Data-based process analysis in machining production: Case study for quality determination in a drilling process

Abstract

The rush of new providers of Industrial Internet of Things solutions and machine learning applications onto the market opens up new possibilities for data acquisition and analysis that go beyond the classical approach of model- and empirical-based process analysis. In this context, classic production tasks, e.g. quality assurance by random sampling, should be critically reviewed for their relevance. These non-value-adding activities can potentially be eliminated by disruptive digitalisation in order to increase labour productivity. This paper showcases the potential of a data-driven approach for quality determination in a drilling process using machine control data.