies are analyzed, hierarchically structured and extended by four developed algorithms. Finally, the data-driven analysis tool is presented and validated using two industrial use cases.