Enhancing data quality and process optimization for smart manufacturing lines in industry 4.0 scenarios

Abstract

An essential component of today's industry is data, which is generated during manufacturing. The goal of industry 4.0 is efficient collection, processing and analysis of this data. In our work, we address these three tasks and present an extensible system to solve them. To the best of our knowledge, the combination of a consistency checker (CC) for data preparation and a digital twin (DT) for analysis activities represents a novel approach. Consistency checking in combination with a DT leads to increased data quality, which in turn has a positive effect on analyses, like reducing errors to decrease costs, identifying relevant parameters to increase the productivity, and determining the bottleneck of a manufacturing line for enhanced production planning.